@article{ZhuangHuangRabczuketal., author = {Zhuang, Xiaoying and Huang, Runqiu and Rabczuk, Timon and Liang, C.}, title = {A coupled thermo-hydro-mechanical model of jointed hard rock for compressed air energy storage}, series = {Mathematical Problems in Engineering}, journal = {Mathematical Problems in Engineering}, abstract = {A coupled thermo-hydro-mechanical model of jointed hard rock for compressed air energy storage}, subject = {Angewandte Mathematik}, language = {en} } @article{ZhuangHuangLiangetal., author = {Zhuang, Xiaoying and Huang, Runqiu and Liang, Chao and Rabczuk, Timon}, title = {A coupled thermo-hydro-mechanical model of jointed hard rock for compressed air energy storage}, series = {Mathematical Problems in Engineering}, journal = {Mathematical Problems in Engineering}, doi = {10.1155/2014/179169}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170428-31726}, abstract = {Renewable energy resources such as wind and solar are intermittent, which causes instability when being connected to utility grid of electricity. Compressed air energy storage (CAES) provides an economic and technical viable solution to this problem by utilizing subsurface rock cavern to store the electricity generated by renewable energy in the form of compressed air. Though CAES has been used for over three decades, it is only restricted to salt rock or aquifers for air tightness reason. In this paper, the technical feasibility of utilizing hard rock for CAES is investigated by using a coupled thermo-hydro-mechanical (THM) modelling of nonisothermal gas flow. Governing equations are derived from the rules of energy balance, mass balance, and static equilibrium. Cyclic volumetric mass source and heat source models are applied to simulate the gas injection and production. Evaluation is carried out for intact rock and rock with discrete crack, respectively. In both cases, the heat and pressure losses using air mass control and supplementary air injection are compared.}, subject = {Energiespeicherung}, language = {en} } @article{ZhangZhuangMuthuetal., author = {Zhang, Yancheng and Zhuang, Xiaoying and Muthu, Jacob and Mabrouki, Tarek and Fontaine, Micha{\"e}l and Gong, Yadong and Rabczuk, Timon}, title = {Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulation}, series = {Composites Part B Engineering}, journal = {Composites Part B Engineering}, pages = {27 -- 33}, abstract = {Load transfer of graphene/carbon nanotube/polyethylene hybrid nanocomposite by molecular dynamics simulation}, 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{VuBacNguyenXuanChenetal., author = {Vu-Bac, N. and Nguyen-Xuan, Hung and Chen, Lei and Lee, C.K. and Zi, Goangseup and Zhuang, Xiaoying and Liu, G.R. and Rabczuk, Timon}, title = {A phantom-node method with edge-based strain smoothing for linear elastic fracture mechanics}, series = {Journal of Applied Mathematics}, journal = {Journal of Applied Mathematics}, doi = {10.1155/2013/978026}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170426-31676}, abstract = {This paper presents a novel numerical procedure based on the combination of an edge-based smoothed finite element (ES-FEM) with a phantom-node method for 2D linear elastic fracture mechanics. In the standard phantom-node method, the cracks are formulated by adding phantom nodes, and the cracked element is replaced by two new superimposed elements. This approach is quite simple to implement into existing explicit finite element programs. The shape functions associated with discontinuous elements are similar to those of the standard finite elements, which leads to certain simplification with implementing in the existing codes. The phantom-node method allows modeling discontinuities at an arbitrary location in the mesh. The ES-FEM model owns a close-to-exact stiffness that is much softer than lower-order finite element methods (FEM). Taking advantage of both the ES-FEM and the phantom-node method, we introduce an edge-based strain smoothing technique for the phantom-node method. Numerical results show that the proposed method achieves high accuracy compared with the extended finite element method (XFEM) and other reference solutions.}, subject = {Finite-Elemente-Methode}, 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} } @article{RenZhuangOterkusetal., author = {Ren, Huilong and Zhuang, Xiaoying and Oterkus, Erkan and Zhu, Hehua and Rabczuk, Timon}, title = {Nonlocal strong forms of thin plate, gradient elasticity, magneto-electro-elasticity and phase-field fracture by nonlocal operator method}, series = {Engineering with Computers}, volume = {2021}, journal = {Engineering with Computers}, doi = {10.1007/s00366-021-01502-8}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20211207-45388}, pages = {1 -- 22}, abstract = {The derivation of nonlocal strong forms for many physical problems remains cumbersome in traditional methods. In this paper, we apply the variational principle/weighted residual method based on nonlocal operator method for the derivation of nonlocal forms for elasticity, thin plate, gradient elasticity, electro-magneto-elasticity and phase-field fracture method. The nonlocal governing equations are expressed as an integral form on support and dual-support. The first example shows that the nonlocal elasticity has the same form as dual-horizon non-ordinary state-based peridynamics. The derivation is simple and general and it can convert efficiently many local physical models into their corresponding nonlocal forms. In addition, a criterion based on the instability of the nonlocal gradient is proposed for the fracture modelling in linear elasticity. Several numerical examples are presented to validate nonlocal elasticity and the nonlocal thin plate.}, subject = {Bruchmechanik}, language = {en} } @article{RabczukZhuangOterkus, author = {Rabczuk, Timon and Zhuang, Xiaoying and Oterkus, Erkan}, title = {Editorial: Computational modeling based on nonlocal theory}, series = {Engineering with Computers}, volume = {2023}, journal = {Engineering with Computers}, number = {Volume 39, issue 3}, publisher = {Springer}, address = {London}, doi = {https://doi.org/10.1007/s00366-022-01775-7}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20230517-63658}, pages = {1}, abstract = {Nonlocal theories concern the interaction of objects, which are separated in space. Classical examples are Coulomb's law or Newton's law of universal gravitation. They had signficiant impact in physics and engineering. One classical application in mechanics is the failure of quasi-brittle materials. While local models lead to an ill-posed boundary value problem and associated mesh dependent results, nonlocal models guarantee the well-posedness and are furthermore relatively easy to implement into commercial computational software.}, subject = {Computersimulation}, language = {en} } @article{RabczukGuoZhuangetal., author = {Rabczuk, Timon and Guo, Hongwei and Zhuang, Xiaoying and Chen, Pengwan and Alajlan, Naif}, title = {Stochastic deep collocation method based on neural architecture search and transfer learning for heterogeneous porous media}, series = {Engineering with Computers}, volume = {2022}, journal = {Engineering with Computers}, publisher = {Springer}, address = {London}, doi = {10.1007/s00366-021-01586-2}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220209-45835}, pages = {1 -- 26}, abstract = {We present a stochastic deep collocation method (DCM) based on neural architecture search (NAS) and transfer learning for heterogeneous porous media. We first carry out a sensitivity analysis to determine the key hyper-parameters of the network to reduce the search space and subsequently employ hyper-parameter optimization to finally obtain the parameter values. The presented NAS based DCM also saves the weights and biases of the most favorable architectures, which is then used in the fine-tuning process. We also employ transfer learning techniques to drastically reduce the computational cost. The presented DCM is then applied to the stochastic analysis of heterogeneous porous material. Therefore, a three dimensional stochastic flow model is built providing a benchmark to the simulation of groundwater flow in highly heterogeneous aquifers. The performance of the presented NAS based DCM is verified in different dimensions using the method of manufactured solutions. We show that it significantly outperforms finite difference methods in both accuracy and computational cost.}, subject = {Maschinelles Lernen}, language = {en} } @article{NooriMortazaviKeshtkarietal., author = {Noori, Hamidreza and Mortazavi, Bohayra and Keshtkari, Leila and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Nanopore creation in MoS2 and graphene monolayers by nanoparticles impact: a reactive molecular dynamics study}, series = {Applied Physics A}, volume = {2021}, journal = {Applied Physics A}, number = {volume 127, article 541}, publisher = {Springer}, address = {Heidelberg}, doi = {10.1007/s00339-021-04693-5}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210804-44756}, pages = {1 -- 13}, abstract = {In this work, extensive reactive molecular dynamics simulations are conducted to analyze the nanopore creation by nano-particles impact over single-layer molybdenum disulfide (MoS2) with 1T and 2H phases. We also compare the results with graphene monolayer. In our simulations, nanosheets are exposed to a spherical rigid carbon projectile with high initial velocities ranging from 2 to 23 km/s. Results for three different structures are compared to examine the most critical factors in the perforation and resistance force during the impact. To analyze the perforation and impact resistance, kinetic energy and displacement time history of the projectile as well as perforation resistance force of the projectile are investigated. Interestingly, although the elasticity module and tensile strength of the graphene are by almost five times higher than those of MoS2, the results demonstrate that 1T and 2H-MoS2 phases are more resistive to the impact loading and perforation than graphene. For the MoS2nanosheets, we realize that the 2H phase is more resistant to impact loading than the 1T counterpart. Our reactive molecular dynamics results highlight that in addition to the strength and toughness, atomic structure is another crucial factor that can contribute substantially to impact resistance of 2D materials. The obtained results can be useful to guide the experimental setups for the nanopore creation in MoS2or other 2D lattices.}, subject = {Nanomechanik}, language = {en} } @article{NguyenThanhValizadehNguyenetal., author = {Nguyen-Thanh, Nhon and Valizadeh, Navid and Nguyen, Manh Hung and Nguyen-Xuan, Hung and Zhuang, Xiaoying and Areias, Pedro and Zi, Goangseup and Bazilevs, Yuri and De Lorenzis, Laura and Rabczuk, Timon}, title = {An extended isogeometric thin shell analysis based on Kirchhoff-Love theory}, series = {Computer Methods in Applied Mechanics and Engineering}, journal = {Computer Methods in Applied Mechanics and Engineering}, pages = {265 -- 291}, abstract = {An extended isogeometric thin shell analysis based on Kirchho_-Love theory}, subject = {Angewandte Mathematik}, language = {en} } @article{NguyenThanhMuthuZhuangetal., author = {Nguyen-Thanh, Nhon and Muthu, Jacob and Zhuang, Xiaoying and Rabczuk, Timon}, title = {An adaptive three-dimensional RHT-splines formulation in linear elasto-statics and elasto-dynamics}, series = {Computational Mechanics}, journal = {Computational Mechanics}, pages = {369 -- 385}, abstract = {An adaptive three-dimensional RHT-splines formulation in linear elasto-statics and elasto-dynamics}, subject = {Angewandte Mathematik}, language = {en} } @article{NanthakumarLahmerZhuangetal., author = {Nanthakumar, S.S. and Lahmer, Tom and Zhuang, Xiaoying and Zi, Goangseup and Rabczuk, Timon}, title = {Detection of material interfaces using a regularized level set method in piezoelectric structures}, series = {Inverse Problems in Science and Engineering}, journal = {Inverse Problems in Science and Engineering}, pages = {153 -- 176}, abstract = {Detection of material interfaces using a regularized level set method in piezoelectric structures}, subject = {Angewandte Mathematik}, language = {en} } @article{NanthakumarLahmerZhuangetal., author = {Nanthakumar, S.S. and Lahmer, Tom and Zhuang, Xiaoying and Zi, Goangseup and Rabczuk, Timon}, title = {Detection of material interfaces using a regularized level set method in piezoelectric structures}, series = {Inverse Problems in Science and Engineering}, journal = {Inverse Problems in Science and Engineering}, abstract = {Detection of material interfaces using a regularized level set method in piezoelectric structures}, subject = {Angewandte Mathematik}, language = {en} } @article{NanthakumarLahmerZhuangetal., author = {Nanthakumar, S.S. and Lahmer, Tom and Zhuang, Xiaoying and Park, Harold S. and Rabczuk, Timon}, title = {Topology optimization of piezoelectric nanostructures}, series = {Journal of the Mechanics and Physics of Solids}, journal = {Journal of the Mechanics and Physics of Solids}, pages = {316 -- 335}, abstract = {Topology optimization of piezoelectric nanostructures}, subject = {Angewandte Mathematik}, language = {en} } @article{JiangZhuangRabczuk, author = {Jiang, Jin-Wu and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Orientation dependent thermal conductance in single-layer MoS 2}, series = {Scientific Reports}, journal = {Scientific Reports}, doi = {10.1038/srep02209}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170418-31417}, abstract = {We investigate the thermal conductivity in the armchair and zigzag MoS2 nanoribbons, by combining the non-equilibrium Green's function approach and the first-principles method. A strong orientation dependence is observed in the thermal conductivity. Particularly, the thermal conductivity for the armchair MoS2 nanoribbon is about 673.6 Wm-1 K-1 in the armchair nanoribbon, and 841.1 Wm-1 K-1 in the zigzag nanoribbon at room temperature. By calculating the Caroli transmission, we disclose the underlying mechanism for this strong orientation dependence to be the fewer phonon transport channels in the armchair MoS2 nanoribbon in the frequency range of [150, 200] cm-1. Through the scaling of the phonon dispersion, we further illustrate that the thermal conductivity calculated for the MoS2 nanoribbon is esentially in consistent with the superior thermal conductivity found for graphene.}, subject = {Mechanische Eigenschaft}, language = {en} } @article{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{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{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{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{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{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} }