A computational physics approach to modeling rigid object motion using spring forces in Python. This focuses on how spring systems can approximate real-world rigid body behavior through numerical ...

This Research Topic is Volume II of a series. The previous volumes can be found here: Natural Disaster Prediction Based on Experimental and Numerical ...

Researchers combine numerical modeling with neural networks to show how nanodiamond aggregation, magnetic fields, and surface ...

This figure illustrates the formation and numerical replication of barred olivine, a unique crystalline texture found in chondrules within meteorites. (a) A polarized light micrograph shows a natural ...

The goal of this study was to accurately match experimental data obtained from compression tests in particle-based simulations of soil behavior. Thanks to a comprehensive sensitivity analysis, the ...

Chinese researchers have published a new AI-driven system designed to interpret scramjet combustion simulations at speeds ...

Using the Frontier supercomputer at the Department of Energy's Oak Ridge National Laboratory, researchers from the Georgia Institute of Technology have performed the largest direct numerical ...

Keywords: ALE, LS-DYNA, earthquake-simulator tests, reactor vessels, reactor internals, seismic fluid-structure interaction, seismic isolation Abstract: This report describes physical and numerical ...

Researchers combined deep learning with high-resolution physics to create the first Milky Way model that tracks over 100 billion stars individually. Their AI learned how gas behaves after supernovae, ...

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and ...