Results 21 to 30 of about 3,809,966 (324)

PARALLEL COMPUTATIONS AND CO-SIMULATION IN UNIVERSAL MECHANISM SOFTWARE. PART II: EXAMPLES [PDF]

open access: yesTransport Problems, 2019
The second part of the paper continues a discussion on the topic of parallel computations in railway dynamics. The algorithms described in the first part of the paper are applied to parallel simulation on computers with multicore processors of six ...
Dmitry POGORELOV   +2 more
doaj   +1 more source

Numerical investigation of the basilar membrane vibration induced by the unsteady fluid flow in the human inner ear [PDF]

open access: yesArchive of Mechanical Engineering, 2020
For a deeper understanding of the inner ear dynamics, a Finite-Element model of the human cochlea is developed. To describe the unsteady, viscous creeping flow of the liquid, a pressure-displacement-based Finite-Element formulation is used.
Philipp Wahl   +2 more
doaj   +1 more source

Computational Mechanics

open access: yesEncyclopedia of Continuum Mechanics, 2015
L. Komzsik
openaire   +2 more sources

An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications [PDF]

open access: yesComputer Methods in Applied Mechanics and Engineering, 2019
Partial Differential Equations (PDE) are fundamental to model different phenomena in science and engineering mathematically. Solving them is a crucial step towards a precise knowledge of the behaviour of natural and engineered systems.
Esteban Samaniego   +7 more
semanticscholar   +1 more source

Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity [PDF]

open access: yesComputer Methods in Applied Mechanics and Engineering, 2020
We present a machine learning approach that integrates geometric deep learning and Sobolev training to generate a family of finite strain anisotropic hyperelastic models that predict the homogenized responses of polycrystals previously unseen during the ...
Nikolaos N. Vlassis, R. Ma, WaiChing Sun
semanticscholar   +1 more source

An introduction to programming Physics-Informed Neural Network-based computational solid mechanics [PDF]

open access: yesInternational Journal of Computational Methods, 2022
Physics-informed neural network (PINN) has recently gained increasing interest in computational mechanics. In this work, we present a detailed introduction to programming PINN-based computational solid mechanics.
Jinshuai Bai   +8 more
semanticscholar   +1 more source

A simple yet consistent constitutive law and mortar-based layer coupling schemes for thermomechanical macroscale simulations of metal additive manufacturing processes

open access: yesAdvanced Modeling and Simulation in Engineering Sciences, 2021
This article proposes a coupled thermomechanical finite element model tailored to the macroscale simulation of metal additive manufacturing processes such as selective laser melting.
Sebastian D. Proell   +2 more
doaj   +1 more source

On phase change and latent heat models in metal additive manufacturing process simulation

open access: yesAdvanced Modeling and Simulation in Engineering Sciences, 2020
This work proposes an extension of phase change and latent heat models for the simulation of metal powder bed fusion additive manufacturing processes on the macroscale and compares different models with respect to accuracy and numerical efficiency ...
Sebastian D. Proell   +2 more
doaj   +1 more source

Examination of polarization coupling in a plucked musical instrument string via experiments and simulations

open access: yesActa Acustica, 2020
In this article, the transient motion of a realistically plucked guitar string is studied experimentally and numerically in both transversal polarizations.
Brauchler Alexander   +2 more
doaj   +1 more source

Model-free Data-Driven Computational Mechanics Enhanced by Tensor Voting [PDF]

open access: yesComputer Methods in Applied Mechanics and Engineering, 2020
The data-driven computing paradigm initially introduced by Kirchdoerfer and Ortiz (2016) is extended by incorporating locally linear tangent spaces into the data set. These tangent spaces are constructed by means of the tensor voting method introduced by
R. Eggersmann   +3 more
semanticscholar   +1 more source

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