Surface-mount polymer positive temperature coefficient (PPTC) devices are widely used resettable protection components in modern electronic systems. These devices are commonly selected when designers ...

Boston Dynamics has revealed how its Atlas humanoid robot learned to lift and carry heavy industrial objects using reinforcement learning and large-scale simulation training. In a newly released ...

Abstract: The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along ...

Pharmaceutical companies and research institutions are using artificial intelligence to design robotic experiments at scale, but they need to know if AI-generated instructions will execute correctly ...

Understand the fundamental concepts of molecular dynamics simulations Set up and run a basic molecular dynamics simulation using GROMACS Analyze and visualize simulation results: radial distribution ...

This paper presents a novel simulation framework for estimating the dynamic response of a full-scale ground-mounted solar panel array under stationary wind loads that are spatially correlated across ...

Researchers in the United States have used an exascale supercomputer to perform the largest fluid dynamics simulation ever. It surpassed one quadrillion degrees of freedom in a single computational ...

Abstract: Product design involves the conceptualization and creation of products, where simulation workflows often require dynamic scheduling. Although deep reinforcement learning has shown ...

We study the cavitation bubble that forms as a nano-scale spherical surface is detached from a flat surface using molecular dynamics (MD) simulations. This investigation maps the onset and early ...

The success of a molecular dynamics simulation depends on the accuracy of the force field used to define the atomic interactions. It is challenging to train both classical and modern machine-learning ...