Results 111 to 120 of about 4,141,656 (337)
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi +4 more
wiley +1 more source
Applying computational complexity to the emergence of classicality [PDF]
Can the computational complexity theory of computer science and mathematics say something new about unresolved problems in quantum physics? Particularly, can the P versus NP question in the computational complexity theory be a factor in the elucidation ...
Bolotin, Arkady
core
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
Grand Challenges in Computational Physics
Kay eHamacher
doaj +3 more sources
The role of various alloying elements in face‐centered cubic aluminum on the barrier of a Shockley partial dislocation during its motion is presented. The study aims to understand how alloying atoms such as Mg, Si, and Zr affect the energy landscape for dislocation motion, thus influencing the solid solution hardening and softening in aluminum, which ...
Inna Plyushchay +3 more
wiley +1 more source
Numerical Generation of Trajectories Statistically Consistent with Stochastic Differential Equations
A weak second-order numerical method for generating trajectories based on stochastic differential equations (SDE) is developed. The proposed approach bypasses direct noise realization by updating the system’s state using independent Gaussian random ...
Mykhaylo Evstigneev
doaj +1 more source
Methods in Computational Physics, Volumes 11 and 12, Volume 11--Seismology : Surface Waves and Earth Oscillations, Volume 12--Seismology: Body Waves and Sources, B. A. Bolt (Editor), (Academic Press, New York & London, x+308pp., x+391pp.) [PDF]
J. Woodhouse
openalex +1 more source
This study presents a 3D representative volume element‐based simulation approach to predict mesoscopic residual stress and strain fields in silicon solid solution‐strengthened ductile cast iron. By modeling phase transformation kinetics with an enhanced Johnson–Mehl–Avrami–Kolmogorov model, the effects of varying cooling rates on residual stresses are ...
Lutz Horbach +6 more
wiley +1 more source

