@phdthesis{Hatahet,
  author    = {Hatahet, Tareq},
  title     = {On the Analysis of the Disproportionate Structural Collapse in RC Buildings},
  doi       = {10.25643/bauhaus-universitaet.3740},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20180329-37405},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {243},
  abstract  = {Increasing structural robustness is the goal which is of interest for structural engineering community. The partial collapse of RC buildings is subject of this dissertation. Understanding the robustness of RC buildings will guide the development of safer structures against abnormal loading scenarios such as; explosions, earthquakes, fine, and/or long-term accumulation effects leading to deterioration or fatigue. Any of these may result in local immediate structural damage, that can propagate to the rest of the structure causing what is known by the disproportionate collapse. This work handels collapse propagation through various analytical approaches which simplifies the mechanical description of damaged reinfoced concrete structures due to extreme acidental event.},
  subject      = {Beton},
  language  = {en}
}
@phdthesis{Froebel,
  author    = {Fr{\"o}bel, Toni},
  title     = {Data coupled civil engineering applications: Modeling and quality assessment methods},
  publisher = {Verlag der Bauhaus-Universit{\"a}t Weimar 2013},
  address   = {Weimar},
  isbn      = {978-3-86068-486-3},
  doi       = {10.25643/bauhaus-universitaet.1836},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20130128-18366},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {153},
  abstract  = {The planning process in civil engineering is highly complex and not manageable in its entirety. The state of the art decomposes complex tasks into smaller, manageable sub-tasks. Due to the close interrelatedness of the sub-tasks, it is essential to couple them. However, from a software engineering point of view, this is quite challenging to do because of the numerous incompatible software applications on the market. This study is concerned with two main objectives: The first is the generic formulation of coupling strategies in order to support engineers in the implementation and selection of adequate coupling strategies. This has been achieved by the use of a coupling pattern language combined with a four-layered, metamodel architecture, whose applicability has been performed on a real coupling scenario. The second one is the quality assessment of coupled software. This has been developed based on the evaluated schema mapping. This approach has been described using mathematical expressions derived from the set theory and graph theory by taking the various mapping patterns into account. Moreover, the coupling quality has been evaluated within the formalization process by considering the uncertainties that arise during mapping and has resulted in global quality values, which can be used by the user to assess the exchange. Finally, the applicability of the proposed approach has been shown using an engineering case study.},
  subject      = {Data exchange, Schema mapping, Quality assessment, Uncertainty, Coupling, BIM, Design patterns, Metamodel architecture},
  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}
}
@phdthesis{Hanna,
  author    = {Hanna, John},
  title     = {Computational Fracture Modeling and Design of Encapsulation-Based Self-Healing Concrete Using XFEM and Cohesive Surface Technique},
  doi       = {10.25643/bauhaus-universitaet.4746},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20221124-47467},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {125},
  abstract  = {Encapsulation-based self-healing concrete (SHC) is the most promising technique for providing a self-healing mechanism to concrete. This is due to its capacity to heal fractures effectively without human interventions, extending the operational life and lowering maintenance costs. The healing mechanism is created by embedding capsules containing the healing agent inside the concrete. The healing agent will be released once the capsules are fractured and the healing occurs in the vicinity of the damaged part. The healing efficiency of the SHC is still not clear and depends on several factors; in the case of microcapsules SHC the fracture of microcapsules is the most important aspect to release the healing agents and hence heal the cracks. This study contributes to verifying the healing efficiency of SHC and the fracture mechanism of the microcapsules. Extended finite element method (XFEM) is a flexible, and powerful discrete crack method that allows crack propagation without the requirement for re-meshing and has been shown high accuracy for modeling fracture in concrete. In this thesis, a computational fracture modeling approach of Encapsulation-based SHC is proposed based on the XFEM and cohesive surface technique (CS) to study the healing efficiency and the potential of fracture and debonding of the microcapsules or the solidified healing agents from the concrete matrix as well. The concrete matrix and a microcapsule shell both are modeled by the XFEM and combined together by CS. The effects of the healed-crack length, the interfacial fracture properties, and microcapsule size on the load carrying capability and fracture pattern of the SHC have been studied. The obtained results are compared to those obtained from the zero thickness cohesive element approach to demonstrate the significant accuracy and the validity of the proposed simulation. The present fracture simulation is developed to study the influence of the capsular clustering on the fracture mechanism by varying the contact surface area of the CS between the microcapsule shell and the concrete matrix. The proposed fracture simulation is expanded to 3D simulations to validate the 2D computational simulations and to estimate the accuracy difference ratio between 2D and 3D simulations. In addition, a proposed design method is developed to design the size of the microcapsules consideration of a sufficient volume of healing agent to heal the expected crack width. This method is based on the configuration of the unit cell (UC), Representative Volume Element (RVE), Periodic Boundary Conditions (PBC), and associated them to the volume fraction (Vf) and the crack width as variables. The proposed microcapsule design is verified through computational fracture simulations.},
  subject      = {Beton},
  language  = {en}
}
@phdthesis{Nanthakumar,
  author    = {Nanthakumar, S.S.},
  title     = {Inverse and optimization problems in piezoelectric materials using Extended Finite Element Method and Level sets},
  doi       = {10.25643/bauhaus-universitaet.2709},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20161128-27095},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  abstract  = {Piezoelectric materials are used in several applications as sensors and actuators where they experience high stress and electric field concentrations as a result of which they may fail due to fracture. Though there are many analytical and experimental works on piezoelectric fracture mechanics. There are very few studies about damage detection, which is an interesting way to prevent the failure of these ceramics. An iterative method to treat the inverse problem of detecting cracks and voids in piezoelectric structures is proposed. Extended finite element method (XFEM) is employed for solving the inverse problem as it allows the use of a single regular mesh for large number of iterations with different flaw geometries. Firstly, minimization of cost function is performed by Multilevel Coordinate Search (MCS) method. The XFEM-MCS methodology is applied to two dimensional electromechanical problems where flaws considered are straight cracks and elliptical voids. Then a numerical method based on combination of classical shape derivative and level set method for front propagation used in structural optimization is utilized to minimize the cost function. The results obtained show that the XFEM-level set methodology is effectively able to determine the number of voids in a piezoelectric structure and its corresponding locations. The XFEM-level set methodology is improved to solve the inverse problem of detecting inclusion interfaces in a piezoelectric structure. The material interfaces are implicitly represented by level sets which are identified by applying regularisation using total variation penalty terms. The formulation is presented for three dimensional structures and inclusions made of different materials are detected by using multiple level sets. The results obtained prove that the iterative procedure proposed can determine the location and approximate shape of material subdomains in the presence of higher noise levels. Piezoelectric nanostructures exhibit size dependent properties because of surface elasticity and surface piezoelectricity. Initially a study to understand the influence of surface elasticity on optimization of nano elastic beams is performed. The boundary of the nano structure is implicitly represented by a level set function, which is considered as the design variable in the optimization process. Two objective functions, minimizing the total potential energy of a nanostructure subjected to a material volume constraint and minimizing the least square error compared to a target displacement, are chosen for the numerical examples. The numerical examples demonstrate the importance of size and aspect ratio in determining how surface effects impact the optimized topology of nanobeams. Finally a conventional cantilever energy harvester with a piezoelectric nano layer is analysed. The presence of surface piezoelectricity in nano beams and nano plates leads to increase in electromechanical coupling coefficient. Topology optimization of these piezoelectric structures in an energy harvesting device to further increase energy conversion using appropriately modified XFEM-level set algorithm is performed .},
  subject      = {Finite-Elemente-Methode},
  language  = {de}
}
@phdthesis{Wang,
  author    = {Wang, Cuixia},
  title     = {Nanomechanical Resonators Based on Quasi-two-dimensional Materials},
  doi       = {10.25643/bauhaus-universitaet.3760},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20180709-37609},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  abstract  = {Advances in nanotechnology lead to the development of nano-electro-mechanical systems (NEMS) such as nanomechanical resonators with ultra-high resonant frequencies. The ultra-high-frequency resonators have recently received significant attention for wide-ranging applications such as molecular separation, molecular transportation, ultra-high sensitive sensing, high-frequency signal processing, and biological imaging. It is well known that for micrometer length scale, first-principles technique, the most accurate approach, poses serious limitations for comparisons with experimental studies. For such larger size, classical molecular dynamics (MD) simulations are desirable, which require interatomic potentials. Additionally, a mesoscale method such as the coarse-grained (CG) method is another useful method to support simulations for even larger system sizes. Furthermore, quasi-two-dimensional (Q2D) materials have attracted intensive research interest due to their many novel properties over the past decades. However, the energy dissipation mechanisms of nanomechanical resonators based on several Q2D materials are still unknown. In this work, the addressed main issues include the development of the CG models for molybdenum disulphide (MoS2), investigation of the mechanism effects on black phosphorus (BP) nanoresonators and the application of graphene nanoresonators. The primary coverage and results of the dissertation are as follows: Method development. Firstly, a two-dimensional (2D) CG model for single layer MoS2 (SLMoS2) is analytically developed. The Stillinger-Weber (SW) potential for this 2D CG model is further parametrized, in which all SW geometrical parameters are determined analytically according to the equilibrium condition for each individual potential term, while the SW energy parameters are derived analytically based on the valence force field model. Next, the 2D CG model is further simplified to one-dimensional (1D) CG model, which describes the 2D SLMoS2 structure using a 1D chain model. This 1D CG model is applied to investigate the relaxed configuration and the resonant oscillation of the folded SLMoS2. Owning to the simplicity nature of the 1D CG model, the relaxed configuration of the folded SLMoS2 is determined analytically, and the resonant oscillation frequency is derived analytically. Considering the increasing interest in studying the properties of other 2D layered materials, and in particular those in the semiconducting transition metal dichalcogenide class like MoS2, the CG models proposed in current work provide valuable simulation approaches. Mechanism understanding. Two energy dissipation mechanisms of BP nanoresonators are focused exclusively, i.e. mechanical strain effects and defect effects (including vacancy and oxidation). Vacancy defect is intrinsic damping factor for the quality (Q)-factor, while mechanical strain and oxidation are extrinsic damping factors. Intrinsic dissipation (induced by thermal vibrations) in BP resonators (BPRs) is firstly investigated. Specifically, classical MD simulations are performed to examine the temperature dependence for the Q-factor of the single layer BPR (SLBPR) along the armchair and zigzag directions, where two-step fitting procedure is used to extract the frequency and Q-factor from the kinetic energy time history. The Q-factors of BPRs are evaluated through comparison with those of graphene and MoS2 nanoresonators. Next, effects of mechanical strain, vacancy and oxidation on BP nanoresonators are investigated in turn. Considering the increasing interest in studying the properties of BP, and in particular the lack of theoretical study for the BPRs, the results in current work provide a useful reference. Application. A novel application for graphene nanoresonators, using them to self-assemble small nanostructures such as water chains, is proposed. All of the underlying physics enabling this phenomenon is elucidated. In particular, by drawing inspiration from macroscale self-assembly using the higher order resonant modes of Chladni plates, classical MD simulations are used to investigate the self-assembly of water molecules using graphene nanoresonators. An analytic formula for the critical resonant frequency based on the interaction between water molecules and graphene is provided. Furthermore, the properties of the water chains assembled by the graphene nanoresonators are studied.},
  subject      = {Nanomechanik},
  language  = {en}
}
@phdthesis{Vollmering,
  author    = {Vollmering, Max},
  title     = {Damage Localization of Mechanical Structures by Subspace Identification and Krein Space Based H-infinity Estimation},
  doi       = {10.25643/bauhaus-universitaet.3772},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20180730-37728},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {205},
  abstract  = {This dissertation is devoted to the theoretical development and experimental laboratory verification of a new damage localization method: The state projection estimation error (SP2E). This method is based on the subspace identification of mechanical structures, Krein space based H-infinity estimation and oblique projections. To explain method SP2E, several theories are discussed and laboratory experiments have been conducted and analysed. A fundamental approach of structural dynamics is outlined first by explaining mechanical systems based on first principles. Following that, a fundamentally different approach, subspace identification, is comprehensively explained. While both theories, first principle and subspace identification based mechanical systems, may be seen as widespread methods, barely known and new techniques follow up. Therefore, the indefinite quadratic estimation theory is explained. Based on a Popov function approach, this leads to the Krein space based H-infinity theory. Subsequently, a new method for damage identification, namely SP2E, is proposed. Here, the introduction of a difference process, the analysis by its average process power and the application of oblique projections is discussed in depth. Finally, the new method is verified in laboratory experiments. Therefore, the identification of a laboratory structure at Leipzig University of Applied Sciences is elaborated. Then structural alterations are experimentally applied, which were localized by SP2E afterwards. In the end four experimental sensitivity studies are shown and discussed. For each measurement series the structural alteration was increased, which was successfully tracked by SP2E. The experimental results are plausible and in accordance with the developed theories. By repeating these experiments, the applicability of SP2E for damage localization is experimentally proven.},
  subject      = {Strukturmechanik},
  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}
}
@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}
}
@phdthesis{Kessler2018,
  author    = {Keßler, Andrea},
  title     = {Matrix-free voxel-based finite element method for materials with heterogeneous microstructures},
  doi       = {10.25643/bauhaus-universitaet.3844},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190116-38448},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {113},
  year      = {2018},
  abstract  = {Modern image detection techniques such as micro computer tomography (μCT), magnetic resonance imaging (MRI) and scanning electron microscopy (SEM) provide us with high resolution images of the microstructure of materials in a non-invasive and convenient way. They form the basis for the geometrical models of high-resolution analysis, so called image-based analysis. However especially in 3D, discretizations of these models reach easily the size of 100 Mill. degrees of freedoms and require extensive hardware resources in terms of main memory and computing power to solve the numerical model. Consequently, the focus of this work is to combine and adapt numerical solution methods to reduce the memory demand first and then the computation time and therewith enable an execution of the image-based analysis on modern computer desktops. Hence, the numerical model is a straightforward grid discretization of the voxel-based (pixels with a third dimension) geometry which omits the boundary detection algorithms and allows reduced storage of the finite element data structure and a matrix-free solution algorithm. This in turn reduce the effort of almost all applied grid-based solution techniques and results in memory efficient and numerically stable algorithms for the microstructural models. Two variants of the matrix-free algorithm are presented. The efficient iterative solution method of conjugate gradients is used with matrix-free applicable preconditioners such as the Jacobi and the especially suited multigrid method. The jagged material boundaries of the voxel-based mesh are smoothed through embedded boundary elements which contain different material information at the integration point and are integrated sub-cell wise though without additional boundary detection. The efficiency of the matrix-free methods can be retained.},
  subject      = {Dissertation},
  language  = {en}
}
@phdthesis{Goebel,
  author    = {G{\"o}bel, Luise},
  title     = {Experimental and semi-analytical multiscale approaches for the characterization of the elastic and viscoelastic behavior of polymer-modified cement-based materials},
  publisher = {Bauhaus-Universit{\"a}tsverlag},
  address   = {Weimar},
  isbn      = {978-3-95773-269-9},
  doi       = {10.25643/bauhaus-universitaet.3827},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181211-38279},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {259},
  abstract  = {Polymer-modified cement concrete (PCC) is a heterogeneous building material with a hierarchically organized microstructure. Therefore, continuum micromechanics-based multiscale models represent a promising method to estimate the mechanical properties. By means of a bottom-up approach, homogenized properties at the macroscopic scale are derived considering microstructural characteristics. The extension of existing multiscale models for the application to PCC is the main objective of this work. For that, cross-scale experimental studies are required. Both macroscopic and microscopic mechanical tests are performed to characterize the elastic and viscoelastic properties of different PCC. The comparison between experiment and model prediction illustrates the success of the modeling approach.},
  subject      = {Elastizit{\"a}tsmodul},
  language  = {en}
}
@phdthesis{Alalade,
  author    = {Alalade, Muyiwa},
  title     = {An Enhanced Full Waveform Inversion Method for the Structural Analysis of Dams},
  doi       = {10.25643/bauhaus-universitaet.3956},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190813-39566},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  abstract  = {Since the Industrial Revolution in the 1700s, the high emission of gaseous wastes into the atmosphere from the usage of fossil fuels has caused a general increase in temperatures globally. To combat the environmental imbalance, there is an increase in the demand for renewable energy sources. Dams play a major role in the generation of "green" energy. However, these structures require frequent and strict monitoring to ensure safe and efficient operation. To tackle the challenges faced in the application of convention dam monitoring techniques, this work proposes the inverse analysis of numerical models to identify damaged regions in the dam. Using a dynamic coupled hydro-mechanical Extended Finite Element Method (XFEM) model and a global optimization strategy, damage (crack) in the dam is identified. By employing seismic waves to probe the dam structure, a more detailed information on the distribution of heterogeneous materials and damaged regions are obtained by the application of the Full Waveform Inversion (FWI) method. The FWI is based on a local optimization strategy and thus it is highly dependent on the starting model. A variety of data acquisition setups are investigated, and an optimal setup is proposed. The effect of different starting models and noise in the measured data on the damage identification is considered. Combining the non-dependence of a starting model of the global optimization strategy based dynamic coupled hydro-mechanical XFEM method and the detailed output of the local optimization strategy based FWI method, an enhanced Full Waveform Inversion is proposed for the structural analysis of dams.},
  subject      = {Talsperre},
  language  = {en}
}
@masterthesis{Marwitz2011,
  type      = {Bachelor Thesis},
  author    = {Marwitz, Simon Jakob},
  title     = {Untersuchungen zur optimalen Sensorpositionierung bei der experimentellen Modalanalyse},
  doi       = {10.25643/bauhaus-universitaet.1531},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20120128-15311},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {70},
  year      = {2011},
  abstract  = {Experimentelle Untersuchung eines Verfahrens zur optimalen Positionierung von Referenzsensoren bei der experimentellen Modalanalyse mit output-only Methoden nach Brehm (2011). Untersuchung des Einflusses der Referenzsensorpositionierung, -anzahl und der Positionierung der wandernden Sensoren unter Anwendung des Stochastic-Subspace-Verfahrens zur Auswertung der output-only Messdaten.},
  subject      = {Modalanalyse},
  language  = {de}
}
@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}
}
@misc{Adler,
  type      = {Master Thesis},
  author    = {Adler, Maria},
  title     = {Energiedissipation durch F{\"u}gestellend{\"a}mpfung in Leichtbauanwendungen},
  doi       = {10.25643/bauhaus-universitaet.4394},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210316-43949},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {71},
  abstract  = {In vielen Leichtbauanwendungen ist der begrenzende Faktor die Schwingungsanf{\"a}lligkeit der Bauteile. Eine M{\"o}glichkeit der Begrenzung von Schwingungsamplituden ist der gezielte Einsatz von Reibungsd{\"a}mpfung in Leichtbaustrukturen. In dieser Arbeit wird der Einfluss dieser Art von Energiedissipation auf Leichtmetallstrukturen sowie topologieoptimierte Bauteil untersucht. Betrachtet werden dabei die Positionierung, Dimensionierung sowie die Reibeigenschaften dissipativer Elemente.},
  subject      = {Leichtbau},
  language  = {de}
}
@phdthesis{HosseinNezhadShirazi,
  author    = {Hossein Nezhad Shirazi, Ali},
  title     = {Multi-Scale Modeling of Lithium ion Batteries: a thermal management approach and molecular dynamic studies},
  doi       = {10.25643/bauhaus-universitaet.4098},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200214-40986},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  abstract  = {Rechargeable lithium ion batteries (LIBs) play a very significant role in power supply and storage. In recent decades, LIBs have caught tremendous attention in mobile communication, portable electronics, and electric vehicles. Furthermore, global warming has become a worldwide issue due to the ongoing production of greenhouse gases. It motivates solutions such as renewable sources of energy. Solar and wind energies are the most important ones in renewable energy sources. By technology progress, they will definitely require batteries to store the produced power to make a balance between power generation and consumption. Nowadays,rechargeable batteries such as LIBs are considered as one of the best solutions. They provide high specific energy and high rate performance while their rate of self-discharge is low. Performance of LIBs can be improved through the modification of battery characteristics. The size of solid particles in electrodes can impact the specific energy and the cyclability of batteries. It can improve the amount of lithium content in the electrode which is a vital parameter in capacity and capability of a battery. There exist diferent sources of heat generation in LIBs such as heat produced during electrochemical reactions, internal resistance in battery. The size of electrode's electroactive particles can directly affect the produced heat in battery. It will be shown that the smaller size of solid particle enhance the thermal characteristics of LIBs. Thermal issues such as overheating, temperature maldistribution in the battery, and thermal runaway have confined applications of LIBs. Such thermal challenges reduce the Life cycle of LIBs. As well, they may lead to dangerous conditions such as fire or even explosion in batteries. However, recent advances in fabrication of advanced materials such as graphene and carbon nanotubes with extraordinary thermal conductivity and electrical properties propose new opportunities to enhance their performance. Since experimental works are expensive, our objective is to use computational methods to investigate the thermal issues in LIBS. Dissipation of the heat produced in the battery can improve the cyclability and specific capacity of LIBs. In real applications, packs of LIB consist several battery cells that are used as the power source. Therefore, it is worth to investigate thermal characteristic of battery packs under their cycles of charging/discharging operations at different applied current rates. To remove the produced heat in batteries, they can be surrounded by materials with high thermal conductivity. Parafin wax absorbs high energy since it has a high latent heat. Absorption high amounts of energy occurs at constant temperature without phase change. As well, thermal conductivity of parafin can be magnified with nano-materials such as graphene, CNT, and fullerene to form a nano-composite medium. Improving the thermal conductivity of LIBs increase the heat dissipation from batteries which is a vital issue in systems of battery thermal management. The application of two-dimensional (2D) materials has been on the rise since exfoliation the graphene from bulk graphite. 2D materials are single-layered in an order of nanosizes which show superior thermal, mechanical, and optoelectronic properties. They are potential candidates for energy storage and supply, particularly in lithium ion batteries as electrode material. The high thermal conductivity of graphene and graphene-like materials can play a significant role in thermal management of batteries. However, defects always exist in nano-materials since there is no ideal fabrication process. One of the most important defects in materials are nano-crack which can dramatically weaken the mechanical properties of the materials. Newly synthesized crystalline carbon nitride with the stoichiometry of C3N have attracted many attentions due to its extraordinary mechanical and thermal properties. The other nano-material is phagraphene which shows anisotropic mechanical characteristics which is ideal in production of nanocomposite. It shows ductile fracture behavior when subjected under uniaxial loadings. It is worth to investigate their thermo-mechanical properties in its pristine and defective states. We hope that the findings of our work not only be useful for both experimental and theoretical researches but also help to design advanced electrodes for LIBs.},
  subject      = {Akkumulator},
  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}
}
@phdthesis{Oucif,
  author    = {Oucif, Chahmi},
  title     = {Analytical Modeling of Self-Healing and Super Healing in Cementitious Materials},
  doi       = {10.25643/bauhaus-universitaet.4229},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200831-42296},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {208},
  abstract  = {Self-healing materials have recently become more popular due to their capability to autonomously and autogenously repair the damage in cementitious materials. The concept of self-healing gives the damaged material the ability to recover its stiffness. This gives a difference in comparing with a material that is not subjected to healing. Once this material is damaged, it cannot sustain loading due to the stiffness degradation. Numerical modeling of self-healing materials is still in its infancy. Multiple experimental researches were conducted in literature to describe the behavior of self-healing of cementitious materials. However, few numerical investigations were undertaken. The thesis presents an analytical framework of self-healing and super healing materials based on continuum damage-healing mechanics. Through this framework, we aim to describe the recovery and strengthening of material stiffness and strength. A simple damage healing law is proposed and applied on concrete material. The proposed damage-healing law is based on a new time-dependent healing variable. The damage-healing model is applied on isotropic concrete material at the macroscale under tensile load. Both autonomous and autogenous self-healing mechanisms are simulated under different loading conditions. These two mechanisms are denoted in the present work by coupled and uncoupled self-healing mechanisms, respectively. We assume in the coupled self-healing that the healing occurs at the same time with damage evolution, while we assume in the uncoupled self-healing that the healing occurs when the material is deformed and subjected to a rest period (damage is constant). In order to describe both coupled and uncoupled healing mechanisms, a one-dimensional element is subjected to different types of loading history. In the same context, derivation of nonlinear self-healing theory is given, and comparison of linear and nonlinear damage-healing models is carried out using both coupled and uncoupled self-healing mechanisms. The nonlinear healing theory includes generalized nonlinear and quadratic healing models. The healing efficiency is studied by varying the values of the healing rest period and the parameter describing the material characteristics. In addition, theoretical formulation of different self-healing variables is presented for both isotropic and anisotropic maerials. The healing variables are defined based on the recovery in elastic modulus, shear modulus, Poisson's ratio, and bulk modulus. The evolution of the healing variable calculated based on cross-section as function of the healing variable calculated based on elastic stiffness is presented in both hypotheses of elastic strain equivalence and elastic energy equivalence. The components of the fourth-rank healing tensor are also obtained in the case of isotropic elasticity, plane stress and plane strain. Recent research revealed that self-healing presents a crucial solution also for the strengthening of the materials. This new concept has been termed ``Super Healing``. Once the stiffness of the material is recovered, further healing can result as a strengthening material. In the present thesis, new theory of super healing materials is defined in isotropic and anisotropic cases using sound mathematical and mechanical principles which are applied in linear and nonlinear super healing theories. Additionally, the link of the proposed theory with the theory of undamageable materials is outlined. In order to describe the super healing efficiency in linear and nonlinear theories, the ratio of effective stress to nominal stress is calculated as function of the super healing variable. In addition, the hypotheses of elastic strain and elastic energy equivalence are applied. In the same context, new super healing matrix in plane strain is proposed based on continuum damage-healing mechanics. In the present work, we also focus on numerical modeling of impact behavior of reinforced concrete slabs using the commercial finite element package Abaqus/Explicit. Plain and reinforced concrete slabs of unconfined compressive strength 41 MPa are simulated under impact of ogive-nosed hard projectile. The constitutive material modeling of the concrete and steel reinforcement bars is performed using the Johnson-Holmquist-2 damage and the Johnson-Cook plasticity material models, respectively. Damage diameters and residual velocities obtained by the numerical model are compared with the experimental results and effect of steel reinforcement and projectile diameter is studied.},
  subject      = {Schaden},
  language  = {en}
}
@misc{Asslan,
  type      = {Master Thesis},
  author    = {Asslan, Milad},
  title     = {An Experimental Study on the Initial Shear Stiffness in Granular Material under Controlled Multi-Phase Laboratory Conditions},
  doi       = {10.25643/bauhaus-universitaet.1584},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20120402-15842},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {100},
  abstract  = {The initial shear modulus, Gmax, of soil is an important parameter for a variety of geotechnical design applications. This modulus is typically associated with shear strain levels about 5*10^-3\% and below. The critical role of soil stiffness at small-strains in the design and analysis of geotechnical infrastructure is now widely accepted. Gmax is a key parameter in small-strain dynamic analyses such as those to predict soil behavior or soil-structure interaction during earthquake, explosions, machine or traffic vibration where it is necessary to know how the shear modulus degrades from its small-strain value as the level of shear strain increases. Gmax can be equally important for small-strain cyclic situations such as those caused by wind or wave loading and for small-strain static situations as well. Gmax may also be used as an indirect indication of various soil parameters, as it, in many cases, correlates well to other soil properties such as density and sample disturbance. In recent years, a technique using bender elements was developed to investigate the small-strain shear modulus Gmax. The objective of this thesis is to study the initial shear stiffness for various sands with different void ratios, densities, grain size distribution under dry and saturated conditions, then to compare empirical equations to predict Gmax and results from other testing devices with results of bender elements from this study.},
  subject      = {Soil},
  language  = {en}
}
@misc{Schwedler2009,
  type      = {Master Thesis},
  author    = {Schwedler, Michael},
  title     = {Untersuchungen adaptiver Modellanpassungen f{\"u}r Probleme dynamischer Bauwerks-Bodeninteraktion},
  doi       = {10.25643/bauhaus-universitaet.1405},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20091022-14896},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  year      = {2009},
  abstract  = {Die Eigenschaften des Baugrunds k{\"o}nnen das dynamische Verhalten eines Bauwerks in erheblichem Maße beeinflussen. Um daraus resultierende Ver{\"a}nderungen der Tragwerksbeanspruchung ermitteln zu k{\"o}nnen, muss der Boden in den Berechnungsmodellen zur Bestimmung der Tragwerksbeanspruchung ber{\"u}cksichtigt werden. Die m{\"o}glichen Modellierungsvarianten unterscheiden sich in ihrer Komplexit{\"a}t erheblich. Im Rahmen dieser Arbeit wird das dynamische Verhalten eines konkreten Bauwerks, der Millikan Library, an einem numerischen Modell untersucht. W{\"a}hrend das Partialmodell Bauwerk w{\"a}hrend der Untersuchungen unver{\"a}ndert bleibt, werden f{\"u}r den Boden verschiedene Modellierungsvarianten verwendet. Allen Bodenmodellen gemein ist, dass sie auf einfachen, gekoppelten Feder-D{\"a}mpferelementen beruhen. Die mit den unterschiedlichen Modellierungsvarianten des Bodens erzielten Ergebnisse werden einander gegen{\"u}ber gestellt und mit dem, im Rahmen anderer Arbeiten experimentell bestimmten, dynamischen Verhalten des untersuchten Bauwerks verglichen.},
  subject      = {Boden-Bauwerk-Wechselwirkung},
  language  = {de}
}
@misc{Udrea,
  type      = {Master Thesis},
  author    = {Udrea, Mihai-Andrei},
  title     = {Assessment of Data from Dynamic Bridge Monitoring},
  doi       = {10.25643/bauhaus-universitaet.2174},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20140429-21742},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  abstract  = {The focus of the thesis is to process measurements acquired from a continuous monitoring system at a railway bridge. Temperature, strain and ambient vibration records are analysed and two main directions of investigation are pursued. The first and the most demanding task is to develop processing routines able to extract modal parameters from ambient vibration measurements. For this purpose, reliable experimental models are achieved on the basis of a stochastic system identification(SSI) procedure. A fully automated algorithm based on a three-stage clustering is implemented to perform a modal parameter estimation for every single measurement. After selecting a baseline of modal parameters, the evolution of eigenfrequencies is studied and correlated to environmental and operational factors. The second aspect deals with the structural response to passing trains. Corresponding triggered records of strain and temperature are processed and their assessment is accomplished using the average strains induced by each train as the reference parameter. Three influences due to speed, temperature and loads are distinguished and treated individually. An attempt to estimate the maximum response variation due to each factor is also carried out.},
  subject      = {Messtechnik},
  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}
}
@phdthesis{Valizadeh,
  author    = {Valizadeh, Navid},
  title     = {Developments in Isogeometric Analysis and Application to High-Order Phase-Field Models of Biomembranes},
  doi       = {10.25643/bauhaus-universitaet.4565},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220114-45658},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  abstract  = {Isogeometric analysis (IGA) is a numerical method for solving partial differential equations (PDEs), which was introduced with the aim of integrating finite element analysis with computer-aided design systems. The main idea of the method is to use the same spline basis functions which describe the geometry in CAD systems for the approximation of solution fields in the finite element method (FEM). Originally, NURBS which is a standard technology employed in CAD systems was adopted as basis functions in IGA but there were several variants of IGA using other technologies such as T-splines, PHT splines, and subdivision surfaces as basis functions. In general, IGA offers two key advantages over classical FEM: (i) by describing the CAD geometry exactly using smooth, high-order spline functions, the mesh generation process is simplified and the interoperability between CAD and FEM is improved, (ii) IGA can be viewed as a high-order finite element method which offers basis functions with high inter-element continuity and therefore can provide a primal variational formulation of high-order PDEs in a straightforward fashion. The main goal of this thesis is to further advance isogeometric analysis by exploiting these major advantages, namely precise geometric modeling and the use of smooth high-order splines as basis functions, and develop robust computational methods for problems with complex geometry and/or complex multi-physics. As the first contribution of this thesis, we leverage the precise geometric modeling of isogeometric analysis and propose a new method for its coupling with meshfree discretizations. We exploit the strengths of both methods by using IGA to provide a smooth, geometrically-exact surface discretization of the problem domain boundary, while the Reproducing Kernel Particle Method (RKPM) discretization is used to provide the volumetric discretization of the domain interior. The coupling strategy is based upon the higher-order consistency or reproducing conditions that are directly imposed in the physical domain. The resulting coupled method enjoys several favorable features: (i) it preserves the geometric exactness of IGA, (ii) it circumvents the need for global volumetric parameterization of the problem domain, (iii) it achieves arbitrary-order approximation accuracy while preserving higher-order smoothness of the discretization. Several numerical examples are solved to show the optimal convergence properties of the coupled IGA-RKPM formulation, and to demonstrate its effectiveness in constructing volumetric discretizations for complex-geometry objects. As for the next contribution, we exploit the use of smooth, high-order spline basis functions in IGA to solve high-order surface PDEs governing the morphological evolution of vesicles. These governing equations are often consisted of geometric PDEs, high-order PDEs on stationary or evolving surfaces, or a combination of them. We propose an isogeometric formulation for solving these PDEs. In the context of geometric PDEs, we consider phase-field approximations of mean curvature flow and Willmore flow problems and numerically study the convergence behavior of isogeometric analysis for these problems. As a model problem for high-order PDEs on stationary surfaces, we consider the Cahn-Hilliard equation on a sphere, where the surface is modeled using a phase-field approach. As for the high-order PDEs on evolving surfaces, a phase-field model of a deforming multi-component vesicle, which consists of two fourth-order nonlinear PDEs, is solved using the isogeometric analysis in a primal variational framework. Through several numerical examples in 2D, 3D and axisymmetric 3D settings, we show the robustness of IGA for solving the considered phase-field models. Finally, we present a monolithic, implicit formulation based on isogeometric analysis and generalized-alpha time integration for simulating hydrodynamics of vesicles according to a phase-field model. Compared to earlier works, the number of equations of the phase-field model which need to be solved is reduced by leveraging high continuity of NURBS functions, and the algorithm is extended to 3D settings. We use residual-based variational multi-scale method (RBVMS) for solving Navier-Stokes equations, while the rest of PDEs in the phase-field model are treated using a standard Galerkin-based IGA. We introduce the resistive immersed surface (RIS) method into the formulation which can be employed for an implicit description of complex geometries using a diffuse-interface approach. The implementation highlights the robustness of the RBVMS method for Navier-Stokes equations of incompressible flows with non-trivial localized forcing terms including bending and tension forces of the vesicle. The potential of the phase-field model and isogeometric analysis for accurate simulation of a variety of fluid-vesicle interaction problems in 2D and 3D is demonstrated.},
  subject      = {Phasenfeldmodell},
  language  = {en}
}