Reduced and all-at-once approaches for model calibration and discovery in computational solid mechanics
In the framework of solid mechanics, the task of deriving material parameters from
experimental data has recently re-emerged with the progress in full-field measurement …
experimental data has recently re-emerged with the progress in full-field measurement …
Electro-chemo-mechanical induced fracture modeling in proton exchange membrane water electrolysis for sustainable hydrogen production
F Aldakheel, C Kandekar, B Bensmann, H Dal… - Computer Methods in …, 2022 - Elsevier
This work provides a framework for predicting fracture of catalyst coated membrane (CCM)
due to coupled electro-chemo-mechanical degradation processes in proton exchange …
due to coupled electro-chemo-mechanical degradation processes in proton exchange …
An Efficient FEniCS implementation for coupling lithium-ion battery charge/discharge processes with fatigue phase-field fracture
Accurately predicting the fatigue failure of lithium-ion battery electrode particles during
charge–discharge cycles is essential for enhancing their structural reliability and lifespan …
charge–discharge cycles is essential for enhancing their structural reliability and lifespan …
Energy criterion for fracture of rocks and rock-like materials on the descending branch of the load–displacement curve
G Kolesnikov, V Shekov - Materials, 2022 - mdpi.com
This article deals with the problem of predicting the brittle fracture of rocks and similar
materials, which can also include frozen sandy soils. Such materials, due to the diversity of …
materials, which can also include frozen sandy soils. Such materials, due to the diversity of …
Differential Energy Criterion of Brittle Fracture as a Criterion for Wood's Transition to the Plastic Deformation Stage
G Kolesnikov, T Gavrilov, M Zaitseva - Symmetry, 2023 - mdpi.com
An experimental study and modeling of the behavior of wood during compression along the
fibers was carried out. The nonlinear analytical dependence of the load on the strain was …
fibers was carried out. The nonlinear analytical dependence of the load on the strain was …
Parameter identification and uncertainty propagation of hydrogel coupled diffusion-deformation using POD-based reduced-order modeling
This study explores reduced-order modeling for analyzing time-dependent diffusion-
deformation of hydrogels. The full-order model describing hydrogel transient behavior …
deformation of hydrogels. The full-order model describing hydrogel transient behavior …
Theoretical framework and inference for fitting extreme data through the modified Weibull distribution in a first-failure censored progressive approach
MS Eliwa, LA Al-Essa, AM Abou-Senna… - Heliyon, 2024 - cell.com
The importance of biomedical physical data is underscored by its crucial role in advancing
our comprehension of human health, unraveling the mechanisms underlying diseases, and …
our comprehension of human health, unraveling the mechanisms underlying diseases, and …
Bayesian optimization-assisted approximate Bayesian computation and its application to identifying cyclic constitutive law of structural steels
A costly finite element model discourages Bayesian inference of the underlying parameters
from noise-corrupted experimental datasets. This arises because the likelihood of such a …
from noise-corrupted experimental datasets. This arises because the likelihood of such a …
Rational design of field-effect sensors using partial differential equations, Bayesian inversion, and artificial neural networks
Silicon nanowire field-effect transistors are promising devices used to detect minute
amounts of different biological species. We introduce the theoretical and computational …
amounts of different biological species. We introduce the theoretical and computational …
Transfer learning-based coupling of smoothed finite element method and physics-informed neural network for solving elastoplastic inverse problems
M Zhou, G Mei - Mathematics, 2023 - mdpi.com
In practical engineering applications, there is a high demand for inverting parameters for
various materials, and obtaining monitoring data can be costly. Traditional inverse methods …
various materials, and obtaining monitoring data can be costly. Traditional inverse methods …