Papers 3677

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Computational stochastic homogenization of heterogeneous media from an elasticity random field having an uncertain spectral measure

This paper presents the computational stochastic homogenization of a heterogeneous 3D-linear anisotropic elastic microstructure that cannot be described in terms of constituents at microscale, as live tissues. The random apparent elasticity field at mesoscale is then modeled in a class of non-Gaussian positive-definite tensor-valued homogeneous random fields. We present an extension of previous works consisting of a novel probabilistic model to take into account uncertainties in the spectral mea...

A least squares recursive gradient meshfree collocation method for superconvergent structural vibration analysis

#1Like Deng (Ha Tai: Xiamen University)H-Index: 2

#2Dongdong Wang (Ha Tai: Xiamen University)H-Index: 21

Last. Dongliang Qi (Ha Tai: Xiamen University)H-Index: 2

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A least squares recursive gradient meshfree collocation method is proposed for the superconvergent computation of structural vibration frequencies. The proposed approach employs the recursive gradients of meshfree shape functions together with smoothed shape functions in the context of least squares formulation, where both meshfree nodes and auxiliary points are taken as the collocation points. It turns out that this least squares formulation can effectively suppress the spurious modes arising f...

Multiscale parareal algorithm for long-time mesoscopic simulations of microvascular blood flow in zebrafish

#1Ansel L. Blumers (Brown University)H-Index: 4

#2Minglang Yin (Brown University)H-Index: 4

Last. George Em Karniadakis (Brown University)H-Index: 7

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Various biological processes such as transport of oxygen and nutrients, thrombus formation, vascular angiogenesis and remodeling are related to cellular/subcellular level biological processes, where mesoscopic simulations resolving detailed cell dynamics provide a key to understanding and identifying the cellular basis of disease. However, the intrinsic stochastic effects can play an important role in mesoscopic processes, while the time step allowed in a mesoscopic simulation is restricted by r...

#1Karl A. Kalina (TUD: Dresden University of Technology)H-Index: 7

#2Lennart Linden (TUD: Dresden University of Technology)

Last. Markus Kästner (TUD: Dresden University of Technology)H-Index: 19

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Herein, an artificial neural network (ANN)-based approach for the efficient automated modeling and simulation of isotropic hyperelastic solids is presented. Starting from a large data set comprising deformations and corresponding stresses, a simple, physically based reduction of the problem’s dimensionality is performed in a data processing step. More specifically, three deformation type invariants serve as the input instead of the deformation tensor itself. In the same way, three corresponding ...

#1Antonio Maria D'Altri (UNIBO: University of Bologna)H-Index: 12

#2L. Patruno (UNIBO: University of Bologna)H-Index: 14

Last. Elio Sacco (University of Naples Federico II)H-Index: 41

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In this paper, a first-order virtual element method for Reissner–Mindlin plates is presented. A standard displacement-based variational formulation is employed, assuming transverse displacement and rotations as independent variables. In the framework of the first-order virtual element, a piecewise linear approximation is assumed for both displacement and rotations on the boundary of the element. The consistent term of the stiffness matrix is determined assuming uncoupled polynomial approximation...

MFNets: data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources

#1Alex A. Gorodetsky (UM: University of Michigan)H-Index: 11

#2John D. Jakeman (SNL: Sandia National Laboratories)H-Index: 16

Last. Gianluca Geraci (SNL: Sandia National Laboratories)H-Index: 10

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We present an approach for constructing a surrogate from ensembles of information sources of varying cost and accuracy. The multifidelity surrogate encodes connections between information sources as a directed acyclic graph, and is trained via gradient-based minimization of a nonlinear least squares objective. While the vast majority of state-of-the-art assumes hierarchical connections between information sources, our approach works with flexibly structured information sources that may not admit...

#1Nima Noii (Leibniz University of Hanover)H-Index: 6

#2Amirreza Khodadadian (Leibniz University of Hanover)H-Index: 10

Last. Peter Wriggers (Leibniz University of Hanover)H-Index: 77

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The prediction of crack initiation and propagation in ductile failure processes are challenging tasks for the design and fabrication of metallic materials and structures on a large scale. Numerical aspects of ductile failure dictate a sub-optimal calibration of plasticity- and fracture-related parameters for a large number of material properties. These parameters enter the system of partial differential equations as a forward model. Thus, an accurate estimation of the material parameters enables...

Variable-order approach to nonlocal elasticity: theoretical formulation, order identification via deep learning, and applications

#1Sansit Patnaik (Purdue University)H-Index: 9

#2Mehdi Jokar (Purdue University)H-Index: 3

Last. Fabio Semperlotti (Purdue University)H-Index: 24

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This study presents the formulation of the variable-order continuum mechanics theory and its application to the analysis of nonlocal heterogeneous solids. The variable-order continuum theory enables a unique approach to model the response of solids exhibiting position-dependent nonlocal behavior. The formulation also guarantees frame-invariance provided that proper constraints on the functional definition of the variable-order are imposed. The study also presents a deep learning approach to iden...

Two-field formulations for isogeometric Reissner–Mindlin plates and shells with global and local condensation

#1G. Kikis (RWTH Aachen University)

#2Sven Klinkel (RWTH Aachen University)H-Index: 22

In this paper, mixed formulations are presented in the framework of isogeometric Reissner–Mindlin plates and shells with the aim of alleviating membrane and shear locking. The formulations are based on the Hellinger-Reissner functional and use the stress resultants as additional unknowns, which have to be interpolated in appropriate approximation spaces. The additional unknowns can be eliminated by static condensation. In the framework of isogeometric analysis static condensation is performed gl...

#1Harris Farooq (ENSMP: Mines ParisTech)H-Index: 1

#2David Ryckelynck (ENSMP: Mines ParisTech)H-Index: 15

Last. Aldo Marano (ENSMP: Mines ParisTech)H-Index: 3

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We are exploring the idea of data pruning via hyperreduction modeling. The main novelty of this paper is a lossy data compression/decompression approach for ploycrystalline data, which is based on a hyperreduction scheme that preserves data driven modeling capabilities after compression. We assume to know a mechanical model whose equations are satisfied by the data. It is shown that the proposed reconstruction of the data performs an oblique projection of selected original data. This is achieved...

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