@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{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{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{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{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{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{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{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{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}
}