@article{ZhangWangLahmeretal., author = {Zhang, Chao and Wang, Cuixia and Lahmer, Tom and He, Pengfei and Rabczuk, Timon}, title = {A dynamic XFEM formulation for crack identification}, series = {International Journal of Mechanics and Materials in Design}, journal = {International Journal of Mechanics and Materials in Design}, pages = {427 -- 448}, abstract = {A dynamic XFEM formulation for crack identification}, subject = {Angewandte Mathematik}, language = {en} } @article{ZhangNanthakumarLahmeretal., author = {Zhang, Chao and Nanthakumar, S.S. and Lahmer, Tom and Rabczuk, Timon}, title = {Multiple cracks identification for piezoelectric structures}, series = {International Journal of Fracture}, journal = {International Journal of Fracture}, pages = {1 -- 19}, abstract = {Multiple cracks identification for piezoelectric structures}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacSilaniLahmeretal., author = {Vu-Bac, N. and Silani, Mohammad and Lahmer, Tom and Zhuang, Xiaoying and Rabczuk, Timon}, title = {A unified framework for stochastic predictions of Young's modulus of clay/epoxy nanocomposites (PCNs)}, series = {Computational Materials Science}, journal = {Computational Materials Science}, pages = {520 -- 535}, abstract = {A unified framework for stochastic predictions of Young's modulus of clay/epoxy nanocomposites (PCNs)}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacRafieeZhuangetal., author = {Vu-Bac, N. and Rafiee, Roham and Zhuang, Xiaoying and Lahmer, Tom and Rabczuk, Timon}, title = {Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters}, series = {Composites Part B: Engineering}, journal = {Composites Part B: Engineering}, pages = {446 -- 464}, abstract = {Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacLahmerZhuangetal., author = {Vu-Bac, N. and Lahmer, Tom and Zhuang, Xiaoying and Nguyen-Thoi, T. and Rabczuk, Timon}, title = {A software framework for probabilistic sensitivity analysis for computationally expensive models}, series = {Advances in Engineering Software}, journal = {Advances in Engineering Software}, pages = {19 -- 31}, abstract = {A software framework for probabilistic sensitivity analysis for computationally expensive models}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacLahmerZhangetal., author = {Vu-Bac, N. and Lahmer, Tom and Zhang, Yancheng and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Stochastic predictions of interfacial characteristic of polymeric nanocomposites (PNCs)}, series = {Composites Part B Engineering}, journal = {Composites Part B Engineering}, pages = {80 -- 95}, abstract = {Stochastic predictions of interfacial characteristic of polymeric nanocomposites (PNCs)}, subject = {Angewandte Mathematik}, language = {en} } @article{VuBacLahmerKeiteletal., author = {Vu-Bac, N. and Lahmer, Tom and Keitel, Holger and Zhao, Jun-Hua and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Stochastic predictions of bulk properties of amorphous polyethylene based on molecular dynamics simulations}, series = {Mechanics of Materials}, journal = {Mechanics of Materials}, pages = {70 -- 84}, abstract = {Stochastic predictions of bulk properties of amorphous polyethylene based on molecular dynamics simulations}, subject = {Angewandte Mathematik}, language = {en} } @inproceedings{TanLahmerSiddappa, author = {Tan, Fengjie and Lahmer, Tom and Siddappa, Manju Gyaraganahalll}, title = {SECTION OPTIMIZATION AND RELIABILITY ANALYSIS OF ARCH-TYPE DAMS INCLUDING COUPLED MECHANICAL-THERMAL AND HYDRAULIC FIELDS}, series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, editor = {G{\"u}rlebeck, Klaus and Lahmer, Tom}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2821}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28212}, pages = {8}, abstract = {From the design experiences of arch dams in the past, it has significant practical value to carry out the shape optimization of arch dams, which can fully make use of material characteristics and reduce the cost of constructions. Suitable variables need to be chosen to formulate the objective function, e.g. to minimize the total volume of the arch dam. Additionally a series of constraints are derived and a reasonable and convenient penalty function has been formed, which can easily enforce the characteristics of constraints and optimal design. For the optimization method, a Genetic Algorithm is adopted to perform a global search. Simultaneously, ANSYS is used to do the mechanical analysis under the coupling of thermal and hydraulic loads. One of the constraints of the newly designed dam is to fulfill requirements on the structural safety. Therefore, a reliability analysis is applied to offer a good decision supporting for matters concerning predictions of both safety and service life of the arch dam. By this, the key factors which would influence the stability and safety of arch dam significantly can be acquired, and supply a good way to take preventive measures to prolong ate the service life of an arch dam and enhances the safety of structure.}, subject = {Angewandte Informatik}, language = {en} } @unpublished{SteinerBourinetLahmer, author = {Steiner, Maria and Bourinet, Jean-Marc and Lahmer, Tom}, title = {An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression}, doi = {10.25643/BAUHAUS-UNIVERSITAET.3832}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181218-38320}, pages = {1 -- 33}, abstract = {In the field of engineering, surrogate models are commonly used for approximating the behavior of a physical phenomenon in order to reduce the computational costs. Generally, a surrogate model is created based on a set of training data, where a typical method for the statistical design is the Latin hypercube sampling (LHS). Even though a space filling distribution of the training data is reached, the sampling process takes no information on the underlying behavior of the physical phenomenon into account and new data cannot be sampled in the same distribution if the approximation quality is not sufficient. Therefore, in this study we present a novel adaptive sampling method based on a specific surrogate model, the least-squares support vector regresson. The adaptive sampling method generates training data based on the uncertainty in local prognosis capabilities of the surrogate model - areas of higher uncertainty require more sample data. The approach offers a cost efficient calculation due to the properties of the least-squares support vector regression. The opportunities of the adaptive sampling method are proven in comparison with the LHS on different analytical examples. Furthermore, the adaptive sampling method is applied to the calculation of global sensitivity values according to Sobol, where it shows faster convergence than the LHS method. With the applications in this paper it is shown that the presented adaptive sampling method improves the estimation of global sensitivity values, hence reducing the overall computational costs visibly.}, subject = {Approximation}, language = {en} } @article{SteinLahmerBock, author = {Stein, Peter and Lahmer, Tom and Bock, Sebastian}, title = {Synthese und Analyse von gekoppelten Modellen im konstruktiven Ingenieurbau}, series = {Bautechnik}, journal = {Bautechnik}, pages = {8 -- 11}, abstract = {Synthese und Analyse von gekoppelten Modellen im konstruktiven Ingenieurbau}, subject = {Angewandte Mathematik}, language = {de} }