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Xiaoying Zhuang
Researcher at Leibniz University of Hanover
Publications - 332
Citations - 15758
Xiaoying Zhuang is an academic researcher from Leibniz University of Hanover. The author has contributed to research in topics: Finite element method & Graphene. The author has an hindex of 54, co-authored 271 publications receiving 10082 citations. Previous affiliations of Xiaoying Zhuang include Tongji University & Norwegian University of Science and Technology.
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An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications
Esteban Samaniego,Cosmin Anitescu,Somdatta Goswami,Vien Minh Nguyen-Thanh,Hongwei Guo,Khader M. Hamdia,Xiaoying Zhuang,Timon Rabczuk +7 more
TL;DR: This contribution focuses in mechanical problems and analyze the energetic format of the PDE, where the energy of a mechanical system seems to be the natural loss function for a machine learning method to approach a mechanical problem.
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Dual‐horizon peridynamics
Huilong Ren,Xiaoying Zhuang,Xiaoying Zhuang,Yongchang Cai,Yongchang Cai,Timon Rabczuk,Timon Rabczuk +6 more
TL;DR: In this article, a dual-horizon peridynamics (DH-PD) formulation is proposed to solve the ghost force issue by considering the unbalanced interactions between the particles with different horizon sizes.
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Dual-horizon peridynamics: A stable solution to varying horizons
TL;DR: In this article, a dual-horizon peridynamics (DH-PD) formulation is presented, which allows for simulations with dual-Horizon with minimal spurious wave reflection and is shown to be less sensitive to the spatial than the original PD formulation.
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A software framework for probabilistic sensitivity analysis for computationally expensive models
TL;DR: A sensitivity analysis toolbox consisting of a set of Matlab functions that offer utilities for quantifying the influence of uncertain input parameters on uncertain model outputs is provided.
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Stochastic analysis of the fracture toughness of polymeric nanoparticle composites using polynomial chaos expansions
Khader M. Hamdia,Khader M. Hamdia,Mohammad Silani,Xiaoying Zhuang,Pengfei He,Timon Rabczuk,Timon Rabczuk +6 more
TL;DR: In this article, the authors presented a methodology for stochastic modeling of the fracture in polymer/particle nanocomposites, which is based on six uncertain parameters: the volume fraction and the diameter of the nanoparticles, Young's modulus and the maximum allowable principal stress of the epoxy matrix, the interphase zone thickness and its Youngs modulus.