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Reduced finite element square techniques (RFE2): towards industrial multiscale fe software [PDF]
, 2019 Reduced order modeling techniques proposed by the authors are assessed for an industrial case study of a 3D reinforced composite laminate. Essentially, the main dominant strain micro-structural modes are obtained through standard reduced order modeling ...
Huespe, Alfredo Edmundo +3 more
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Investigating the effects of intersection flow localization in equivalent-continuum-based upscaling of flow in discrete fracture networks [PDF]
Solid Earth, 2021 Predicting effective permeabilities of fractured rock masses is a crucial component of reservoir modeling. Its often realized with the discrete fracture network (DFN) method, whereby single-phase incompressible fluid flow is modeled in discrete ...
M. O. Kottwitz +6 more
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Data‐Driven Stochastic Lie Transport Modeling of the 2D Euler Equations
Journal of Advances in Modeling Earth Systems, 2023 In this paper, we propose and assess several stochastic parametrizations for data‐driven modeling of the two‐dimensional Euler equations using coarse‐grid SPDEs.
Sagy R. Ephrati +3 more
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Multiscale Cancer Modeling [PDF]
Annual Review of Biomedical Engineering, 2011 Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insights in the
Deisboeck, Thomas S. +3 more
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High energy barriers for edge dislocation motion in body-centered cubic high entropy alloys
npj Computational Materials, 2021 Recent theory proposes that edge dislocations in random body-centered cubic (BCC) high entropy alloys have high barriers for motion, conveying high strengths up to high temperatures.
R. E. Kubilay +3 more
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Multiscale brain modelling [PDF]
Philosophical Transactions of the Royal Society B: Biological Sciences, 2005 A central difficulty of brain modelling is to span the range of spatio-temporal scales from synapses to the whole brain. This paper overviews results from a recent model of the generation of brain electrical activity that incorporates both basic microscopic neurophysiology and large-scale brain anatomy to predict brain electrical activity at scales ...
P A, Robinson +4 more
openaire +2 more sources
Mathematics, 2022 In this paper, we consider the poroelasticity problem in heterogeneous media. The mathematical model is described by a coupled system of equations for displacement and pressure in the coupled dual continuum porous media.
Aleksei Tyrylgin +4 more
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Origins of the change in mechanical strength of silicon/gold nanocomposites during irradiation
Scientific Reports, 2021 Silicon-based layered nanocomposites, comprised of covalent-metal interfaces, have demonstrated elevated resistance to radiation. The amorphization of the crystalline silicon sublayer during irradiation and/or heating can provide an additional mechanism ...
Elton Y. Chen +4 more
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Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
Nature Communications, 2021 In machine learning approaches relevant for chemical physics and material science, neural network potentials can be trained on the experimental data. The authors propose a training method applying trajectory reweighting instead of direct backpropagation ...
Stephan Thaler, Julija Zavadlav
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A Quantitative Molecular Orbital Perspective of the Chalcogen Bond
ChemistryOpen, 2021 Invited for this month's cover are the groups of Prof. Dr. Teodorico C. Ramalho (Federal University of Lavras and University Hradec Kralove) and Prof. Dr. F. Matthias Bickelhaupt (Vrije Universiteit Amsterdam and Radboud University).
Lucas deAzevedo Santos +4 more
doaj +2 more sources