@article{JiangWangRabczuk, author = {Jiang, Jin-Wu and Wang, Bing-Shen and Rabczuk, Timon}, title = {Why twisting angles are diverse in graphene Moir'e patterns?}, series = {Journal of Applied Physics}, journal = {Journal of Applied Physics}, abstract = {Why twisting angles are diverse in graphene Moir'e patterns?}, subject = {Angewandte Mathematik}, language = {en} } @inproceedings{AhmadZabelKoenke, author = {Ahmad, Sofyan and Zabel, Volkmar and K{\"o}nke, Carsten}, title = {WAVELET-BASED INDICATORS FOR RESPONSE SURFACE MODELS IN DAMAGE IDENTIFICATION OF STRUCTURES}, series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 04 - 06 2012, Bauhaus-University Weimar}, booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 04 - 06 2012, Bauhaus-University Weimar}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2758}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170306-27588}, pages = {14}, abstract = {In this paper, wavelet energy damage indicator is used in response surface methodology to identify the damage in simulated filler beam railway bridge. The approximate model is addressed to include the operational and surrounding condition in the assessment. The procedure is split into two stages, the training and detecting phase. During training phase, a so-called response surface is built from training data using polynomial regression and radial basis function approximation approaches. The response surface is used to detect the damage in structure during detection phase. The results show that the response surface model is able to detect moderate damage in one of bridge supports while the temperatures and train velocities are varied.}, subject = {Angewandte Mathematik}, language = {en} } @phdthesis{Alkam, author = {Alkam, Feras}, title = {Vibration-based Monitoring of Concrete Catenary Poles using Bayesian Inference}, volume = {2021}, publisher = {Bauhaus-Universit{\"a}tsverlag}, address = {Weimar}, doi = {10.25643/bauhaus-universitaet.4433}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210526-44338}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {177}, abstract = {This work presents a robust status monitoring approach for detecting damage in cantilever structures based on logistic functions. Also, a stochastic damage identification approach based on changes of eigenfrequencies is proposed. The proposed algorithms are verified using catenary poles of electrified railways track. The proposed damage features overcome the limitation of frequency-based damage identification methods available in the literature, which are valid to detect damage in structures to Level 1 only. Changes in eigenfrequencies of cantilever structures are enough to identify possible local damage at Level 3, i.e., to cover damage detection, localization, and quantification. The proposed algorithms identified the damage with relatively small errors, even at a high noise level.}, subject = {Parameteridentifikation}, language = {en} } @phdthesis{Brehm2011, author = {Brehm, Maik}, title = {Vibration-based model updating: Reduction and quantification of uncertainties}, doi = {10.25643/bauhaus-universitaet.1465}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20110926-15553}, school = {Bauhaus-Universit{\"a}t Weimar}, year = {2011}, abstract = {Numerical models and their combination with advanced solution strategies are standard tools for many engineering disciplines to design or redesign structures and to optimize designs with the purpose to improve specific requirements. As the successful application of numerical models depends on their suitability to represent the behavior related to the intended use, they should be validated by experimentally obtained results. If the discrepancy between numerically derived and experimentally obtained results is not acceptable, a model revision or a revision of the experiment need to be considered. Model revision is divided into two classes, the model updating and the basic revision of the numerical model. The presented thesis is related to a special branch of model updating, the vibration-based model updating. Vibration-based model updating is a tool to improve the correlation of the numerical model by adjusting uncertain model input parameters by means of results extracted from vibration tests. Evidently, uncertainties related to the experiment, the numerical model, or the applied numerical solving strategies can influence the correctness of the identified model input parameters. The reduction of uncertainties for two critical problems and the quantification of uncertainties related to the investigation of several nominally identical structures are the main emphases of this thesis. First, the reduction of uncertainties by optimizing reference sensor positions is considered. The presented approach relies on predicted power spectral amplitudes and an initial finite element model as a basis to define the assessment criterion for predefined sensor positions. In combination with geometry-based design variables, which represent the sensor positions, genetic and particle swarm optimization algorithms are applied. The applicability of the proposed approach is demonstrated on a numerical benchmark study of a simply supported beam and a case study of a real test specimen. Furthermore, the theory of determining the predicted power spectral amplitudes is validated with results from vibration tests. Second, the possibility to reduce uncertainties related to an inappropriate assignment for numerically derived and experimentally obtained modes is investigated. In the context of vibration-based model updating, the correct pairing is essential. The most common criterion for indicating corresponding mode shapes is the modal assurance criterion. Unfortunately, this criterion fails in certain cases and is not reliable for automatic approaches. Hence, an alternative criterion, the energy-based modal assurance criterion, is proposed. This criterion combines the mathematical characteristic of orthogonality with the physical properties of the structure by modal strain energies. A numerical example and a case study with experimental data are presented to show the advantages of the proposed energy-based modal assurance criterion in comparison to the traditional modal assurance criterion. Third, the application of optimization strategies combined with information theory based objective functions is analyzed for the purpose of stochastic model updating. This approach serves as an alternative to the common sensitivity-based stochastic model updating strategies. Their success depends strongly on the defined initial model input parameters. In contrast, approaches based on optimization strategies can be more flexible. It can be demonstrated, that the investigated nature inspired optimization strategies in combination with Bhattacharyya distance and Kullback-Leibler divergence are appropriate. The obtained accuracies and the respective computational effort are comparable with sensitivity-based stochastic model updating strategies. The application of model updating procedures to improve the quality and suitability of a numerical model is always related to additional costs. The presented innovative approaches will contribute to reduce and quantify uncertainties within a vibration-based model updating process. Therefore, the increased benefit can compensate the additional effort, which is necessary to apply model updating procedures.}, subject = {Dynamik}, language = {en} } @article{DoeringHoffmeyerSeegeretal., author = {D{\"o}ring, R. and Hoffmeyer, J. and Seeger, T. and Vormwald, Michael}, title = {Verformungsverhalten und rechnerische Absch{\"a}tzung der Erm{\"u}dungslebensdauer metallischer Werkstoffe unter mehrachsig nichtproportionaler Beanspruchung}, series = {Materialwissenschaft und Werkstofftechnik}, journal = {Materialwissenschaft und Werkstofftechnik}, pages = {280 -- 288}, abstract = {Verformungsverhalten und rechnerische Absch{\"a}tzung der Erm{\"u}dungslebensdauer metallischer Werkstoffe unter mehrachsig nichtproportionaler Beanspruchung}, subject = {Angewandte Mathematik}, language = {de} } @article{LahmerIlgLerch, author = {Lahmer, Tom and Ilg, J. and Lerch, Reinhard}, title = {Variance-based sensitivity analyses of piezoelectric models}, series = {Computer Modeling in Engineering \& Sciences}, journal = {Computer Modeling in Engineering \& Sciences}, pages = {105 -- 126}, abstract = {Variance-based sensitivity analyses of piezoelectric models}, subject = {Angewandte Mathematik}, language = {en} } @article{FaizollahzadehArdabiliNajafiAlizamiretal., author = {Faizollahzadeh Ardabili, Sina and Najafi, Bahman and Alizamir, Meysam and Mosavi, Amir and Shamshirband, Shahaboddin and Rabczuk, Timon}, title = {Using SVM-RSM and ELM-RSM Approaches for Optimizing the Production Process of Methyl and Ethyl Esters}, series = {Energies}, journal = {Energies}, number = {11, 2889}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/en11112889}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181025-38170}, pages = {1 -- 20}, abstract = {The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86\% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. \%, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46\% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. \%, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6\% for ethyl ester and 3.1\% for methyl ester, compared with those for the experimental data.}, subject = {Biodiesel}, language = {en} } @misc{Nikulla2008, author = {Nikulla, Susanne}, title = {Untersuchung des dynamischen Verhaltens von Eisenbahnbr{\"u}cken bei wechselnden Umweltbedingungen}, doi = {10.25643/bauhaus-universitaet.1356}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20081020-14324}, year = {2008}, abstract = {Im Zuge des Ausbaus von Eisenbahnstrecken f{\"u}r den Hochgeschwindigkeitsverkehr muss sichergestellt werden, dass keine Resonanz zwischen den periodisch einwirkenden Radlasten und den Br{\"u}ckeneigenfrequenzen entsteht. Bei der Untersuchung einzelner Bauwerke wurden teilweise recht große Schwankungen des dynamischen Verhaltens im Verlauf der Jahreszeiten festgestellt. Um diese Beobachtungen zu pr{\"a}zisieren, wurden an zwei ausgew{\"a}hlten Walztr{\"a}ger-in-Beton-Br{\"u}cken {\"u}ber den Zeitraum von 15 Monaten Beschleunigungsmessungen durchgef{\"u}hrt. Die gewonnenen Daten wurden mit der Stochastic Subspace Methode, die im ersten Teil der Arbeit n{\"a}her erl{\"a}utert wird, ausgewertet. Es konnte f{\"u}r alle Eigenmoden ein Absinken der Eigenfrequenz bei steigender Temperatur beobachtet werden. Um die Ursachen hierf{\"u}r genauer zu untersuchen, wurde f{\"u}r eine der beiden Br{\"u}cken ein Finite-Elemente-Modell mit dem Programm SLang erstellt. Mittels einer Sensitivit{\"a}tsanalyse wurden die f{\"u}r das Schwingverhalten maßgebenden Systemeigenschaften identifiziert. Die anschließend durchgef{\"u}hrte Strukturoptimierung unter Nutzung des genetischen Algorithmus sowie des adaptiven Antwortfl{\"a}chenverfahrens konnte die Temperaturabh{\"a}ngigkeit einzelner Materialparameter aufzeigen, die zumindest eine Ursache f{\"u}r Schwankungen der Eigenfrequenzen darstellen.}, subject = {Dynamik}, language = {de} } @article{IlyaniAkmarLahmerBordasetal., author = {Ilyani Akmar, A.B. and Lahmer, Tom and Bordas, St{\´e}phane Pierre Alain and Beex, L.A.A. and Rabczuk, Timon}, title = {Uncertainty quantification of dry woven fabrics: A sensitivity analysis on material properties}, series = {Composite Structures}, journal = {Composite Structures}, doi = {10.1016/j.compstruct.2014.04.014}, pages = {1 -- 17}, abstract = {Uncertainty quantification of dry woven fabrics: A sensitivity analysis on material properties}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacRafieeZhuangetal., author = {Vu-Bac, N. and Rafiee, Roham and Zhuang, Xiaoying and Lahmer, Tom and Rabczuk, Timon}, title = {Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters}, series = {Composites Part B: Engineering}, journal = {Composites Part B: Engineering}, pages = {446 -- 464}, abstract = {Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters}, subject = {Angewandte Mathematik}, language = {en} } @article{GoebelLahmerOsburg, author = {G{\"o}bel, Luise and Lahmer, Tom and Osburg, Andrea}, title = {Uncertainty analysis in multiscale modeling of concrete based on continuum micromechanics}, series = {European Journal of Mechanics-A/Solids}, journal = {European Journal of Mechanics-A/Solids}, abstract = {Uncertainty analysis in multiscale modeling of concrete based on continuum micromechanics}, subject = {Angewandte Mathematik}, language = {en} } @article{GhasemiRafieeZhuangetal., author = {Ghasemi, Hamid and Rafiee, Roham and Zhuang, Xiaoying and Muthu, Jacob and Rabczuk, Timon}, title = {Uncertainties propagation in metamodel-based probabilistic optimization of CNT/polymer composite structure using stochastic multi-scale modeling}, series = {Computational Materials Science}, journal = {Computational Materials Science}, pages = {295 -- 305}, abstract = {Uncertainties propagation in metamodel-based probabilistic optimization of CNT/polymer composite structure using stochastic multi-scale modeling}, subject = {Angewandte Mathematik}, language = {en} } @inproceedings{JaouadiLahmer, author = {Jaouadi, Zouhour and Lahmer, Tom}, title = {Topology optimization of structures subjected to multiple load cases by introducing the Epsilon constraint method}, series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, editor = {G{\"u}rlebeck, Klaus and Lahmer, Tom}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2804}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28042}, pages = {7}, abstract = {A topology optimization method has been developed for structures subjected to multiple load cases (Example of a bridge pier subjected to wind loads, traffic, superstructure...). We formulate the problem as a multi-criterial optimization problem, where the compliance is computed for each load case. Then, the Epsilon constraint method (method proposed by Chankong and Haimes, 1971) is adapted. The strategy of this method is based on the concept of minimizing the maximum compliance resulting from the critical load case while the other remaining compliances are considered in the constraints. In each iteration, the compliances of all load cases are computed and only the maximum one is minimized. The topology optimization process is switching from one load to another according to the variation of the resulting compliance. In this work we will motivate and explain the proposed methodology and provide some numerical examples.}, subject = {Angewandte Informatik}, language = {en} } @article{NanthakumarLahmerZhuangetal., author = {Nanthakumar, S.S. and Lahmer, Tom and Zhuang, Xiaoying and Park, Harold S. and Rabczuk, Timon}, title = {Topology optimization of piezoelectric nanostructures}, series = {Journal of the Mechanics and Physics of Solids}, journal = {Journal of the Mechanics and Physics of Solids}, pages = {316 -- 335}, abstract = {Topology optimization of piezoelectric nanostructures}, subject = {Angewandte Mathematik}, language = {en} } @article{AlemuHabteLahmeretal., author = {Alemu, Yohannes L. and Habte, Bedilu and Lahmer, Tom and Urgessa, Girum}, title = {Topologically preoptimized ground structure (TPOGS) for the optimization of 3D RC buildings}, series = {Asian Journal of Civil Engineering}, volume = {2023}, journal = {Asian Journal of Civil Engineering}, publisher = {Springer International Publishing}, address = {Cham}, doi = {10.1007/s42107-023-00640-2}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20230517-63677}, pages = {1 -- 11}, abstract = {As an optimization that starts from a randomly selected structure generally does not guarantee reasonable optimality, the use of a systemic approach, named the ground structure, is widely accepted in steel-made truss and frame structural design. However, in the case of reinforced concrete (RC) structural optimization, because of the orthogonal orientation of structural members, randomly chosen or architect-sketched framing is used. Such a one-time fixed layout trend, in addition to its lack of a systemic approach, does not necessarily guarantee optimality. In this study, an approach for generating a candidate ground structure to be used for cost or weight minimization of 3D RC building structures with included slabs is developed. A multiobjective function at the floor optimization stage and a single objective function at the frame optimization stage are considered. A particle swarm optimization (PSO) method is employed for selecting the optimal ground structure. This method enables generating a simple, yet potential, real-world representation of topologically preoptimized ground structure while both structural and main architectural requirements are considered. This is supported by a case study for different floor domain sizes.}, subject = {Bodenmechanik}, language = {en} } @phdthesis{Nickerson, author = {Nickerson, Seth}, title = {Thermo-Mechanical Behavior of Honeycomb, Porous, Microcracked Ceramics}, doi = {10.25643/bauhaus-universitaet.3975}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190911-39753}, school = {Bauhaus-Universit{\"a}t Weimar}, abstract = {The underlying goal of this work is to reduce the uncertainty related to thermally induced stress prediction. This is accomplished by considering use of non-linear material behavior, notably path dependent thermal hysteresis behavior in the elastic properties. Primary novel factors of this work center on two aspects. 1. Broad material characterization and mechanistic material understanding, giving insight into why this class of material behaves in characteristic manners. 2. Development and implementation of a thermal hysteresis material model and its use to determine impact on overall macroscopic stress predictions. Results highlight microcracking evolution and behavior as the dominant mechanism for material property complexity in this class of materials. Additionally, it was found that for the cases studied, thermal hysteresis behavior impacts relevant peak stress predictions of a heavy-duty diesel particulate filter undergoing a drop-to-idle regeneration by less than ~15\% for all conditions tested. It is also found that path independent heating curves may be utilized for a linear solution assumption to simplify analysis. This work brings forth a newly conceived concept of a 3 state, 4 path, thermally induced microcrack evolution process; demonstrates experimental behavior that is consistent with the proposed mechanisms, develops a mathematical framework that describes the process and quantifies the impact in a real world application space.}, subject = {Keramik}, language = {en} } @article{LahmerNguyenTuanKoenkeetal., author = {Lahmer, Tom and Nguyen-Tuan, Long and K{\"o}nke, Carsten and Bettzieche, Volker}, title = {Thermo-hydro-mechanische 3-D-Simulation von Staumauern-Modellierung und Validierung}, series = {WASSERWIRTSCHAFT}, journal = {WASSERWIRTSCHAFT}, pages = {27 -- 30}, abstract = {Thermo-hydro-mechanische 3-D-Simulation von Staumauern-Modellierung und Validierung}, subject = {Angewandte Mathematik}, language = {de} } @article{ZhangHaoWangetal., author = {Zhang, Chao and Hao, Xiao-Li and Wang, Cuixia and Wei, Ning and Rabczuk, Timon}, title = {Thermal conductivity of graphene nanoribbons under shear deformation: A molecular dynamics simulation}, series = {Scientific Reports}, journal = {Scientific Reports}, doi = {10.1038/srep41398}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170428-31718}, abstract = {Tensile strain and compress strain can greatly affect the thermal conductivity of graphene nanoribbons (GNRs). However, the effect of GNRs under shear strain, which is also one of the main strain effect, has not been studied systematically yet. In this work, we employ reverse nonequilibrium molecular dynamics (RNEMD) to the systematical study of the thermal conductivity of GNRs (with model size of 4 nm × 15 nm) under the shear strain. Our studies show that the thermal conductivity of GNRs is not sensitive to the shear strain, and the thermal conductivity decreases only 12-16\% before the pristine structure is broken. Furthermore, the phonon frequency and the change of the micro-structure of GNRs, such as band angel and bond length, are analyzed to explore the tendency of thermal conductivity. The results show that the main influence of shear strain is on the in-plane phonon density of states (PDOS), whose G band (higher frequency peaks) moved to the low frequency, thus the thermal conductivity is decreased. The unique thermal properties of GNRs under shear strains suggest their great potentials for graphene nanodevices and great potentials in the thermal managements and thermoelectric applications.}, subject = {W{\"a}rmeleitf{\"a}higkeit}, language = {en} } @article{ZhaoLuRabczuk, author = {Zhao, Jiyun and Lu, Lixin and Rabczuk, Timon}, title = {The tensile and shear failure behavior dependence on chain length and temperature in amorphous polymers}, series = {Computational Materials Science}, journal = {Computational Materials Science}, pages = {567 -- 572}, abstract = {The tensile and shear failure behavior dependence on chain length and temperature in amorphous polymers}, subject = {Angewandte Mathematik}, language = {en} } @article{FathiSajadzadehMohammadiSheshkaletal., author = {Fathi, Sadegh and Sajadzadeh, Hassan and Mohammadi Sheshkal, Faezeh and Aram, Farshid and Pinter, Gergo and Felde, Imre and Mosavi, Amir}, title = {The Role of Urban Morphology Design on Enhancing Physical Activity and Public Health}, series = {International Journal of Environmental Research and Public Health}, volume = {2020}, journal = {International Journal of Environmental Research and Public Health}, number = {Volume 17, Issue 7, 2359}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/ijerph17072359}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200402-41225}, pages = {29}, abstract = {Along with environmental pollution, urban planning has been connected to public health. The research indicates that the quality of built environments plays an important role in reducing mental disorders and overall health. The structure and shape of the city are considered as one of the factors influencing happiness and health in urban communities and the type of the daily activities of citizens. The aim of this study was to promote physical activity in the main structure of the city via urban design in a way that the main form and morphology of the city can encourage citizens to move around and have physical activity within the city. Functional, physical, cultural-social, and perceptual-visual features are regarded as the most important and effective criteria in increasing physical activities in urban spaces, based on literature review. The environmental quality of urban spaces and their role in the physical activities of citizens in urban spaces were assessed by using the questionnaire tool and analytical network process (ANP) of structural equation modeling. Further, the space syntax method was utilized to evaluate the role of the spatial integration of urban spaces on improving physical activities. Based on the results, consideration of functional diversity, spatial flexibility and integration, security, and the aesthetic and visual quality of urban spaces plays an important role in improving the physical health of citizens in urban spaces. Further, more physical activities, including motivation for walking and the sense of public health and happiness, were observed in the streets having higher linkage and space syntax indexes with their surrounding texture.}, subject = {Morphologie}, language = {en} } @article{BenZhaoZhangetal., author = {Ben, S. and Zhao, Jun-Hua and Zhang, Yancheng and Rabczuk, Timon}, title = {The interface strength and debonding for composite structures: review and recent developments}, series = {Composite Structures}, journal = {Composite Structures}, abstract = {The interface strength and debonding for composite structures: review and recent developments}, subject = {Angewandte Mathematik}, language = {en} } @article{AreiasRabczukBarbosa, author = {Areias, Pedro and Rabczuk, Timon and Barbosa, J.I.}, title = {The extended unsymmetric frontal solution for multiple-point constraints}, series = {Engineering Computations}, journal = {Engineering Computations}, abstract = {The extended unsymmetric frontal solution for multiple-point constraints}, subject = {Angewandte Mathematik}, language = {en} } @article{IşıkBueyueksaracLeventEkincietal., author = {I{\c{s}}{\i}k, Ercan and B{\"u}y{\"u}ksara{\c{c}}, Ayd{\i}n and Levent Ekinci, Yunus and Ayd{\i}n, Mehmet Cihan and Harirchian, Ehsan}, title = {The Effect of Site-Specific Design Spectrum on Earthquake-Building Parameters: A Case Study from the Marmara Region (NW Turkey)}, series = {Applied Sciences}, volume = {2020}, journal = {Applied Sciences}, number = {Volume 10, issue 20, article 7247}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/app10207247}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20201022-42758}, pages = {23}, abstract = {The Marmara Region (NW Turkey) has experienced significant earthquakes (M > 7.0) to date. A destructive earthquake is also expected in the region. To determine the effect of the specific design spectrum, eleven provinces located in the region were chosen according to the Turkey Earthquake Building Code updated in 2019. Additionally, the differences between the previous and updated regulations of the country were investigated. Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) were obtained for each province by using earthquake ground motion levels with 2\%, 10\%, 50\%, and 68\% probability of exceedance in 50-year periods. The PGA values in the region range from 0.16 to 0.7 g for earthquakes with a return period of 475 years. For each province, a sample of a reinforced-concrete building having two different numbers of stories with the same ground and structural characteristics was chosen. Static adaptive pushover analyses were performed for the sample reinforced-concrete building using each province's design spectrum. The variations in the earthquake and structural parameters were investigated according to different geographical locations. It was determined that the site-specific design spectrum significantly influences target displacements for performance-based assessments of buildings due to seismicity characteristics of the studied geographic location.}, subject = {Erdbeben}, language = {en} } @article{ZerbstVormwaldAnderschetal., author = {Zerbst, U. and Vormwald, Michael and Andersch, C. and M{\"a}dler, K. and Pfuff, M.}, title = {The development of a damage tolerance concept for railway components and its demonstration for a railway axle}, series = {Engineering Fracture Mechanics}, journal = {Engineering Fracture Mechanics}, pages = {209 -- 239}, abstract = {The development of a damage tolerance concept for railway components and its demonstration for a railway axle}, subject = {Angewandte Mathematik}, language = {en} } @article{ZhaoKouJiangetal., author = {Zhao, Jun-Hua and Kou, Liangzhi and Jiang, Jin-Wu and Rabczuk, Timon}, title = {Tension-induced phase transition of single-layer molybdenum disulphide (MoS2) at low temperatures}, series = {Nanotechnology}, journal = {Nanotechnology}, doi = {10.1088/0957-4484/25/29/295701}, abstract = {Tension-induced phase transition of single-layer molybdenum disulphide (MoS2) at low temperatures}, subject = {Angewandte Mathematik}, language = {en} } @article{GhorashiValizadehMohammadietal., author = {Ghorashi, Seyed Shahram and Valizadeh, Navid and Mohammadi, S. and Rabczuk, Timon}, title = {T-spline based XIGA for Fracture Analysis of Orthotropic Media}, series = {Computers \& Structures}, journal = {Computers \& Structures}, pages = {138 -- 146}, abstract = {T-spline based XIGA for Fracture Analysis of Orthotropic Media}, subject = {Angewandte Mathematik}, language = {en} } @article{UngerTeughelsDeRoeck, author = {Unger, J{\"o}rg F. and Teughels, A. and De Roeck, G.}, title = {System identification and damage detection of a prestressed concrete beam}, series = {Journal of Structural Engineering}, journal = {Journal of Structural Engineering}, pages = {1691 -- 1698}, abstract = {System identification and damage detection of a prestressed concrete beam}, subject = {Angewandte Mathematik}, language = {en} } @article{SteinLahmerBock, author = {Stein, Peter and Lahmer, Tom and Bock, Sebastian}, title = {Synthese und Analyse von gekoppelten Modellen im konstruktiven Ingenieurbau}, series = {Bautechnik}, journal = {Bautechnik}, pages = {8 -- 11}, abstract = {Synthese und Analyse von gekoppelten Modellen im konstruktiven Ingenieurbau}, subject = {Angewandte Mathematik}, language = {de} } @article{JiangZhaoZhouetal., author = {Jiang, Jin-Wu and Zhao, Jun-Hua and Zhou, K. and Rabczuk, Timon}, title = {Superior thermal conductivity and extremely high mechanical strength in polyethylene chains from ab initio calculation}, series = {Journal of Applied Physics}, journal = {Journal of Applied Physics}, doi = {10.1063/1.4729489}, abstract = {The upper limit of the thermal conductivity and the mechanical strength are predicted for the polyethylene chain, by performing the ab initio calculation and applying the quantum mechanical non-equilibrium Green's function approach. Specially, there are two main findings from our calculation: (1) the thermal conductivity can reach a high value of 310 Wm-1 K-1 in a 100 nm polyethylene chain at room temperature and the thermal conductivity increases with the length of the chain; (2) the Young's modulus in the polyethylene chain is as high as 374.5 GPa, and the polyethylene chain can sustain 32.85\%±0.05\% (ultimate) strain before undergoing structural phase transition into gaseous ethylene.}, subject = {Angewandte Mathematik}, language = {en} } @article{GhazvineiDarvishiMosavietal., author = {Ghazvinei, Pezhman Taherei and Darvishi, Hossein Hassanpour and Mosavi, Amir and Yusof, Khamaruzaman bin Wan and Alizamir, Meysam and Shamshirband, Shahaboddin and Chau, Kwok-Wing}, title = {Sugarcane growth prediction based on meteorological parameters using extreme learning machine and artificial neural network}, series = {Engineering Applications of Computational Fluid Mechanics}, volume = {2018}, journal = {Engineering Applications of Computational Fluid Mechanics}, number = {12,1}, publisher = {Taylor \& Francis}, doi = {10.1080/19942060.2018.1526119}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181017-38129}, pages = {738 -- 749}, abstract = {Management strategies for sustainable sugarcane production need to deal with the increasing complexity and variability of the whole sugar system. Moreover, they need to accommodate the multiple goals of different industry sectors and the wider community. Traditional disciplinary approaches are unable to provide integrated management solutions, and an approach based on whole systems analysis is essential to bring about beneficial change to industry and the community. The application of this approach to water management, environmental management and cane supply management is outlined, where the literature indicates that the application of extreme learning machine (ELM) has never been explored in this realm. Consequently, the leading objective of the current research was set to filling this gap by applying ELM to launch swift and accurate model for crop production data-driven. The key learning has been the need for innovation both in the technical aspects of system function underpinned by modelling of sugarcane growth. Therefore, the current study is an attempt to establish an integrate model using ELM to predict the concluding growth amount of sugarcane. Prediction results were evaluated and further compared with artificial neural network (ANN) and genetic programming models. Accuracy of the ELM model is calculated using the statistics indicators of Root Means Square Error (RMSE), Pearson Coefficient (r), and Coefficient of Determination (R2) with promising results of 0.8, 0.47, and 0.89, respectively. The results also show better generalization ability in addition to faster learning curve. Thus, proficiency of the ELM for supplementary work on advancement of prediction model for sugarcane growth was approved with promising results.}, subject = {K{\"u}nstliche Intelligenz}, language = {en} } @phdthesis{Mai, author = {Mai, Luu}, title = {Structural Control Systems in High-speed Railway Bridges}, issn = {1610-7381}, doi = {10.25643/bauhaus-universitaet.2339}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20141223-23391}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {147}, abstract = {Structural vibration control of high-speed railway bridges using tuned mass dampers, semi-active tuned mass dampers, fluid viscous dampers and magnetorheological dampers to reduce resonant structural vibrations is studied. In this work, the addressed main issues include modeling of the dynamic interaction of the structures, optimization of the parameters of the dampers and comparison of their efficiency. A new approach to optimize multiple tuned mass damper systems on an uncertain model is proposed based on the H-infinity optimization criteria and the DK iteration procedure with norm-bounded uncertainties in frequency domain. The parameters of tuned mass dampers are optimized directly and simultaneously on different modes contributing significantly to the multi-resonant peaks to explore the different possible combinations of parameters. The effectiveness of the present method is also evaluated through comparison with a previous method. In the case of semi-active tuned mass dampers, an optimization algorithm is derived to control the magnetorheological damper in these semi-active damping systems. The use of the proposed algorithm can generate various combinations of control gains and state variables. This can lead to the improvement of the ability of MR dampers to track the desired control forces. An uncertain model to reduce detuning effects is also considered in this work. Next, for fluid viscous dampers, in order to tune the optimal parameters of fluid viscous dampers to the vicinity of the exact values, analytical formulae which can include structural damping are developed based on the perturbation method. The proposed formulae can also be considered as an improvement of the previous analytical formulae, especially for bridge beams with large structural damping. Finally, a new combination of magnetorheological dampers and a double-beam system to improve the performance of the primary structure vibration is proposed. An algorithm to control magnetorheological dampers in this system is developed by using standard linear matrix inequality techniques. Weight functions as a loop shaping procedure are also introduced in the feedback controllers to improve the tracking ability of magnetorheological damping forces. To this end, the effectiveness of magnetorheological dampers controlled by the proposed scheme, along with the effects of the uncertain and time-delay parameters on the models, are evaluated through numerical simulations. Additionally, a comparison of the dampers based on their performance is also considered in this work.}, subject = {High-speed railway bridge}, language = {en} } @phdthesis{KhademiZahedi, author = {Khademi Zahedi, Reza}, title = {Stress Distribution in Buried Defective PE Pipes and Crack Propagation in Nanosheets}, doi = {10.25643/bauhaus-universitaet.4481}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210803-44814}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {235}, abstract = {Buried PE pipelines are the main choice for transporting hazardous hydrocarbon fluids and are used in urban gas distribution networks. Molecular dynamics (MD) simulations used to investigate material behavior at nanoscale.}, subject = {Gasleitung}, language = {en} } @phdthesis{Vu, author = {Vu, Bac Nam}, title = {Stochastic uncertainty quantification for multiscale modeling of polymeric nanocomposites}, doi = {10.25643/bauhaus-universitaet.2555}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20160322-25551}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {265}, abstract = {Nanostructured materials are extensively applied in many fields of material science for new industrial applications, particularly in the automotive, aerospace industry due to their exceptional physical and mechanical properties. Experimental testing of nanomaterials is expensive, timeconsuming,challenging and sometimes unfeasible. Therefore,computational simulations have been employed as alternative method to predict macroscopic material properties. The behavior of polymeric nanocomposites (PNCs) are highly complex. The origins of macroscopic material properties reside in the properties and interactions taking place on finer scales. It is therefore essential to use multiscale modeling strategy to properly account for all large length and time scales associated with these material systems, which across many orders of magnitude. Numerous multiscale models of PNCs have been established, however, most of them connect only two scales. There are a few multiscale models for PNCs bridging four length scales (nano-, micro-, meso- and macro-scales). In addition, nanomaterials are stochastic in nature and the prediction of macroscopic mechanical properties are influenced by many factors such as fine-scale features. The predicted mechanical properties obtained by traditional approaches significantly deviate from the measured values in experiments due to neglecting uncertainty of material features. This discrepancy is indicated that the effective macroscopic properties of materials are highly sensitive to various sources of uncertainty, such as loading and boundary conditions and material characteristics, etc., while very few stochastic multiscale models for PNCs have been developed. Therefore, it is essential to construct PNC models within the framework of stochastic modeling and quantify the stochastic effect of the input parameters on the macroscopic mechanical properties of those materials. This study aims to develop computational models at four length scales (nano-, micro-, meso- and macro-scales) and hierarchical upscaling approaches bridging length scales from nano- to macro-scales. A framework for uncertainty quantification (UQ) applied to predict the mechanical properties of the PNCs in dependence of material features at different scales is studied. Sensitivity and uncertainty analysis are of great helps in quantifying the effect of input parameters, considering both main and interaction effects, on the mechanical properties of the PNCs. To achieve this major goal, the following tasks are carried out: At nano-scale, molecular dynamics (MD) were used to investigate deformation mechanism of glassy amorphous polyethylene (PE) in dependence of temperature and strain rate. Steered molecular dynamics (SMD)were also employed to investigate interfacial characteristic of the PNCs. At mico-scale, we developed an atomistic-based continuum model represented by a representative volume element (RVE) in which the SWNT's properties and the SWNT/polymer interphase are modeled at nano-scale, the surrounding polymer matrix is modeled by solid elements. Then, a two-parameter model was employed at meso-scale. A hierarchical multiscale approach has been developed to obtain the structure-property relations at one length scale and transfer the effect to the higher length scales. In particular, we homogenized the RVE into an equivalent fiber. The equivalent fiber was then employed in a micromechanical analysis (i.e. Mori-Tanaka model) to predict the effective macroscopic properties of the PNC. Furthermore, an averaging homogenization process was also used to obtain the effective stiffness of the PCN at meso-scale. Stochastic modeling and uncertainty quantification consist of the following ingredients: - Simple random sampling, Latin hypercube sampling, Sobol' quasirandom sequences, Iman and Conover's method (inducing correlation in Latin hypercube sampling) are employed to generate independent and dependent sample data, respectively. - Surrogate models, such as polynomial regression, moving least squares (MLS), hybrid method combining polynomial regression and MLS, Kriging regression, and penalized spline regression, are employed as an approximation of a mechanical model. The advantage of the surrogate models is the high computational efficiency and robust as they can be constructed from a limited amount of available data. - Global sensitivity analysis (SA) methods, such as variance-based methods for models with independent and dependent input parameters, Fourier-based techniques for performing variance-based methods and partial derivatives, elementary effects in the context of local SA, are used to quantify the effects of input parameters and their interactions on the mechanical properties of the PNCs. A bootstrap technique is used to assess the robustness of the global SA methods with respect to their performance. In addition, the probability distribution of mechanical properties are determined by using the probability plot method. The upper and lower bounds of the predicted Young's modulus according to 95 \% prediction intervals were provided. The above-mentioned methods study on the behaviour of intact materials. Novel numerical methods such as a node-based smoothed extended finite element method (NS-XFEM) and an edge-based smoothed phantom node method (ES-Phantom node) were developed for fracture problems. These methods can be used to account for crack at macro-scale for future works. The predicted mechanical properties were validated and verified. They show good agreement with previous experimental and simulations results.}, subject = {Polymere}, language = {en} } @article{MostBucher, author = {Most, Thomas and Bucher, Christian}, title = {Stochastic simulation of cracking in concrete structures using multi-parameter random fields}, series = {International Journal of Reliability and Safety}, journal = {International Journal of Reliability and Safety}, pages = {168 -- 187}, abstract = {Stochastic simulation of cracking in concrete structures using multi-parameter random fields}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacLahmerZhangetal., author = {Vu-Bac, N. and Lahmer, Tom and Zhang, Yancheng and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Stochastic predictions of interfacial characteristic of polymeric nanocomposites (PNCs)}, series = {Composites Part B Engineering}, journal = {Composites Part B Engineering}, pages = {80 -- 95}, abstract = {Stochastic predictions of interfacial characteristic of polymeric nanocomposites (PNCs)}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacLahmerKeiteletal., author = {Vu-Bac, N. and Lahmer, Tom and Keitel, Holger and Zhao, Jun-Hua and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Stochastic predictions of bulk properties of amorphous polyethylene based on molecular dynamics simulations}, series = {Mechanics of Materials}, journal = {Mechanics of Materials}, pages = {70 -- 84}, abstract = {Stochastic predictions of bulk properties of amorphous polyethylene based on molecular dynamics simulations}, subject = {Angewandte Mathematik}, language = {en} } @phdthesis{Ghasemi, author = {Ghasemi, Hamid}, title = {Stochastic optimization of fiber reinforced composites considering uncertainties}, doi = {10.25643/bauhaus-universitaet.2704}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20161117-27042}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {140}, abstract = {Briefly, the two basic questions that this research is supposed to answer are: 1. Howmuch fiber is needed and how fibers should be distributed through a fiber reinforced composite (FRC) structure in order to obtain the optimal and reliable structural response? 2. How do uncertainties influence the optimization results and reliability of the structure? Giving answer to the above questions a double stage sequential optimization algorithm for finding the optimal content of short fiber reinforcements and their distribution in the composite structure, considering uncertain design parameters, is presented. In the first stage, the optimal amount of short fibers in a FRC structure with uniformly distributed fibers is conducted in the framework of a Reliability Based Design Optimization (RBDO) problem. Presented model considers material, structural and modeling uncertainties. In the second stage, the fiber distribution optimization (with the aim to further increase in structural reliability) is performed by defining a fiber distribution function through a Non-Uniform Rational BSpline (NURBS) surface. The advantages of using the NURBS surface as a fiber distribution function include: using the same data set for the optimization and analysis; high convergence rate due to the smoothness of the NURBS; mesh independency of the optimal layout; no need for any post processing technique and its non-heuristic nature. The output of stage 1 (the optimal fiber content for homogeneously distributed fibers) is considered as the input of stage 2. The output of stage 2 is the Reliability Index (b ) of the structure with the optimal fiber content and distribution. First order reliability method (in order to approximate the limit state function) as well as different material models including Rule of Mixtures, Mori-Tanaka, energy-based approach and stochastic multi-scales are implemented in different examples. The proposed combined model is able to capture the role of available uncertainties in FRC structures through a computationally efficient algorithm using all sequential, NURBS and sensitivity based techniques. The methodology is successfully implemented for interfacial shear stress optimization in sandwich beams and also for optimization of the internal cooling channels in a ceramic matrix composite. Finally, after some changes and modifications by combining Isogeometric Analysis, level set and point wise density mapping techniques, the computational framework is extended for topology optimization of piezoelectric / flexoelectric materials.}, subject = {Finite-Elemente-Methode}, language = {en} } @phdthesis{Liu, author = {Liu, Bokai}, title = {Stochastic multiscale modeling of polymeric nanocomposites using Data-driven techniques}, doi = {10.25643/bauhaus-universitaet.4637}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220503-46379}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {134}, abstract = {In recent years, lightweight materials, such as polymer composite materials (PNCs) have been studied and developed due to their excellent physical and chemical properties. Structures composed of these composite materials are widely used in aerospace engineering structures, automotive components, and electrical devices. The excellent and outstanding mechanical, thermal, and electrical properties of Carbon nanotube (CNT) make it an ideal filler to strengthen polymer materials' comparable properties. The heat transfer of composite materials has very promising engineering applications in many fields, especially in electronic devices and energy storage equipment. It is essential in high-energy density systems since electronic components need heat dissipation functionality. Or in other words, in electronic devices the generated heat should ideally be dissipated by light and small heat sinks. Polymeric composites consist of fillers embedded in a polymer matrix, the first ones will significantly affect the overall (macroscopic) performance of the material. There are many common carbon-based fillers such as single-walled carbon nanotubes (SWCNT), multi-walled carbon nanotubes (MWCNT), carbon nanobuds (CNB), fullerene, and graphene. Additives inside the matrix have become a popular subject for researchers. Some extraordinary characters, such as high-performance load, lightweight design, excellent chemical resistance, easy processing, and heat transfer, make the design of polymeric nanotube composites (PNCs) flexible. Due to the reinforcing effects with different fillers on composite materials, it has a higher degree of freedom and can be designed for the structure according to specific applications' needs. As already stated, our research focus will be on SWCNT enhanced PNCs. Since experiments are timeconsuming, sometimes expensive and cannot shed light into phenomena taking place for instance at the interfaces/interphases of composites, they are often complemented through theoretical and computational analysis. While most studies are based on deterministic approaches, there is a comparatively lower number of stochastic methods accounting for uncertainties in the input parameters. In deterministic models, the output of the model is fully determined by the parameter values and the initial conditions. However, uncertainties in the input parameters such as aspect ratio, volume fraction, thermal properties of fiber and matrix need to be taken into account for reliable predictions. In this research, a stochastic multiscale method is provided to study the influence of numerous uncertain input parameters on the thermal conductivity of the composite. Therefore, a hierarchical multi-scale method based on computational homogenization is presented in to predict the macroscopic thermal conductivity based on the fine-scale structure. In order to study the inner mechanism, we use the finite element method and employ surrogate models to conduct a Global Sensitivity Analysis (GSA). The SA is performed in order to quantify the influence of the conductivity of the fiber, matrix, Kapitza resistance, volume fraction and aspect ratio on the macroscopic conductivity. Therefore, we compute first-order and total-effect sensitivity indices with different surrogate models. As stochastic multiscale models are computational expensive, surrogate approaches are commonly exploited. With the emergence of high performance computing and artificial intelligence, machine learning has become a popular modeling tool for numerous applications. Machine learning (ML) is commonly used in regression and maps data through specific rules with algorithms to build input and output models. They are particularly useful for nonlinear input-output relationships when sufficient data is available. ML has also been used in the design of new materials and multiscale analysis. For instance, Artificial neural networks and integrated learning seem to be ideally for such a task. They can theoretically simulate any non-linear relationship through the connection of neurons. Mapping relationships are employed to carry out data-driven simulations of inputs and outputs in stochastic modeling. This research aims to develop a stochastic multi-scale computational models of PNCs in heat transfer. Multi-scale stochastic modeling with uncertainty analysis and machine learning methods consist of the following components: -Uncertainty Analysis. A surrogate based global sensitivity analysis is coupled with a hierarchical multi-scale method employing computational homogenization. The effect of the conductivity of the fibers and the matrix, the Kapitza resistance, volume fraction and aspect ratio on the 'macroscopic' conductivity of the composite is systematically studied. All selected surrogate models yield consistently the conclusions that the most influential input parameters are the aspect ratio followed by the volume fraction. The Kapitza Resistance has no significant effect on the thermal conductivity of the PNCs. The most accurate surrogate model in terms of the R2 value is the moving least square (MLS). -Hybrid Machine Learning Algorithms. A combination of artificial neural network (ANN) and particle swarm optimization (PSO) is applied to estimate the relationship between variable input and output parameters. The ANN is used for modeling the composite while PSO improves the prediction performance through an optimized global minimum search. The thermal conductivity of the fibers and the matrix, the kapitza resistance, volume fraction and aspect ratio are selected as input parameters. The output is the macroscopic (homogenized) thermal conductivity of the composite. The results show that the PSO significantly improves the predictive ability of this hybrid intelligent algorithm, which outperforms traditional neural networks. -Stochastic Integrated Machine Learning. A stochastic integrated machine learning based multiscale approach for the prediction of the macroscopic thermal conductivity in PNCs is developed. Seven types of machine learning models are exploited in this research, namely Multivariate Adaptive Regression Splines (MARS), Support Vector Machine (SVM), Regression Tree (RT), Bagging Tree (Bag), Random Forest (RF), Gradient Boosting Machine (GBM) and Cubist. They are used as components of stochastic modeling to construct the relationship between the variable of the inputs' uncertainty and the macroscopic thermal conductivity of PNCs. Particle Swarm Optimization (PSO) is used for hyper-parameter tuning to find the global optimal values leading to a significant reduction in the computational cost. The advantages and disadvantages of various methods are also analyzed in terms of computing time and model complexity to finally give a recommendation for the applicability of different models.}, subject = {Polymere}, language = {en} } @article{RabczukGuoZhuangetal., author = {Rabczuk, Timon and Guo, Hongwei and Zhuang, Xiaoying and Chen, Pengwan and Alajlan, Naif}, title = {Stochastic deep collocation method based on neural architecture search and transfer learning for heterogeneous porous media}, series = {Engineering with Computers}, volume = {2022}, journal = {Engineering with Computers}, publisher = {Springer}, address = {London}, doi = {10.1007/s00366-021-01586-2}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220209-45835}, pages = {1 -- 26}, abstract = {We present a stochastic deep collocation method (DCM) based on neural architecture search (NAS) and transfer learning for heterogeneous porous media. We first carry out a sensitivity analysis to determine the key hyper-parameters of the network to reduce the search space and subsequently employ hyper-parameter optimization to finally obtain the parameter values. The presented NAS based DCM also saves the weights and biases of the most favorable architectures, which is then used in the fine-tuning process. We also employ transfer learning techniques to drastically reduce the computational cost. The presented DCM is then applied to the stochastic analysis of heterogeneous porous material. Therefore, a three dimensional stochastic flow model is built providing a benchmark to the simulation of groundwater flow in highly heterogeneous aquifers. The performance of the presented NAS based DCM is verified in different dimensions using the method of manufactured solutions. We show that it significantly outperforms finite difference methods in both accuracy and computational cost.}, subject = {Maschinelles Lernen}, language = {en} } @misc{Almasi, type = {Master Thesis}, author = {Almasi, Ashkan}, title = {Stochastic Analysis of Interfacial Effects on the Polymeric Nanocomposites}, doi = {10.25643/bauhaus-universitaet.2433}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20150709-24339}, school = {Bauhaus-Universit{\"a}t Weimar}, abstract = {The polymeric clay nanocomposites are a new class of materials of which recently have become the centre of attention due to their superior mechanical and physical properties. Several studies have been performed on the mechanical characterisation of these nanocomposites; however most of those studies have neglected the effect of the interfacial region between the clays and the matrix despite of its significant influence on the mechanical performance of the nanocomposites. There are different analytical methods to calculate the overall elastic material properties of the composites. In this study we use the Mori-Tanaka method to determine the overall stiffness of the composites for simple inclusion geometries of cylinder and sphere. Furthermore, the effect of interphase layer on the overall properties of composites is calculated. Here, we intend to get ounds for the effective mechanical properties to compare with the analytical results. Hence, we use linear displacement boundary conditions (LD) and uniform traction boundary conditions (UT) accordingly. Finally, the analytical results are compared with numerical results and they are in a good agreement. The next focus of this dissertation is a computational approach with a hierarchical multiscale method on the mesoscopic level. In other words, in this study we use the stochastic analysis and computational homogenization method to analyse the effect of thickness and stiffness of the interfacial region on the overall elastic properties of the clay/epoxy nanocomposites. The results show that the increase in interphase thickness, reduces the stiffness of the clay/epoxy naocomposites and this decrease becomes significant in higher clay contents. The results of the sensitivity analysis prove that the stiffness of the interphase layer has more significant effect on the final stiffness of nanocomposites. We also validate the results with the available experimental results from the literature which show good agreement.}, language = {en} } @article{KerfridenSchmidtRabczuketal., author = {Kerfriden, Pierre and Schmidt, K.M. and Rabczuk, Timon and Bordas, St{\´e}phane Pierre Alain}, title = {Statistical extraction of process zones and representative subspaces in fracture of random composites}, series = {International Journal for Multiscale Computational Engineering}, journal = {International Journal for Multiscale Computational Engineering}, abstract = {Statistical extraction of process zones and representative subspaces in fracture of random composites}, subject = {Angewandte Mathematik}, language = {en} } @article{ThaiNguyenXuanNguyenThanhetal., author = {Thai, Chien H. and Nguyen-Xuan, Hung and Nguyen-Thanh, Nhon and Le, T.H. and Nguyen-Thoi, T. and Rabczuk, Timon}, title = {Static, free vibration and buckling analysis of laminated composite Reissner-Mindlin plates using NURBS-based isogeometric approach}, series = {International Journal for Numerical Methods in Engineering}, journal = {International Journal for Numerical Methods in Engineering}, doi = {10.1002/nme.4282}, pages = {571 -- 603}, abstract = {This paper presents a novel numerical procedure based on the framework of isogeometric analysis for static, free vibration, and buckling analysis of laminated composite plates using the first-order shear deformation theory. The isogeometric approach utilizes non-uniform rational B-splines to implement for the quadratic, cubic, and quartic elements. Shear locking problem still exists in the stiffness formulation, and hence, it can be significantly alleviated by a stabilization technique. Several numerical examples are presented to show the performance of the method, and the results obtained are compared with other available ones.}, subject = {Angewandte Mathematik}, language = {en} } @article{DehghaniSalehiMosavietal., author = {Dehghani, Majid and Salehi, Somayeh and Mosavi, Amir and Nabipour, Narjes and Shamshirband, Shahaboddin and Ghamisi, Pedram}, title = {Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices}, series = {ISPRS, International Journal of Geo-Information}, volume = {2020}, journal = {ISPRS, International Journal of Geo-Information}, number = {Volume 9, Issue 2, 73}, publisher = {MDPI}, doi = {10.3390/ijgi9020073}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200128-40740}, pages = {23}, abstract = {Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing the variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Ni{\~n}o-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then, the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Additionally, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100\%. However, the seasonal precipitation may increase more than 100\% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.}, subject = {Maschinelles Lernen}, language = {en} } @inproceedings{SchraderKoenke, author = {Schrader, Kai and K{\"o}nke, Carsten}, title = {SPARSE APPROXIMATE COMPUTATION OF SADDLE POINT PROBLEMS ARISING FROM FETI-DP DISCRETIZATION}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2887}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28874}, pages = {12}, abstract = {The numerical simulation of microstructure models in 3D requires, due to enormous d.o.f., significant resources of memory as well as parallel computational power. Compared to homogeneous materials, the material hetrogeneity on microscale induced by different material phases demand for adequate computational methods for discretization and solution process of the resulting highly nonlinear problem. To enable an efficient/scalable solution process of the linearized equation systems the heterogeneous FE problem will be described by a FETI-DP (Finite Element Tearing and Interconnecting - Dual Primal) discretization. The fundamental FETI-DP equation can be solved by a number of different approaches. In our approach the FETI-DP problem will be reformulated as Saddle Point system, by eliminating the primal and Lagrangian variables. For the reduced Saddle Point system, only defined by interior and dual variables, special Uzawa algorithms can be adapted for iteratively solving the FETI-DP saddle-point equation system (FETI-DP SPE). A conjugate gradient version of the Uzawa algorithm will be shown as well as some numerical tests regarding to FETI-DP discretization of small examples using the presented solution technique. Furthermore the inversion of the interior-dual Schur complement operator can be approximated using different techniques building an adequate preconditioning matrix and therewith leading to substantial gains in computing time efficiency.}, subject = {Angewandte Informatik}, language = {en} } @phdthesis{Chan, author = {Chan, Chiu Ling}, title = {Smooth representation of thin shells and volume structures for isogeometric analysis}, doi = {10.25643/bauhaus-universitaet.4208}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200812-42083}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {162}, abstract = {The purpose of this study is to develop self-contained methods for obtaining smooth meshes which are compatible with isogeometric analysis (IGA). The study contains three main parts. We start by developing a better understanding of shapes and splines through the study of an image-related problem. Then we proceed towards obtaining smooth volumetric meshes of the given voxel-based images. Finally, we treat the smoothness issue on the multi-patch domains with C1 coupling. Following are the highlights of each part. First, we present a B-spline convolution method for boundary representation of voxel-based images. We adopt the filtering technique to compute the B-spline coefficients and gradients of the images effectively. We then implement the B-spline convolution for developing a non-rigid images registration method. The proposed method is in some sense of "isoparametric", for which all the computation is done within the B-splines framework. Particularly, updating the images by using B-spline composition promote smooth transformation map between the images. We show the possible medical applications of our method by applying it for registration of brain images. Secondly, we develop a self-contained volumetric parametrization method based on the B-splines boundary representation. We aim to convert a given voxel-based data to a matching C1 representation with hierarchical cubic splines. The concept of the osculating circle is employed to enhance the geometric approximation, where it is done by a single template and linear transformations (scaling, translations, and rotations) without the need for solving an optimization problem. Moreover, we use the Laplacian smoothing and refinement techniques to avoid irregular meshes and to improve mesh quality. We show with several examples that the method is capable of handling complex 2D and 3D configurations. In particular, we parametrize the 3D Stanford bunny which contains irregular shapes and voids. Finally, we propose the B´ezier ordinates approach and splines approach for C1 coupling. In the first approach, the new basis functions are defined in terms of the B´ezier Bernstein polynomials. For the second approach, the new basis is defined as a linear combination of C0 basis functions. The methods are not limited to planar or bilinear mappings. They allow the modeling of solutions to fourth order partial differential equations (PDEs) on complex geometric domains, provided that the given patches are G1 continuous. Both methods have their advantages. In particular, the B´ezier approach offer more degree of freedoms, while the spline approach is more computationally efficient. In addition, we proposed partial degree elevation to overcome the C1-locking issue caused by the over constraining of the solution space. We demonstrate the potential of the resulting C1 basis functions for application in IGA which involve fourth order PDEs such as those appearing in Kirchhoff-Love shell models, Cahn-Hilliard phase field application, and biharmonic problems.}, subject = {Modellierung}, language = {en} } @article{JiangZhaoRabczuk, author = {Jiang, Jin-Wu and Zhao, Jun-Hua and Rabczuk, Timon}, title = {Size-Sensitive Young's Modulus of Kinked Silicon Nanowires}, series = {Nanotechnology}, journal = {Nanotechnology}, doi = {10.1088/0957-4484/24/18/185702}, abstract = {We perform both classical molecular dynamics simulations and beam model calculations to investigate the Young's modulus of kinked silicon nanowires (KSiNWs). The Young's modulus is found to be highly sensitive to the arm length of the kink and is essentially inversely proportional to the arm length. The mechanism underlying the size dependence is found to be the interplay between the kink angle potential and the arm length potential, where we obtain an analytic relationship between the Young's modulus and the arm length of the KSiNW. Our results provide insight into the application of this novel building block in nanomechanical devices.}, subject = {Angewandte Mathematik}, language = {en} } @article{NatarajanChakrabortyThangaveletal., author = {Natarajan, S. and Chakraborty, S. and Thangavel, M. and Bordas, St{\´e}phane Pierre Alain and Rabczuk, Timon}, title = {Size dependent free flexural vibration behavior of functionally graded nanoplates}, series = {Computational Materials Science}, journal = {Computational Materials Science}, pages = {74 -- 80}, abstract = {Size dependent free flexural vibration behavior of functionally graded nanoplates}, subject = {Angewandte Mathematik}, language = {en} } @article{NabipourDehghaniMosavietal., author = {Nabipour, Narjes and Dehghani, Majid and Mosavi, Amir and Shamshirband, Shahaboddin}, title = {Short-Term Hydrological Drought Forecasting Based on Different Nature-Inspired Optimization Algorithms Hybridized With Artificial Neural Networks}, series = {IEEE Access}, volume = {2020}, journal = {IEEE Access}, number = {volume 8}, publisher = {IEEE}, doi = {10.1109/ACCESS.2020.2964584}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200213-40796}, pages = {15210 -- 15222}, abstract = {Hydrological drought forecasting plays a substantial role in water resources management. Hydrological drought highly affects the water allocation and hydropower generation. In this research, short term hydrological drought forecasted based on the hybridized of novel nature-inspired optimization algorithms and Artificial Neural Networks (ANN). For this purpose, the Standardized Hydrological Drought Index (SHDI) and the Standardized Precipitation Index (SPI) were calculated in one, three, and six aggregated months. Then, three states where proposed for SHDI forecasting, and 36 input-output combinations were extracted based on the cross-correlation analysis. In the next step, newly proposed optimization algorithms, including Grasshopper Optimization Algorithm (GOA), Salp Swarm algorithm (SSA), Biogeography-based optimization (BBO), and Particle Swarm Optimization (PSO) hybridized with the ANN were utilized for SHDI forecasting and the results compared to the conventional ANN. Results indicated that the hybridized model outperformed compared to the conventional ANN. PSO performed better than the other optimization algorithms. The best models forecasted SHDI1 with R2 = 0.68 and RMSE = 0.58, SHDI3 with R 2 = 0.81 and RMSE = 0.45 and SHDI6 with R 2 = 0.82 and RMSE = 0.40.}, subject = {Maschinelles Lernen}, language = {en} } @phdthesis{Tan, author = {Tan, Fengjie}, title = {Shape Optimization Design of Arch Type Dams under Uncertainties}, doi = {10.25643/bauhaus-universitaet.3960}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190819-39608}, school = {Bauhaus-Universit{\"a}t Weimar}, abstract = {Due to an increased need for hydro-electricity, water storage, and flood protection, it is assumed that a series of new dams will be built throughout the world. Comparing existing design methodologies for arch-type dams, model-based shape optimization can effectively reduce construction costs and leverage the properties of construction materials. To apply the means of shape optimization, suitable variables need to be chosen to formulate the objective function, which is the volume of the arch dam here. In order to increase the consistency with practical conditions, a great number of geometrical and behavioral constraints are included in the mathematical model. An optimization method, namely Genetic Algorithm is adopted which allows a global search. Traditional optimization techniques are realized based on a deterministic approach, which means that the material properties and loading conditions are assumed to be fixed values. As a result, the real-world structures that are optimized by these approaches suffer from uncertainties that one needs to be aware of. Hence, in any optimization process for arch dams, it is nec- essary to find a methodology that is capable of considering the influences of uncertainties and generating a solution which is robust enough against the uncertainties. The focus of this thesis is the formulation and the numerical method for the optimization of the arch dam under the uncertainties. The two main models, the probabilistic model, and non-probabilistic models are intro- duced and discussed. Classic procedures of probabilistic approaches un- der uncertainties, such as RDO (robust design optimization) and RBDO (reliability-based design optimization), are in general computationally ex- pensive and rely on estimates of the system's response variance and fail- ure probabilities. Instead, the robust optimization (RO) method which is based on the non-probabilistic model, will not follow a full probabilistic approach but works with pre-defined confidence levels. This leads to a bi-level optimization program where the volume of the dam is optimized under the worst combination of the uncertain parameters. By this, robust and reliable designs are obtained and the result is independent of any as- sumptions on stochastic properties of the random variables in the model. The optimization of an arch-type dam is realized here by a robust optimiza- tion method under load uncertainty, where hydraulic and thermal loads are considered. The load uncertainty is modeled as an ellipsoidal expression. Comparing with any traditional deterministic optimization (DO) method, which only concerns the minimum objective value and offers a solution candidate close to limit-states, the RO method provides a robust solution against uncertainties. All the above mentioned methods are applied to the optimization of the arch dam to compare with the optimal design with DO methods. The re- sults are compared and analyzed to discuss the advantages and drawbacks of each method. In order to reduce the computational cost, a ranking strategy and an ap- proximation model are further involved to do a preliminary screening. By means of these, the robust design can generate an improved arch dam structure which ensures both safety and serviceability during its lifetime.}, subject = {Wasserbau}, language = {en} } @article{GhasemiBrighentiZhuangetal., author = {Ghasemi, Hamid and Brighenti, Roberto and Zhuang, Xiaoying and Muthu, Jacob and Rabczuk, Timon}, title = {Sequential reliability based optimization of fiber content and dispersion in fiber reinforced composite by using NURBS finite elements}, series = {Structural and Multidisciplinary Optimization}, journal = {Structural and Multidisciplinary Optimization}, abstract = {Sequential reliability based optimization of fiber content and dispersion in fiber reinforced composite by using NURBS finite elements}, subject = {Angewandte Mathematik}, language = {en} } @article{NasserSchwedlerWuttkeetal., author = {Nasser, Mourad and Schwedler, Michael and Wuttke, Frank and K{\"o}nke, Carsten}, title = {Seismic analysis of structural response using simplified soil-structure interaction models}, series = {Bauingenieur, D-A-CH-Mitteilungsblatt}, journal = {Bauingenieur, D-A-CH-Mitteilungsblatt}, abstract = {Seismic analysis of structural response using simplified soil-structure interaction models}, subject = {Angewandte Mathematik}, language = {en} } @inproceedings{TanLahmerSiddappa, author = {Tan, Fengjie and Lahmer, Tom and Siddappa, Manju Gyaraganahalll}, title = {SECTION OPTIMIZATION AND RELIABILITY ANALYSIS OF ARCH-TYPE DAMS INCLUDING COUPLED MECHANICAL-THERMAL AND HYDRAULIC FIELDS}, series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, editor = {G{\"u}rlebeck, Klaus and Lahmer, Tom}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2821}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28212}, pages = {8}, abstract = {From the design experiences of arch dams in the past, it has significant practical value to carry out the shape optimization of arch dams, which can fully make use of material characteristics and reduce the cost of constructions. Suitable variables need to be chosen to formulate the objective function, e.g. to minimize the total volume of the arch dam. Additionally a series of constraints are derived and a reasonable and convenient penalty function has been formed, which can easily enforce the characteristics of constraints and optimal design. For the optimization method, a Genetic Algorithm is adopted to perform a global search. Simultaneously, ANSYS is used to do the mechanical analysis under the coupling of thermal and hydraulic loads. One of the constraints of the newly designed dam is to fulfill requirements on the structural safety. Therefore, a reliability analysis is applied to offer a good decision supporting for matters concerning predictions of both safety and service life of the arch dam. By this, the key factors which would influence the stability and safety of arch dam significantly can be acquired, and supply a good way to take preventive measures to prolong ate the service life of an arch dam and enhances the safety of structure.}, subject = {Angewandte Informatik}, language = {en} } @article{NguyenThanhKiendlNguyenXuanetal., author = {Nguyen-Thanh, Nhon and Kiendl, J. and Nguyen-Xuan, Hung and W{\"u}chner, R. and Bletzinger, Kai-Uwe and Bazilevs, Yuri and Rabczuk, Timon}, title = {Rotation free isogeometric thin shell analysis using PHT-splines}, series = {Computer Methods in Applied Mechanics and Engineering}, journal = {Computer Methods in Applied Mechanics and Engineering}, pages = {3410 -- 3424}, abstract = {Rotation free isogeometric thin shell analysis using PHT-splines}, subject = {Angewandte Mathematik}, language = {en} } @article{OuaerHosseiniAmaretal., author = {Ouaer, Hocine and Hosseini, Amir Hossein and Amar, Menad Nait and Ben Seghier, Mohamed El Amine and Ghriga, Mohammed Abdelfetah and Nabipour, Narjes and Andersen, P{\aa}l {\O}steb{\o} and Mosavi, Amir and Shamshirband, Shahaboddin}, title = {Rigorous Connectionist Models to Predict Carbon Dioxide Solubility in Various Ionic Liquids}, series = {Applied Sciences}, volume = {2020}, journal = {Applied Sciences}, number = {Volume 10, Issue 1, 304}, publisher = {MDPI}, doi = {https://doi.org/10.3390/app10010304}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200107-40558}, pages = {18}, abstract = {Estimating the solubility of carbon dioxide in ionic liquids, using reliable models, is of paramount importance from both environmental and economic points of view. In this regard, the current research aims at evaluating the performance of two data-driven techniques, namely multilayer perceptron (MLP) and gene expression programming (GEP), for predicting the solubility of carbon dioxide (CO2) in ionic liquids (ILs) as the function of pressure, temperature, and four thermodynamical parameters of the ionic liquid. To develop the above techniques, 744 experimental data points derived from the literature including 13 ILs were used (80\% of the points for training and 20\% for validation). Two backpropagation-based methods, namely Levenberg-Marquardt (LM) and Bayesian Regularization (BR), were applied to optimize the MLP algorithm. Various statistical and graphical assessments were applied to check the credibility of the developed techniques. The results were then compared with those calculated using Peng-Robinson (PR) or Soave-Redlich-Kwong (SRK) equations of state (EoS). The highest coefficient of determination (R2 = 0.9965) and the lowest root mean square error (RMSE = 0.0116) were recorded for the MLP-LMA model on the full dataset (with a negligible difference to the MLP-BR model). The comparison of results from this model with the vastly applied thermodynamic equation of state models revealed slightly better performance, but the EoS approaches also performed well with R2 from 0.984 up to 0.996. Lastly, the newly established correlation based on the GEP model exhibited very satisfactory results with overall values of R2 = 0.9896 and RMSE = 0.0201.}, subject = {Maschinelles Lernen}, language = {en} } @article{ThumserBergmannVormwald, author = {Thumser, Rayk and Bergmann, Joachim W. and Vormwald, Michael}, title = {Residual stress fields and fatigue analysis of autofrettaged parts}, series = {International Journal of Pressure Vessels and Piping}, journal = {International Journal of Pressure Vessels and Piping}, pages = {113 -- 117}, abstract = {Residual stress fields and fatigue analysis of autofrettaged parts}, subject = {Angewandte Mathematik}, language = {en} } @phdthesis{Ahmad, author = {Ahmad, Sofyan}, title = {Reference Surface-Based System Identification}, doi = {10.25643/bauhaus-universitaet.2113}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20140205-21132}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {153}, abstract = {Environmental and operational variables and their impact on structural responses have been acknowledged as one of the most important challenges for the application of the ambient vibration-based damage identification in structures. The damage detection procedures may yield poor results, if the impacts of loading and environmental conditions of the structures are not considered. The reference-surface-based method, which is proposed in this thesis, is addressed to overcome this problem. In the proposed method, meta-models are used to take into account significant effects of the environmental and operational variables. The usage of the approximation models, allows the proposed method to simply handle multiple non-damaged variable effects simultaneously, which for other methods seems to be very complex. The input of the meta-model are the multiple non-damaged variables while the output is a damage indicator. The reference-surface-based method diminishes the effect of the non-damaged variables to the vibration based damage detection results. Hence, the structure condition that is assessed by using ambient vibration data at any time would be more reliable. Immediate reliable information regarding the structure condition is required to quickly respond to the event, by means to take necessary actions concerning the future use or further investigation of the structures, for instance shortly after extreme events such as earthquakes. The critical part of the proposed damage detection method is the learning phase, where the meta-models are trained by using input-output relation of observation data. Significant problems that may encounter during the learning phase are outlined and some remedies to overcome the problems are suggested. The proposed damage identification method is applied to numerical and experimental models. In addition to the natural frequencies, wavelet energy and stochastic subspace damage indicators are used.}, subject = {System Identification}, language = {en} } @article{BeexKerfridenRabczuketal., author = {Beex, L.A.A. and Kerfriden, Pierre and Rabczuk, Timon and Bordas, St{\´e}phane Pierre Alain}, title = {Quasicontinuum-based multiscale approaches for plate-like beam lattices experiencing in-plane and out-of-plane deformation}, series = {Computer Methods in Applied Mechanics and Engineering}, journal = {Computer Methods in Applied Mechanics and Engineering}, abstract = {Quasicontinuum-based multiscale approaches for plate-like beam lattices experiencing in-plane and out-of-plane deformation}, subject = {Angewandte Mathematik}, language = {en} } @article{ZhangWeiZhaoetal., author = {Zhang, Yancheng and Wei, Ning and Zhao, Jun-Hua and Gong, Yadong and Rabczuk, Timon}, title = {Quasi-analytical solution for the stable system of the multi-layer folded graphene wrinkles}, series = {Journal of Applied Physics}, journal = {Journal of Applied Physics}, abstract = {Quasi-analytical solution for the stable system of the multi-layer folded graphene wrinkles}, subject = {Angewandte Mathematik}, language = {en} } @misc{Zafar, type = {Master Thesis}, author = {Zafar, Usman}, title = {Probabilistic Reliability Analysis of Wind Turbines}, doi = {10.25643/bauhaus-universitaet.3977}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20240507-39773}, school = {Bauhaus-Universit{\"a}t Weimar}, abstract = {Renewable energy use is on the rise and these alternative resources of energy can help combat with the climate change. Around 80\% of the world's electricity comes from coal and petroleum however, the renewables are the fastest growing source of energy in the world. Solar, wind, hydro, geothermal and biogas are the most common forms of renewable energy. Among them, wind energy is emerging as a reliable and large-scaled source of power production. The recent research and confidence in the performance has led to the construction of more and bigger wind turbines around the world. As wind turbines are getting bigger, a concern regarding their safety is also in discussion. Wind turbines are expensive machinery to construct and the enormous capital investment is one of the main reasons, why many countries are unable to adopt to the wind energy. Generally, a reliable wind turbine will result in better performance and assist in minimizing the cost of operation. If a wind turbine fails, it's a loss of investment and can be harmful for the surrounding habitat. This thesis aims towards estimating the reliability of an offshore wind turbine. A model of Jacket type offshore wind turbine is prepared by using finite element software package ABAQUS and is compared with the structural failure criteria of the wind turbine tower. UQLab, which is a general uncertainty quantification framework developed at ETH Z{\"u}rich, is used for the reliability analysis. Several probabilistic methods are included in the framework of UQLab, which include Monte Carlo, First Order Reliability Analysis and Adaptive Kriging Monte Carlo simulation. This reliability study is performed only for the structural failure of the wind turbine but it can be extended to many other forms of failures e.g. reliability for power production, or reliability for different component failures etc. It's a useful tool that can be utilized to estimate the reliability of future wind turbines, that could result in more safer and better performance of wind turbines.}, subject = {Windturbine}, language = {en} } @article{MostBucher, author = {Most, Thomas and Bucher, Christian}, title = {Probabilistic analysis of concrete cracking using neural networks and random fields}, series = {Probabilistic Engineering Mechanics}, journal = {Probabilistic Engineering Mechanics}, pages = {219 -- 229}, abstract = {Probabilistic analysis of concrete cracking using neural networks and random fields}, subject = {Angewandte Mathematik}, language = {en} } @article{MousaviSteinkeJuniorTeixeiraetal., author = {Mousavi, Seyed Nasrollah and Steinke J{\´u}nior, Renato and Teixeira, Eder Daniel and Bocchiola, Daniele and Nabipour, Narjes and Mosavi, Amir and Shamshirband, Shahaboddin}, title = {Predictive Modeling the Free Hydraulic Jumps Pressure through Advanced Statistical Methods}, series = {Mathematics}, volume = {2020}, journal = {Mathematics}, number = {Volume 8, Issue 3, 323}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/math8030323}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200402-41140}, pages = {16}, abstract = {Pressure fluctuations beneath hydraulic jumps potentially endanger the stability of stilling basins. This paper deals with the mathematical modeling of the results of laboratory-scale experiments to estimate the extreme pressures. Experiments were carried out on a smooth stilling basin underneath free hydraulic jumps downstream of an Ogee spillway. From the probability distribution of measured instantaneous pressures, pressures with different probabilities could be determined. It was verified that maximum pressure fluctuations, and the negative pressures, are located at the positions near the spillway toe. Also, minimum pressure fluctuations are located at the downstream of hydraulic jumps. It was possible to assess the cumulative curves of pressure data related to the characteristic points along the basin, and different Froude numbers. To benchmark the results, the dimensionless forms of statistical parameters include mean pressures (P*m), the standard deviations of pressure fluctuations (σ*X), pressures with different non-exceedance probabilities (P*k\%), and the statistical coefficient of the probability distribution (Nk\%) were assessed. It was found that an existing method can be used to interpret the present data, and pressure distribution in similar conditions, by using a new second-order fractional relationships for σ*X, and Nk\%. The values of the Nk\% coefficient indicated a single mean value for each probability.}, subject = {Maschinelles Lernen}, language = {en} } @article{SadeghzadehMaddahAhmadietal., author = {Sadeghzadeh, Milad and Maddah, Heydar and Ahmadi, Mohammad Hossein and Khadang, Amirhosein and Ghazvini, Mahyar and Mosavi, Amir Hosein and Nabipour, Narjes}, title = {Prediction of Thermo-Physical Properties of TiO2-Al2O3/Water Nanoparticles by Using Artificial Neural Network}, series = {Nanomaterials}, volume = {2020}, journal = {Nanomaterials}, number = {Volume 10, Issue 4, 697}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/nano10040697}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200421-41308}, abstract = {In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol-gel method. The results indicated that 1.5 vol.\% of nanofluids enhanced the thermal conductivity by up to 25\%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. View Full-Text}, subject = {W{\"a}rmeleitf{\"a}higkeit}, language = {en} } @article{ShamshirbandBabanezhadMosavietal., author = {Shamshirband, Shahaboddin and Babanezhad, Meisam and Mosavi, Amir and Nabipour, Narjes and Hajnal, Eva and Nadai, Laszlo and Chau, Kwok-Wing}, title = {Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants}, series = {Engineering Applications of Computational Fluid Mechanics}, volume = {2020}, journal = {Engineering Applications of Computational Fluid Mechanics}, number = {volume 14, issue 1}, publisher = {Taylor \& Francis}, doi = {10.1080/19942060.2020.1715842}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200227-41013}, pages = {367 -- 378}, abstract = {A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR.}, subject = {Maschinelles Lernen}, language = {en} } @unpublished{AbbasKavrakovMorgenthaletal., author = {Abbas, Tajammal and Kavrakov, Igor and Morgenthal, Guido and Lahmer, Tom}, title = {Prediction of aeroelastic response of bridge decks using artificial neural networks}, doi = {10.25643/bauhaus-universitaet.4097}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200225-40974}, abstract = {The assessment of wind-induced vibrations is considered vital for the design of long-span bridges. The aim of this research is to develop a methodological framework for robust and efficient prediction strategies for complex aerodynamic phenomena using hybrid models that employ numerical analyses as well as meta-models. Here, an approach to predict motion-induced aerodynamic forces is developed using artificial neural network (ANN). The ANN is implemented in the classical formulation and trained with a comprehensive dataset which is obtained from computational fluid dynamics forced vibration simulations. The input to the ANN is the response time histories of a bridge section, whereas the output is the motion-induced forces. The developed ANN has been tested for training and test data of different cross section geometries which provide promising predictions. The prediction is also performed for an ambient response input with multiple frequencies. Moreover, the trained ANN for aerodynamic forcing is coupled with the structural model to perform fully-coupled fluid--structure interaction analysis to determine the aeroelastic instability limit. The sensitivity of the ANN parameters to the model prediction quality and the efficiency has also been highlighted. The proposed methodology has wide application in the analysis and design of long-span bridges.}, subject = {Aerodynamik}, language = {en} } @article{HamdiaLahmerNguyenThoietal., author = {Hamdia, Khader and Lahmer, Tom and Nguyen-Thoi, T. and Rabczuk, Timon}, title = {Predicting The Fracture Toughness of PNCs: A Stochastic Approach Based on ANN and ANFIS}, series = {Computational Materials Science}, journal = {Computational Materials Science}, pages = {304 -- 313}, abstract = {Predicting The Fracture Toughness of PNCs: A Stochastic Approach Based on ANN and ANFIS}, subject = {Angewandte Mathematik}, language = {en} } @unpublished{KhosraviSheikhKhozaniCooper, author = {Khosravi, Khabat and Sheikh Khozani, Zohreh and Cooper, James R.}, title = {Predicting stable gravel-bed river hydraulic geometry: A test of novel, advanced, hybrid data mining algorithms}, volume = {2021}, doi = {10.25643/bauhaus-universitaet.4499}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20211004-44998}, abstract = {Accurate prediction of stable alluvial hydraulic geometry, in which erosion and sedimentation are in equilibrium, is one of the most difficult but critical topics in the field of river engineering. Data mining algorithms have been gaining more attention in this field due to their high performance and flexibility. However, an understanding of the potential for these algorithms to provide fast, cheap, and accurate predictions of hydraulic geometry is lacking. This study provides the first quantification of this potential. Using at-a-station field data, predictions of flow depth, water-surface width and longitudinal water surface slope are made using three standalone data mining techniques -, Instance-based Learning (IBK), KStar, Locally Weighted Learning (LWL) - along with four types of novel hybrid algorithms in which the standalone models are trained with Vote, Attribute Selected Classifier (ASC), Regression by Discretization (RBD), and Cross-validation Parameter Selection (CVPS) algorithms (Vote-IBK, Vote-Kstar, Vote-LWL, ASC-IBK, ASC-Kstar, ASC-LWL, RBD-IBK, RBD-Kstar, RBD-LWL, CVPSIBK, CVPS-Kstar, CVPS-LWL). Through a comparison of their predictive performance and a sensitivity analysis of the driving variables, the results reveal: (1) Shield stress was the most effective parameter in the prediction of all geometry dimensions; (2) hybrid models had a higher prediction power than standalone data mining models, empirical equations and traditional machine learning algorithms; (3) Vote-Kstar model had the highest performance in predicting depth and width, and ASC-Kstar in estimating slope, each providing very good prediction performance. Through these algorithms, the hydraulic geometry of any river can potentially be predicted accurately and with ease using just a few, readily available flow and channel parameters. Thus, the results reveal that these models have great potential for use in stable channel design in data poor catchments, especially in developing nations where technical modelling skills and understanding of the hydraulic and sediment processes occurring in the river system may be lacking.}, subject = {Maschinelles Lernen}, language = {en} } @article{LutherKoenke, author = {Luther, Torsten and K{\"o}nke, Carsten}, title = {Polycrystal models for the analysis of intergranular crack growth in metallic materials}, series = {Engineering Fracture Mechanics}, journal = {Engineering Fracture Mechanics}, pages = {2332 -- 2343}, abstract = {Polycrystal models for the analysis of intergranular crack growth in metallic materials}, subject = {Angewandte Mathematik}, language = {en} } @article{BanihaniRabczukAlmomani, author = {Banihani, Suleiman and Rabczuk, Timon and Almomani, Thakir}, title = {POD for real-time simulation of hyperelastic soft biological tissue using the point collocation method of finite spheres}, series = {Mathematical Problems in Engineering}, journal = {Mathematical Problems in Engineering}, doi = {10.1155/2013/386501}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170413-31203}, abstract = {The point collocation method of finite spheres (PCMFS) is used to model the hyperelastic response of soft biological tissue in real time within the framework of virtual surgery simulation. The proper orthogonal decomposition (POD) model order reduction (MOR) technique was used to achieve reduced-order model of the problem, minimizing computational cost. The PCMFS is a physics-based meshfree numerical technique for real-time simulation of surgical procedures where the approximation functions are applied directly on the strong form of the boundary value problem without the need for integration, increasing computational efficiency. Since computational speed has a significant role in simulation of surgical procedures, the proposed technique was able to model realistic nonlinear behavior of organs in real time. Numerical results are shown to demonstrate the effectiveness of the new methodology through a comparison between full and reduced analyses for several nonlinear problems. It is shown that the proposed technique was able to achieve good agreement with the full model; moreover, the computational and data storage costs were significantly reduced.}, subject = {Chirurgie}, language = {en} } @article{JiangWangRabczuk, author = {Jiang, Jin-Wu and Wang, Bing-Shen and Rabczuk, Timon}, title = {Phonon modes in single-walled molybdenum disulphide nanotubes: lattice dynamics calculation and molecular dynamics simulation}, series = {Nanotechnology}, journal = {Nanotechnology}, abstract = {Phonon modes in single-walled molybdenum disulphide nanotubes: lattice dynamics calculation and molecular dynamics simulation}, subject = {Angewandte Mathematik}, language = {en} } @article{AmiriMillanShenetal., author = {Amiri, Fatemeh and Mill{\´a}n, D. and Shen, Y. and Rabczuk, Timon and Arroyo, M.}, title = {Phase-field modeling of fracture in linear thin shells}, series = {Theoretical and Applied Fracture Mechanics}, journal = {Theoretical and Applied Fracture Mechanics}, pages = {102 -- 109}, abstract = {Phase-field modeling of fracture in linear thin shells}, subject = {Angewandte Mathematik}, language = {en} } @article{JamshidianRabczuk, author = {Jamshidian, M. and Rabczuk, Timon}, title = {Phase field modelling of stressed grain growth: Analytical study and the effect of microstructural length scale}, series = {Journal of Computational Physics}, journal = {Journal of Computational Physics}, pages = {23 -- 35}, abstract = {Phase field modelling of stressed grain growth: Analytical study and the effect of microstructural length scale}, subject = {Angewandte Mathematik}, language = {en} } @phdthesis{Goswami, author = {Goswami, Somdatta}, title = {Phase field modeling of fracture with isogeometric analysis and machine learning methods}, doi = {10.25643/bauhaus-universitaet.4384}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210304-43841}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {168}, abstract = {This thesis presents the advances and applications of phase field modeling in fracture analysis. In this approach, the sharp crack surface topology in a solid is approximated by a diffusive crack zone governed by a scalar auxiliary variable. The uniqueness of phase field modeling is that the crack paths are automatically determined as part of the solution and no interface tracking is required. The damage parameter varies continuously over the domain. But this flexibility comes with associated difficulties: (1) a very fine spatial discretization is required to represent sharp local gradients correctly; (2) fine discretization results in high computational cost; (3) computation of higher-order derivatives for improved convergence rates and (4) curse of dimensionality in conventional numerical integration techniques. As a consequence, the practical applicability of phase field models is severely limited. The research presented in this thesis addresses the difficulties of the conventional numerical integration techniques for phase field modeling in quasi-static brittle fracture analysis. The first method relies on polynomial splines over hierarchical T-meshes (PHT-splines) in the framework of isogeometric analysis (IGA). An adaptive h-refinement scheme is developed based on the variational energy formulation of phase field modeling. The fourth-order phase field model provides increased regularity in the exact solution of the phase field equation and improved convergence rates for numerical solutions on a coarser discretization, compared to the second-order model. However, second-order derivatives of the phase field are required in the fourth-order model. Hence, at least a minimum of C1 continuous basis functions are essential, which is achieved using hierarchical cubic B-splines in IGA. PHT-splines enable the refinement to remain local at singularities and high gradients, consequently reducing the computational cost greatly. Unfortunately, when modeling complex geometries, multiple parameter spaces (patches) are joined together to describe the physical domain and there is typically a loss of continuity at the patch boundaries. This decrease of smoothness is dictated by the geometry description, where C0 parameterizations are normally used to deal with kinks and corners in the domain. Hence, the application of the fourth-order model is severely restricted. To overcome the high computational cost for the second-order model, we develop a dual-mesh adaptive h-refinement approach. This approach uses a coarser discretization for the elastic field and a finer discretization for the phase field. Independent refinement strategies have been used for each field. The next contribution is based on physics informed deep neural networks. The network is trained based on the minimization of the variational energy of the system described by general non-linear partial differential equations while respecting any given law of physics, hence the name physics informed neural network (PINN). The developed approach needs only a set of points to define the geometry, contrary to the conventional mesh-based discretization techniques. The concept of `transfer learning' is integrated with the developed PINN approach to improve the computational efficiency of the network at each displacement step. This approach allows a numerically stable crack growth even with larger displacement steps. An adaptive h-refinement scheme based on the generation of more quadrature points in the damage zone is developed in this framework. For all the developed methods, displacement-controlled loading is considered. The accuracy and the efficiency of both methods are studied numerically showing that the developed methods are powerful and computationally efficient tools for accurately predicting fractures.}, subject = {Phasenfeldmodell}, language = {en} } @phdthesis{Msekh, author = {Msekh, Mohammed Abdulrazzak}, title = {Phase Field Modeling for Fracture with Applications to Homogeneous and Heterogeneous Materials}, doi = {10.25643/bauhaus-universitaet.3229}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170615-32291}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {190}, abstract = {The thesis presents an implementation including different applications of a variational-based approach for gradient type standard dissipative solids. Phase field model for brittle fracture is an application of the variational-based framework for gradient type solids. This model allows the prediction of different crack topologies and states. Of significant concern is the application of theoretical and numerical formulation of the phase field modeling into the commercial finite element software Abaqus in 2D and 3D. The fully coupled incremental variational formulation of phase field method is implemented by using the UEL and UMAT subroutines of Abaqus. The phase field method considerably reduces the implementation complexity of fracture problems as it removes the need for numerical tracking of discontinuities in the displacement field that are characteristic of discrete crack methods. This is accomplished by replacing the sharp discontinuities with a scalar damage phase field representing the diffuse crack topology wherein the amount of diffusion is controlled by a regularization parameter. The nonlinear coupled system consisting of the linear momentum equation and a diffusion type equation governing the phase field evolution is solved simultaneously via a Newton- Raphson approach. Post-processing of simulation results to be used as visualization module is performed via an additional UMAT subroutine implemented in the standard Abaqus viewer. In the same context, we propose a simple yet effective algorithm to initiate and propagate cracks in 2D geometries which is independent of both particular constitutive laws and specific element technology and dimension. It consists of a localization limiter in the form of the screened Poisson equation with, optionally, local mesh refinement. A staggered scheme for standard equilibrium and screened Cauchy equations is used. The remeshing part of the algorithm consists of a sequence of mesh subdivision and element erosion steps. Element subdivision is based on edge split operations using a given constitutive quantity (either damage or void fraction). Mesh smoothing makes use of edge contraction as function of a given constitutive quantity such as the principal stress or void fraction. To assess the robustness and accuracy of this algorithm, we use both quasi-brittle benchmarks and ductile tests. Furthermore, we introduce a computational approach regarding mechanical loading in microscale on an inelastically deforming composite material. The nanocomposites material of fully exfoliated clay/epoxy is shaped to predict macroscopic elastic and fracture related material parameters based on their fine-scale features. Two different configurations of polymer nanocomposites material (PNCs) have been studied. These configurations are fully bonded PNCs and PNCs with an interphase zone formation between the matrix and the clay reinforcement. The representative volume element of PNCs specimens with different clay weight contents, different aspect ratios, and different interphase zone thicknesses are generated by adopting Python scripting. Different constitutive models are employed for the matrix, the clay platelets, and the interphase zones. The brittle fracture behavior of the epoxy matrix and the interphase zones material are modeled using the phase field approach, whereas the stiff silicate clay platelets of the composite are designated as a linear elastic material. The comprehensive study investigates the elastic and fracture behavior of PNCs composites, in addition to predict Young's modulus, tensile strength, fracture toughness, surface energy dissipation, and cracks surface area in the composite for different material parameters, geometry, and interphase zones properties and thicknesses.}, subject = {Finite-Elemente-Methode}, language = {en} } @article{ChauDinhZiLeeetal., author = {Chau-Dinh, T. and Zi, Goangseup and Lee, P.S. and Song, Jeong-Hoon and Rabczuk, Timon}, title = {Phantom-node method for shell models with arbitrary cracks}, series = {Computers \& Structures}, journal = {Computers \& Structures}, doi = {10.1016/j.compstruc.2011.10.021}, abstract = {A phantom-node method is developed for three-node shell elements to describe cracks. This method can treat arbitrary cracks independently of the mesh. The crack may cut elements completely or partially. Elements are overlapped on the position of the crack, and they are partially integrated to implement the discontinuous displacement across the crack. To consider the element containing a crack tip, a new kinematical relation between the overlapped elements is developed. There is no enrichment function for the discontinuous displacement field. Several numerical examples are presented to illustrate the proposed method.}, subject = {Angewandte Mathematik}, language = {en} } @article{KaltenbacherLahmerMohretal., author = {Kaltenbacher, Barbara and Lahmer, Tom and Mohr, Marcus and Kaltenbacher, Manfred}, title = {PDE based determination of piezoelectric material tensors}, series = {European Journal of Applied Mathematics}, journal = {European Journal of Applied Mathematics}, doi = {10.25643/bauhaus-universitaet.3595}, pages = {383 -- 416}, abstract = {PDE based determination of piezoelectric material tensors.}, subject = {Angewandte Mathematik}, language = {en} } @unpublished{RadmardRahmaniKoenke, author = {Radmard Rahmani, Hamid and K{\"o}nke, Carsten}, title = {Passive Control of Tall Buildings Using Distributed Multiple Tuned Mass Dampers}, doi = {10.25643/bauhaus-universitaet.3859}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190311-38597}, pages = {43}, abstract = {The vibration control of the tall building during earthquake excitations is a challenging task due to their complex seismic behavior. This paper investigates the optimum placement and properties of the Tuned Mass Dampers (TMDs) in tall buildings, which are employed to control the vibrations during earthquakes. An algorithm was developed to spend a limited mass either in a single TMD or in multiple TMDs and distribute them optimally over the height of the building. The Non-dominated Sorting Genetic Algorithm (NSGA - II) method was improved by adding multi-variant genetic operators and utilized to simultaneously study the optimum design parameters of the TMDs and the optimum placement. The results showed that under earthquake excitations with noticeable amplitude in higher modes, distributing TMDs over the height of the building is more effective in mitigating the vibrations compared to the use of a single TMD system. From the optimization, it was observed that the locations of the TMDs were related to the stories corresponding to the maximum modal displacements in the lower modes and the stories corresponding to the maximum modal displacements in the modes which were highly activated by the earthquake excitations. It was also noted that the frequency content of the earthquake has significant influence on the optimum location of the TMDs.}, subject = {Schwingungsd{\"a}mpfer}, language = {en} } @inproceedings{UngerKoenke, author = {Unger, J{\"o}rg F. and K{\"o}nke, Carsten}, title = {PARAMETER IDENTIFICATION OF MESOSCALE MODELS FROM MACROSCOPIC TESTS USING BAYESIAN NEURAL NETWORKS}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2898}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28984}, pages = {5}, abstract = {In this paper, a parameter identification procedure using Bayesian neural networks is proposed. Based on a training set of numerical simulations, where the material parameters are simulated in a predefined range using Latin Hypercube sampling, a Bayesian neural network, which has been extended to describe the noise of multiple outputs using a full covariance matrix, is trained to approximate the inverse relation from the experiment (displacements, forces etc.) to the material parameters. The method offers not only the possibility to determine the parameters itself, but also the accuracy of the estimate and the correlation between these parameters. As a result, a set of experiments can be designed to calibrate a numerical model.}, subject = {Angewandte Informatik}, language = {en} } @inproceedings{NguyenTuanLahmerDatchevaetal., author = {Nguyen-Tuan, Long and Lahmer, Tom and Datcheva, Maria and Stoimenova, Eugenia and Schanz, Tom}, title = {PARAMETER IDENTIFICATION APPLYING IN COMPLEX THERMO-HYDRO-MECHANICAL PROBLEMS LIKE THE DESIGN OF BUFFER ELEMENTS}, series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, editor = {G{\"u}rlebeck, Klaus and Lahmer, Tom}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2816}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28162}, pages = {6}, abstract = {This study contributes to the identification of coupled THM constitutive model parameters via back analysis against information-rich experiments. A sampling based back analysis approach is proposed comprising both the model parameter identification and the assessment of the reliability of identified model parameters. The results obtained in the context of buffer elements indicate that sensitive parameter estimates generally obey the normal distribution. According to the sensitivity of the parameters and the probability distribution of the samples we can provide confidence intervals for the estimated parameters and thus allow a qualitative estimation on the identified parameters which are in future work used as inputs for prognosis computations of buffer elements. These elements play e.g. an important role in the design of nuclear waste repositories.}, subject = {Angewandte Informatik}, language = {en} } @article{ShiraziMohebbiAzadiKakavandetal., author = {Shirazi, A. H. N. and Mohebbi, Farzad and Azadi Kakavand, M. R. and He, B. and Rabczuk, Timon}, title = {Paraffin Nanocomposites for Heat Management of Lithium-Ion Batteries: A Computational Investigation}, series = {JOURNAL OF NANOMATERIALS}, journal = {JOURNAL OF NANOMATERIALS}, doi = {10.1155/2016/2131946}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170411-31141}, abstract = {Lithium-ion (Li-ion) batteries are currently considered as vital components for advances in mobile technologies such as those in communications and transport. Nonetheless, Li-ion batteries suffer from temperature rises which sometimes lead to operational damages or may even cause fire. An appropriate solution to control the temperature changes during the operation of Li-ion batteries is to embed batteries inside a paraffin matrix to absorb and dissipate heat. In the present work, we aimed to investigate the possibility of making paraffin nanocomposites for better heat management of a Li-ion battery pack. To fulfill this aim, heat generation during a battery charging/discharging cycles was simulated using Newman's well established electrochemical pseudo-2D model. We couple this model to a 3D heat transfer model to predict the temperature evolution during the battery operation. In the later model, we considered different paraffin nanocomposites structures made by the addition of graphene, carbon nanotubes, and fullerene by assuming the same thermal conductivity for all fillers. This way, our results mainly correlate with the geometry of the fillers. Our results assess the degree of enhancement in heat dissipation of Li-ion batteries through the use of paraffin nanocomposites. Our results may be used as a guide for experimental set-ups to improve the heat management of Li-ion batteries.}, subject = {Batterie}, language = {en} } @article{JiangZhuangRabczuk, author = {Jiang, Jin-Wu and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Orientation dependent thermal conductance in single-layer MoS 2}, series = {Scientific Reports}, journal = {Scientific Reports}, doi = {10.1038/srep02209}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170418-31417}, abstract = {We investigate the thermal conductivity in the armchair and zigzag MoS2 nanoribbons, by combining the non-equilibrium Green's function approach and the first-principles method. A strong orientation dependence is observed in the thermal conductivity. Particularly, the thermal conductivity for the armchair MoS2 nanoribbon is about 673.6 Wm-1 K-1 in the armchair nanoribbon, and 841.1 Wm-1 K-1 in the zigzag nanoribbon at room temperature. By calculating the Caroli transmission, we disclose the underlying mechanism for this strong orientation dependence to be the fewer phonon transport channels in the armchair MoS2 nanoribbon in the frequency range of [150, 200] cm-1. Through the scaling of the phonon dispersion, we further illustrate that the thermal conductivity calculated for the MoS2 nanoribbon is esentially in consistent with the superior thermal conductivity found for graphene.}, subject = {Mechanische Eigenschaft}, language = {en} } @article{GhasemiBrighentiZhuangetal., author = {Ghasemi, Hamid and Brighenti, Roberto and Zhuang, Xiaoying and Muthu, Jacob and Rabczuk, Timon}, title = {Optimum fiber content and distribution in fiber-reinforced solids using a reliability and NURBS based sequential optimization approach}, series = {Structural and Multidisciplinary Optimization}, journal = {Structural and Multidisciplinary Optimization}, pages = {99 -- 112}, abstract = {Optimum _ber content and distribution in _ber-reinforced solids using a reliability and NURBS based sequential optimization approach}, subject = {Angewandte Mathematik}, language = {en} } @article{MackeHiguchi, author = {Macke, M. and Higuchi, Shoko}, title = {Optimizing maintenance interventions for deteriorating structures using cost-benefit criteria}, series = {Journal of Structural Engineering}, journal = {Journal of Structural Engineering}, pages = {925 -- 934}, abstract = {Optimizing maintenance interventions for deteriorating structures using cost-benefit criteria}, subject = {Angewandte Mathematik}, language = {en} } @article{BucherFrangopol, author = {Bucher, Christian and Frangopol, D.M.}, title = {Optimization of lifetime maintenance strategies for deteriorting structures considering probabilities of violating safety, condition, and cost thresholds}, series = {Probabilistic Engineering Mechanics}, journal = {Probabilistic Engineering Mechanics}, pages = {1 -- 8}, abstract = {Optimization of lifetime maintenance strategies for deteriorting structures considering probabilities of violating safety, condition, and cost thresholds}, subject = {Angewandte Mathematik}, language = {en} } @article{GhasemiBrighentiZhuangetal., author = {Ghasemi, Hamid and Brighenti, Roberto and Zhuang, Xiaoying and Muthu, Jacob and Rabczuk, Timon}, title = {Optimization of fiber distribution in fiber reinforced composite by using NURBS functions}, series = {Computational Materials Science}, journal = {Computational Materials Science}, pages = {463 -- 473}, abstract = {Optimization of fiber distribution in fiber reinforced composite by using NURBS functions}, subject = {Angewandte Mathematik}, language = {en} } @article{BakarKramerBordasetal., author = {Bakar, I. and Kramer, O. and Bordas, St{\´e}phane Pierre Alain and Rabczuk, Timon}, title = {Optimization of Elastic Properties and Weaving Patterns of Woven Composites}, series = {Composite Structures}, journal = {Composite Structures}, pages = {575 -- 591}, abstract = {Optimization of Elastic Properties and Weaving Patterns of Woven Composites}, subject = {Angewandte Mathematik}, language = {en} } @phdthesis{Schemmann, author = {Schemmann, Christoph}, title = {Optimierung von radialen Verdichterlaufr{\"a}dern unter Ber{\"u}cksichtigung empirischer und analytischer Vorinformationen mittels eines mehrstufigen Sampling Verfahrens}, doi = {10.25643/bauhaus-universitaet.3974}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190910-39748}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {233}, abstract = {Turbomachinery plays an important role in many cases of energy generation or conversion. Therefore, turbomachinery is a promising approaching point for optimization in order to increase the efficiency of energy use. In recent years, the use of automated optimization strategies in combination with numerical simulation has become increasingly popular in many fields of engineering. The complex interactions between fluid and solid mechanics encountered in turbomachines on the one hand and the high computational expense needed to calculate the performance on the other hand, have, however, prevented a widespread use of these techniques in this field of engineering. The objective of this work was the development of a strategy for efficient metamodel based optimization of centrifugal compressor impellers. In this context, the main focus is the reduction of the required numerical expense. The central idea followed in this research was the incorporation of preliminary information acquired from low-fidelity computation methods and empirical correlations into the sampling process to identify promising regions of the parameter space. This information was then used to concentrate the numerically expensive high-fidelity computations of the fluid dynamic and structure mechanic performance of the impeller in these regions while still maintaining a good coverage of the whole parameter space. The development of the optimization strategy can be divided into three main tasks. Firstly, the available preliminary information had to be researched and rated. This research identified loss models based on one dimensional flow physics and empirical correlations as the best suited method to predict the aerodynamic performance. The loss models were calibrated using available performance data to obtain a high prediction quality. As no sufficiently exact models for the prediction of the mechanical loading of the impellercould be identified, a metamodel based on finite element computations was chosen for this estimation. The second task was the development of a sampling method which concentrates samples in regions of the parameter space where high quality designs are predicted by the preliminary information while maintaining a good overall coverage. As available methods like rejection sampling or Markov-chain Monte-Carlo methods did not meet the requirements in terms of sample distribution and input correlation, a new multi-fidelity sampling method called "Filtered Sampling"has been developed. The last task was the development of an automated computational workflow. This workflow encompasses geometry parametrization, geometry generation, grid generation and computation of the aerodynamic performance and the structure mechanic loading. Special emphasis was put into the development of a geometry parametrization strategy based on fluid mechanic considerations to prevent the generation of physically inexpedient designs. Finally, the optimization strategy, which utilizes the previously developed tools, was successfully employed to carry out three optimization tasks. The efficiency of the method was proven by the first and second testcase where an existing compressor design was optimized by the presented method. The results were comparable to optimizations which did not take preliminary information into account, while the required computational expense cloud be halved. In the third testcase, the method was applied to generate a new impeller design. In contrast to the previous examples, this optimization featuredlargervariationsoftheimpellerdesigns. Therefore, theapplicability of the method to parameter spaces with significantly varying designs could be proven, too.}, subject = {Simulation}, language = {en} } @article{LahmerKoenkeBettzieche, author = {Lahmer, Tom and K{\"o}nke, Carsten and Bettzieche, Volker}, title = {Optimale Positionierung von Messeinrichtungen an Staumauern zur Bauwerks{\"u}berwachung}, series = {WASSERWIRTSCHAFT}, journal = {WASSERWIRTSCHAFT}, pages = {16 -- 16}, abstract = {Optimale Positionierung von Messeinrichtungen an Staumauern zur Bauwerks{\"u}berwachung}, subject = {Angewandte Mathematik}, language = {de} } @article{BrehmZabelBucher, author = {Brehm, Maik and Zabel, Volkmar and Bucher, Christian}, title = {Optimal reference sensor positions for applications in model updating using output-only vibration test data based on random excitation: Part 2 - improved search strategy and experimental case study}, series = {Mechanical Systems and Signal Processing}, journal = {Mechanical Systems and Signal Processing}, abstract = {Optimal reference sensor positions for applications in model updating using output-only vibration test data based on random excitation: Part 2 - improved search strategy and experimental case study}, subject = {Angewandte Mathematik}, language = {en} } @article{LahmerKoenkeBettzieche, author = {Lahmer, Tom and K{\"o}nke, Carsten and Bettzieche, Volker}, title = {Optimal positioning of sensors for the monitoring of water dams}, series = {WASSERWIRTSCHAFT}, journal = {WASSERWIRTSCHAFT}, pages = {16 -- 19}, abstract = {Optimal positioning of sensors for the monitoring of water dams}, subject = {Angewandte Mathematik}, language = {de} } @article{LahmerKaltenbacherSchulz, author = {Lahmer, Tom and Kaltenbacher, Barbara and Schulz, V.}, title = {Optimal measurement selection for piezoelectric material tensor identification}, series = {Inverse Problems in Science and Engineering}, journal = {Inverse Problems in Science and Engineering}, doi = {10.25643/bauhaus-universitaet.3593}, pages = {369 -- 387}, abstract = {Optimal measurement selection for piezoelectric material tensor identification.}, subject = {Angewandte Mathematik}, language = {en} } @article{Lahmer, author = {Lahmer, Tom}, title = {Optimal experimental design for nonlinear ill-posed problems applied to gravity dams}, series = {Inverse Problems}, journal = {Inverse Problems}, abstract = {Optimal experimental design for nonlinear ill-posed problems applied to gravity dams}, subject = {Angewandte Mathematik}, language = {en} } @phdthesis{Zabel, author = {Zabel, Volkmar}, title = {Operational modal analysis - Theory and aspects of application in civil engineering}, editor = {K{\"o}nke, Carsten and Lahmer, Tom and Rabczuk, Timon}, doi = {10.25643/bauhaus-universitaet.4006}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20191030-40061}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {263}, abstract = {In recent years the demand on dynamic analyses of existing structures in civil engineering has remarkably increased. These analyses are mainly based on numerical models. Accordingly, the generated results depend on the quality of the used models. Therefore it is very important that the models describe the considered systems such that the behaviour of the physical structure is realistically represented. As any model is based on assumptions, there is always a certain degree of uncertainty present in the results of a simulation based on the respective numerical model. To minimise these uncertainties in the prediction of the response of a structure to a certain loading, it has become common practice to update or calibrate the parameters of a numerical model based on observations of the structural behaviour of the respective existing system. The determination of the behaviour of an existing structure requires experimental investigations. If the numerical analyses concern the dynamic response of a structure it is sensible to direct the experimental investigations towards the identification of the dynamic structural behaviour which is determined by the modal parameters of the system. In consequence, several methods for the experimental identification of modal parameters have been developed since the 1980ies. Due to various technical restraints in civil engineering which limit the possibilities to excitate a structure with economically reasonable effort, several methods have been developed that allow a modal identification form tests with an ambient excitation. The approach of identifying modal parameters only from measurements of the structural response without precise knowledge of the excitation is known as output-only or operational modal analysis. Since operational modal analysis (OMA) can be considered as a link between numerical modelling and simulation on the one hand and the dynamic behaviour of an existing structure on the other hand, the respective algorithms connect both the concepts of structural dynamics and mathematical tools applied within the processing of experimental data. Accordingly, the related theoretical topics are revised after an introduction into the topic. Several OMA methods have been developed over the last decades. The most established algorithms are presented here and their application is illustrated by means of both a small numerical and an experimental example. Since experimentally obtained results always underly manifold influences, an appropriate postprocessing of the results is necessary for a respective quality assessment. This quality assessment does not only require respective indicators but should also include the quantification of uncertainties. One special feature in modal testing is that it is common to instrument the structure in different sensor setups to improve the spacial resolution of identified mode shapes. The modal information identified from tests in several setups needs to be merged a posteriori. Algorithms to cope with this problem are also presented. Due to the fact that the amount of data generated in modal tests can become very large, manual processing can become extremely expensive or even impossible, for example in the case of a long-term continuous structural monitoring. In these situations an automated analysis and postprocessing are essential. Descriptions of respective methodologies are therefore also included in this work. Every structural system in civil engineering is unique and so also every identification of modal parameters has its specific challenges. Some aspects that can be faced in practical applications of operational modal analysis are presented and discussed in a chapter that is dedicated specific problems that an analyst may have to overcome. Case studies of systems with very close modes, with limited accessibility as well as the application of different OMA methods are described and discussed. In this context the focus is put on several types of uncertainty that may occur in the multiple stages of an operational modal analysis. In literature only very specific uncertainties at certain stages of the analysis are addressed. Here, the topic of uncertainties has been considered in a broader sense and approaches for treating respective problems are suggested. Eventually, it is concluded that the methodologies of operatinal modal analysis and related technical solutions have been well-engineered already. However, as in any discipline that includes experiments, a certain degree of uncertainty always remains in the results. From these conclusions has been derived a demand for further research and development that should be directed towards the minimisation of these uncertainties and to a respective optimisation of the steps and corresponding parameters included in an operational modal analysis.}, subject = {Modalanalyse}, language = {en} } @article{TalebiSamaniegoSamaniegoetal., author = {Talebi, Hossein and Samaniego, C. and Samaniego, Esteban and Rabczuk, Timon}, title = {On the numerical stability and mass-lumping schemes for explicit enriched meshfree methods}, series = {International Journal for Numerical Methods in Engineering}, journal = {International Journal for Numerical Methods in Engineering}, doi = {10.1002/nme.3275}, pages = {1009 -- 1027}, abstract = {Meshfree methods (MMs) such as the element free Galerkin (EFG)method have gained popularity because of some advantages over other numerical methods such as the finite element method (FEM). A group of problems that have attracted a great deal of attention from the EFG method community includes the treatment of large deformations and dealing with strong discontinuities such as cracks. One efficient solution to model cracks is adding special enrichment functions to the standard shape functions such as extended FEM, within the FEM context, and the cracking particles method, based on EFG method. It is well known that explicit time integration in dynamic applications is conditionally stable. Furthermore, in enriched methods, the critical time step may tend to very small values leading to computationally expensive simulations. In this work, we study the stability of enriched MMs and propose two mass-lumping strategies. Then we show that the critical time step for enriched MMs based on lumped mass matrices is of the same order as the critical time step of MMs without enrichment. Moreover, we show that, in contrast to extended FEM, even with a consistent mass matrix, the critical time step does not vanish even when the crack directly crosses a node.}, subject = {Angewandte Mathematik}, language = {en} } @phdthesis{Hamdia, author = {Hamdia, Khader}, title = {On the fracture toughness of polymeric nanocomposites: Comprehensive stochastic and numerical studies}, doi = {10.25643/bauhaus-universitaet.3765}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20180712-37652}, school = {Bauhaus-Universit{\"a}t Weimar}, abstract = {Polymeric nanocomposites (PNCs) are considered for numerous nanotechnology such as: nano-biotechnology, nano-systems, nanoelectronics, and nano-structured materials. Commonly , they are formed by polymer (epoxy) matrix reinforced with a nanosized filler. The addition of rigid nanofillers to the epoxy matrix has offered great improvements in the fracture toughness without sacrificing other important thermo-mechanical properties. The physics of the fracture in PNCs is rather complicated and is influenced by different parameters. The presence of uncertainty in the predicted output is expected as a result of stochastic variance in the factors affecting the fracture mechanism. Consequently, evaluating the improved fracture toughness in PNCs is a challenging problem. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have been employed to predict the fracture energy of polymer/particle nanocomposites. The ANN and ANFIS models were constructed, trained, and tested based on a collection of 115 experimental datasets gathered from the literature. The performance evaluation indices of the developed ANN and ANFIS showed relatively small error, with high coefficients of determination (R2), and low root mean square error and mean absolute percentage error. In the framework for uncertainty quantification of PNCs, a sensitivity analysis (SA) has been conducted to examine the influence of uncertain input parameters on the fracture toughness of polymer/clay nanocomposites (PNCs). The phase-field approach is employed to predict the macroscopic properties of the composite considering six uncertain input parameters. The efficiency, robustness, and repeatability are compared and evaluated comprehensively for five different SA methods. The Bayesian method is applied to develop a methodology in order to evaluate the performance of different analytical models used in predicting the fracture toughness of polymeric particles nanocomposites. The developed method have considered the model and parameters uncertainties based on different reference data (experimental measurements) gained from the literature. Three analytical models differing in theory and assumptions were examined. The coefficients of variation of the model predictions to the measurements are calculated using the approximated optimal parameter sets. Then, the model selection probability is obtained with respect to the different reference data. Stochastic finite element modeling is implemented to predict the fracture toughness of polymer/particle nanocomposites. For this purpose, 2D finite element model containing an epoxy matrix and rigid nanoparticles surrounded by an interphase zone is generated. The crack propagation is simulated by the cohesive segments method and phantom nodes. Considering the uncertainties in the input parameters, a polynomial chaos expansion (PCE) surrogate model is construed followed by a sensitivity analysis.}, subject = {Bruch}, language = {en} } @article{SilaniTalebiArnoldetal., author = {Silani, Mohammad and Talebi, Hossein and Arnold, Daniel and Ziaei-Rad, S. and Rabczuk, Timon}, title = {On the coupling of a commercial finite element package with lammps for multiscale modeling of materials}, series = {Steel Research International}, journal = {Steel Research International}, abstract = {On the coupling of a commercial finite element package with lammps for multiscale modeling of materials}, subject = {Angewandte Mathematik}, language = {en} } @article{BucherPham, author = {Bucher, Christian and Pham, Hoang Anh}, title = {On model updating of existing structures utilizing measured dynamic responses}, series = {Structure and Infrastructure Engineering}, journal = {Structure and Infrastructure Engineering}, pages = {135 -- 143}, abstract = {On model updating of existing structures utilizing measured dynamic responses}, subject = {Angewandte Mathematik}, language = {en} } @article{ValizadehNatarajanGonzalezEstradaetal., author = {Valizadeh, Navid and Natarajan, S. and Gonzalez-Estrada, O.A. and Rabczuk, Timon and Tinh Quoc, Bui and Bordas, St{\´e}phane Pierre Alain}, title = {NURBS-based finite element analysis of functionally graded plates: static bending, vibration, buckling and flutter}, series = {Composite Structures}, journal = {Composite Structures}, pages = {309 -- 326}, abstract = {NURBS-based finite element analysis of functionally graded plates: static bending, vibration, buckling and flutter}, subject = {Angewandte Mathematik}, language = {en} } @article{BruhinStockDrueckeretal., author = {Bruhin, R. and Stock, U.A. and Dr{\"u}cker, J.-P. and Azhari, T. and Wippermann, J. and Albes, J.M. and Hintze, D. and Eckardt, Stefan and K{\"o}nke, Carsten and Wahlers, T.}, title = {Numerical simulation techniques to study the structural response of the human chest following median sternotomy}, series = {The Annals of Thoracic Surgery}, journal = {The Annals of Thoracic Surgery}, pages = {623 -- 630}, abstract = {Numerical simulation techniques to study the structural response of the human chest following median sternotomy}, subject = {Angewandte Mathematik}, language = {en} } @inproceedings{Itam, author = {Itam, Zarina}, title = {NUMERICAL SIMULATION OF THERMO-HYGRAL ALKALI-SILICA REACTION MODEL IN CONCRETE AT THE MESOSCALE}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2853}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28536}, pages = {7}, abstract = {This research aims to model Alkali-Silica Reaction gel expansion in concrete under the influence of hygral and thermal loading, based on experimental results. ASR provokes a heterogeneous expansion in concrete leading to dimensional changes and eventually the premature failure of the concrete structure. This can result in map cracking on the concrete surface which will decrease the concrete stiffness. Factors that influence ASR are parameters such as the cement alkalinity, the number of deleterious silica from the aggregate used, concrete porosity, and external factors like temperature, humidity and external source of alkali from ingression of deicing salts. Uncertainties of the influential factors make ASR a difficult phenomenon to solve; hence my approach to this matter is to solve the problem using stochastic modelling, where a numerical simulation of concrete cross-section with integration of experimental results from Finger-Institute for Building Materials Science at the Bauhaus-Universit{\"a}t Weimar. The problem is formulated as a multi-field problem, combining heat transfer, fluid transfer and the reaction rate model with the mechanical stress field. Simulation is performed as a mesoscale model considering aggregates and mortar matrix. The reaction rate model will be conducted using experimental results from concrete expansions due to ASR gained from concrete prism tests. Expansive strains values for transient environmental conditions due to the reaction rate will be determined from calculation based on the reaction rate model. Results from these models will be able to predict the rate of ASR expansion and the cracking propagation that may arise.}, subject = {Angewandte Informatik}, language = {en} } @phdthesis{Zacharias, author = {Zacharias, Christin}, title = {Numerical Simulation Models for Thermoelastic Damping Effects}, doi = {10.25643/bauhaus-universitaet.4735}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20221116-47352}, school = {Bauhaus-Universit{\"a}t Weimar}, pages = {191}, abstract = {Finite Element Simulations of dynamically excited structures are mainly influenced by the mass, stiffness, and damping properties of the system, as well as external loads. The prediction quality of dynamic simulations of vibration-sensitive components depends significantly on the use of appropriate damping models. Damping phenomena have a decisive influence on the vibration amplitude and the frequencies of the vibrating structure. However, developing realistic damping models is challenging due to the multiple sources that cause energy dissipation, such as material damping, different types of friction, or various interactions with the environment. This thesis focuses on thermoelastic damping, which is the main cause of material damping in homogeneous materials. The effect is caused by temperature changes due to mechanical strains. In vibrating structures, temperature gradients arise in adjacent tension and compression areas. Depending on the vibration frequency, they result in heat flows, leading to increased entropy and the irreversible transformation of mechanical energy into thermal energy. The central objective of this thesis is the development of efficient simulation methods to incorporate thermoelastic damping in finite element analyses based on modal superposition. The thermoelastic loss factor is derived from the structure's mechanical mode shapes and eigenfrequencies. In subsequent analyses that are performed in the time and frequency domain, it is applied as modal damping. Two approaches are developed to determine the thermoelastic loss in thin-walled plate structures, as well as three-dimensional solid structures. The realistic representation of the dissipation effects is verified by comparing the simulation results with experimentally determined data. Therefore, an experimental setup is developed to measure material damping, excluding other sources of energy dissipation. The three-dimensional solid approach is based on the determination of the generated entropy and therefore the generated heat per vibration cycle, which is a measure for thermoelastic loss in relation to the total strain energy. For thin plate structures, the amount of bending energy in a modal deformation is calculated and summarized in the so-called Modal Bending Factor (MBF). The highest amount of thermoelastic loss occurs in the state of pure bending. Therefore, the MBF enables a quantitative classification of the mode shapes concerning the thermoelastic damping potential. The results of the developed simulations are in good agreement with the experimental results and are appropriate to predict thermoelastic loss factors. Both approaches are based on modal superposition with the advantage of a high computational efficiency. Overall, the modeling of thermoelastic damping represents an important component in a comprehensive damping model, which is necessary to perform realistic simulations of vibration processes.}, subject = {Werkstoffd{\"a}mpfung}, language = {en} }