@article{BudarapuGracieYangetal., author = {Budarapu, Pattabhi Ramaiah and Gracie, Robert and Yang, Shih-Wei and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Efficient Coarse Graining in Multiscale Modeling of Fracture}, series = {Theoretical and Applied Fracture Mechanics}, journal = {Theoretical and Applied Fracture Mechanics}, pages = {126 -- 143}, abstract = {Efficient Coarse Graining in Multiscale Modeling of Fracture}, subject = {Angewandte Mathematik}, language = {en} } @article{BudarapuNarayanaRammohanetal., author = {Budarapu, Pattabhi Ramaiah and Narayana, T.S.S. and Rammohan, B. and Rabczuk, Timon}, title = {Directionality of sound radiation from rectangular panels}, series = {Applied Acoustics}, journal = {Applied Acoustics}, pages = {128 -- 140}, abstract = {Directionality of sound radiation from rectangular panels}, subject = {Angewandte Mathematik}, language = {en} } @article{ChakrabortyAnitescuZhuangetal., author = {Chakraborty, Ayan and Anitescu, Cosmin and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Domain adaptation based transfer learning approach for solving PDEs on complex geometries}, series = {Engineering with Computers}, volume = {2022}, journal = {Engineering with Computers}, doi = {10.1007/s00366-022-01661-2}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220811-46776}, pages = {1 -- 20}, abstract = {In machine learning, if the training data is independently and identically distributed as the test data then a trained model can make an accurate predictions for new samples of data. Conventional machine learning has a strong dependence on massive amounts of training data which are domain specific to understand their latent patterns. In contrast, Domain adaptation and Transfer learning methods are sub-fields within machine learning that are concerned with solving the inescapable problem of insufficient training data by relaxing the domain dependence hypothesis. In this contribution, this issue has been addressed and by making a novel combination of both the methods we develop a computationally efficient and practical algorithm to solve boundary value problems based on nonlinear partial differential equations. We adopt a meshfree analysis framework to integrate the prevailing geometric modelling techniques based on NURBS and present an enhanced deep collocation approach that also plays an important role in the accuracy of solutions. We start with a brief introduction on how these methods expand upon this framework. We observe an excellent agreement between these methods and have shown that how fine-tuning a pre-trained network to a specialized domain may lead to an outstanding performance compare to the existing ones. As proof of concept, we illustrate the performance of our proposed model on several benchmark problems.}, subject = {Maschinelles Lernen}, 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{ChenNguyenThanhNguyenXuanetal., author = {Chen, Lei and Nguyen-Thanh, Nhon and Nguyen-Xuan, Hung and Rabczuk, Timon and Bordas, St{\´e}phane Pierre Alain and Limbert, Georges}, title = {Explicit finite deformation analysis of isogeometric membranes}, series = {Computer Methods in Applied Mechanics and Engineering}, journal = {Computer Methods in Applied Mechanics and Engineering}, pages = {104 -- 130}, abstract = {Explicit finite deformation analysis of isogeometric membranes}, subject = {Angewandte Mathematik}, language = {en} } @article{ChenRabczukLiuetal., author = {Chen, Lei and Rabczuk, Timon and Liu, G.R. and Zeng, K.Y. and Kerfriden, Pierre and Bordas, St{\´e}phane Pierre Alain}, title = {Extended finite element method with edge-based strain smoothing (ESm-XFEM) for linear elastic crack growth}, series = {Computer Methods in Applied Mechanics and Engineering}, journal = {Computer Methods in Applied Mechanics and Engineering}, doi = {10.1016/j.cma.2011.08.013}, abstract = {This paper presents a strain smoothing procedure for the extended finite element method (XFEM). The resulting "edge-based" smoothed extended finite element method (ESm-XFEM) is tailored to linear elastic fracture mechanics and, in this context, to outperform the standard XFEM. In the XFEM, the displacement-based approximation is enriched by the Heaviside and asymptotic crack tip functions using the framework of partition of unity. This eliminates the need for the mesh alignment with the crack and re-meshing, as the crack evolves. Edge-based smoothing (ES) relies on a generalized smoothing operation over smoothing domains associated with edges of simplex meshes, and produces a softening effect leading to a close-to-exact stiffness, "super-convergence" and "ultra-accurate" solutions. The present method takes advantage of both the ES-FEM and the XFEM. Thanks to the use of strain smoothing, the subdivision of elements intersected by discontinuities and of integrating the (singular) derivatives of the approximation functions is suppressed via transforming interior integration into boundary integration. Numerical examples show that the proposed method improves significantly the accuracy of stress intensity factors and achieves a near optimal convergence rate in the energy norm even without geometrical enrichment or blending correction.}, 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} } @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{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{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{GhasemiKerfridenBordasetal., author = {Ghasemi, Hamid and Kerfriden, Pierre and Bordas, St{\´e}phane Pierre Alain and Muthu, Jacob and Zi, Goangseup and Rabczuk, Timon}, title = {Interfacial shear stress optimization in sandwich beams with polymeric core using nonuniform distribution of reinforcing ingredients}, series = {Composite Structures}, journal = {Composite Structures}, pages = {221 -- 230}, abstract = {Interfacial shear stress optimization in sandwich beams with polymeric core using nonuniform distribution of reinforcing ingredients}, 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} } @article{GhorashiLahmerBagherzadehetal., author = {Ghorashi, Seyed Shahram and Lahmer, Tom and Bagherzadeh, Amir Saboor and Zi, Goangseup and Rabczuk, Timon}, title = {A stochastic computational method based on goal-oriented error estimation for heterogeneous geological materials}, series = {Engineering Geology}, journal = {Engineering Geology}, abstract = {A stochastic computational method based on goal-oriented error estimation for heterogeneous geological materials}, subject = {Angewandte Mathematik}, language = {en} } @inproceedings{GhorashiRabczukRodenasGarciaetal., author = {Ghorashi, Seyed Shahram and Rabczuk, Timon and R{\´o}denas Garc{\´i}a, Juan Jos{\´e} and Lahmer, Tom}, title = {T-SPLINE BASED XIGA FOR ADAPTIVE MODELING OF CRACKED BODIES}, 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}, editor = {G{\"u}rlebeck, Klaus and Lahmer, Tom and Werner, Frank}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2763}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-27637}, pages = {13}, abstract = {Safety operation of important civil structures such as bridges can be estimated by using fracture analysis. Since the analytical methods are not capable of solving many complicated engineering problems, numerical methods have been increasingly adopted. In this paper, a part of isotropic material which contains a crack is considered as a partial model and the proposed model quality is evaluated. EXtended IsoGeometric Analysis (XIGA) is a new developed numerical approach [1, 2] which benefits from advantages of its origins: eXtended Finite Element Method (XFEM) and IsoGeometric Analysis (IGA). It is capable of simulating crack propagation problems with no remeshing necessity and capturing singular field at the crack tip by using the crack tip enrichment functions. Also, exact representation of geometry is possible using only few elements. XIGA has also been successfully applied for fracture analysis of cracked orthotropic bodies [3] and for simulation of curved cracks [4]. XIGA applies NURBS functions for both geometry description and solution field approximation. The drawback of NURBS functions is that local refinement cannot be defined regarding that it is based on tensorproduct constructs unless multiple patches are used which has also some limitations. In this contribution, the XIGA is further developed to make the local refinement feasible by using Tspline basis functions. Adopting a recovery based error estimator in the proposed approach for evaluation of the model quality and performing the adaptive processes is in progress. Finally, some numerical examples with available analytical solutions are investigated by the developed scheme.}, subject = {Angewandte Informatik}, 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{GuoAlajlanZhuangetal., author = {Guo, Hongwei and Alajlan, Naif and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Physics-informed deep learning for three-dimensional transient heat transfer analysis of functionally graded materials}, series = {Computational Mechanics}, volume = {2023}, journal = {Computational Mechanics}, publisher = {Springer}, address = {Berlin}, doi = {10.1007/s00466-023-02287-x}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20230517-63666}, pages = {1 -- 12}, abstract = {We present a physics-informed deep learning model for the transient heat transfer analysis of three-dimensional functionally graded materials (FGMs) employing a Runge-Kutta discrete time scheme. Firstly, the governing equation, associated boundary conditions and the initial condition for transient heat transfer analysis of FGMs with exponential material variations are presented. Then, the deep collocation method with the Runge-Kutta integration scheme for transient analysis is introduced. The prior physics that helps to generalize the physics-informed deep learning model is introduced by constraining the temperature variable with discrete time schemes and initial/boundary conditions. Further the fitted activation functions suitable for dynamic analysis are presented. Finally, we validate our approach through several numerical examples on FGMs with irregular shapes and a variety of boundary conditions. From numerical experiments, the predicted results with PIDL demonstrate well agreement with analytical solutions and other numerical methods in predicting of both temperature and flux distributions and can be adaptive to transient analysis of FGMs with different shapes, which can be the promising surrogate model in transient dynamic analysis.}, subject = {W{\"a}rme{\"u}bergang}, language = {en} } @article{GuoZhuangChenetal., author = {Guo, Hongwei and Zhuang, Xiaoying and Chen, Pengwan and Alajlan, Naif and Rabczuk, Timon}, title = {Analysis of three-dimensional potential problems in non-homogeneous media with physics-informed deep collocation method using material transfer learning and sensitivity analysis}, series = {Engineering with Computers}, volume = {2022}, journal = {Engineering with Computers}, doi = {10.1007/s00366-022-01633-6}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220811-46764}, pages = {1 -- 22}, abstract = {In this work, we present a deep collocation method (DCM) for three-dimensional potential problems in non-homogeneous media. This approach utilizes a physics-informed neural network with material transfer learning reducing the solution of the non-homogeneous partial differential equations to an optimization problem. We tested different configurations of the physics-informed neural network including smooth activation functions, sampling methods for collocation points generation and combined optimizers. A material transfer learning technique is utilized for non-homogeneous media with different material gradations and parameters, which enhance the generality and robustness of the proposed method. In order to identify the most influential parameters of the network configuration, we carried out a global sensitivity analysis. Finally, we provide a convergence proof of our DCM. The approach is validated through several benchmark problems, also testing different material variations.}, subject = {Deep learning}, 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} } @article{IlyaniAkmarKramerRabczuk, author = {Ilyani Akmar, A.B. and Kramer, O. and Rabczuk, Timon}, title = {Multi-objective evolutionary optimization of sandwich structures: An evaluation by elitist non-dominated sorting evolution strategy}, series = {American Journal of Engineering and Applied Sciences}, journal = {American Journal of Engineering and Applied Sciences}, doi = {10.3844/ajeassp.2015.185.201}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170418-31402}, pages = {185 -- 201}, abstract = {In this study, an application of evolutionary multi-objective optimization algorithms on the optimization of sandwich structures is presented. The solution strategy is known as Elitist Non-Dominated Sorting Evolution Strategy (ENSES) wherein Evolution Strategies (ES) as Evolutionary Algorithm (EA) in the elitist Non-dominated Sorting Genetic algorithm (NSGA-II) procedure. Evolutionary algorithm seems a compatible approach to resolve multi-objective optimization problems because it is inspired by natural evolution, which closely linked to Artificial Intelligence (AI) techniques and elitism has shown an important factor for improving evolutionary multi-objective search. In order to evaluate the notion of performance by ENSES, the well-known study case of sandwich structures are reconsidered. For Case 1, the goals of the multi-objective optimization are minimization of the deflection and the weight of the sandwich structures. The length, the core and skin thicknesses are the design variables of Case 1. For Case 2, the objective functions are the fabrication cost, the beam weight and the end deflection of the sandwich structures. There are four design variables i.e., the weld height, the weld length, the beam depth and the beam width in Case 2. Numerical results are presented in terms of Paretooptimal solutions for both evaluated cases.}, subject = {Optimierung}, language = {en} } @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} }