Ansys has introduced SimAI, a cloud-native, AI-powered simulation platform designed to make advanced engineering analysis ...

Customers can also predict geometry performance with built-in validation against high-fidelity CFD results to support faster, ...

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...

Running a single physics simulation can take hours or days, depending on the complexity of the geometry and the equations involved. For engineers iterating through hundreds of design variations, that ...

Design engineering is running headfirst into a materials bottleneck. Industries such as automotive, aerospace, electronics, and semiconductors now depend on increasingly complex materials. Yet ...

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 ...

Combining artificial intelligence with physical climate modelling enables more accurate characterization of rare weather ...

Breakthroughs in Neural Rendering, GPU Innovation, and Generative AI Take Center Stage With Speakers From NVIDIA, Bolt ...

Scientists found that transfer learning can make the search for new physics in the universe much faster, slashing the need for expensive simulations. Yet the approach can backfire when AI relies too ...

During surgery to correct an abnormal heartbeat, doctors rely on a mix of imaging and inference. Still, many critical details remain hidden. At RIT, artificial intelligence (AI) researchers want to ...