USC researchers are developing a computational model that combines satellite data and physics-based simulations to forecast a ...

Dyad AI from JuliaHub is bringing an AI-for-Science environment to product development. Users can model and interrogate systems, research formulations, derive governing equations, assemble models, run ...

Electrochemical impedance spectroscopy (EIS) provides valuable insights into the physical processes within batteries – but how can these measurements directly inform physics-based models? In this ...

Why real-world, physics-based simulation is important to designers. What is a pluggable solver? What is Ansys Perceive EM? These days, most products are simulated well before they’re constructed or ...

MUNICH--(BUSINESS WIRE)--SimScale GmbH announced today the worlds’ first fully integrated and cloud-native A.I. based physics predictions coming to its simulation software. SimScale has partnered with ...

At SAE World Congress 2026, Luminary, the Physics AI company, today announced SHIFT-Crash, the first Physics AI model that predicts full-vehicle crash response, including deformation and stress fields ...

Mechanical engineering has traditionally relied on physics, mathematics, and empirical knowledge to design and optimize systems. Machine learning (ML) introduces powerful tools that can complement ...

Researchers from BIFOLD and Google DeepMind have developed MD-ET, a transformer-based molecular dynamics model that omits traditional physics constraints like energy conservation and equivariance.

The use of better-quality data can improve the business case for a number of solar projects. Image: Photon Group. The integrity of a PV project largely depends on the quality of the solar, ...