Dan Negrut and Asher Elmquist are among the co-authors of a recent paper published in the Proceedings of the National Academy of Sciences (PNAS). The “perspectives” manuscript discusses opportunities and challenges associated with the use …
Year: 2020
SBEL receives $200,000 grant from the US Army Research Office via a DURIP instrumentation award
At the beginning of December, SBEL received a $200,000 grant to upgrade the Euler supercomputer. The money will be spent to deploy a Mellanox Infiniband interconnect between the nodes of Euler. In addition, the money …
SBEL collaborates with NASA in preparation for 2024 lunar mission
For the next two years, SBEL will work on a NASA project tied to the 2024 lunar mission in which the VIPER rover will search for frozen water at the South Pole of moon. Our …
Continuum Modeling of Granular Material Flows and their Interactions with Solid Bodies
This project outlines a continuous approach for treating discrete granular flows that hold across multiple scales: from experiments that focus on centimeter-sized control volumes to tests that involve landslides and tall buildings. The motion of …
Producing 3D Friction Loads by Tracking the Motion of the Contact Point on Bodies in Mutual Contact
Lab researchers, Luning Fang and Dan Negrut, recently completed a paper to be published by the Journal, Computational Particle Mechanics. Their general approach to modeling friction is inspired by tracking the evolution of the contact …
Chrono Tutorials at MaGIC 2020
Several SBEL-ites presented Chrono-related tutorials at the 2020 edition of the Machine-Ground Interaction Consortium (MaGIC). Asher Elmquist presented on Chrono::Sensor Jay Taves and Aaron Young presented on SynChrono Luning Fang presented on Chrono::Granular Radu Serban …
Two SBEL Students Win Poster Prize at MaGIC 2020
At the 2020 edition of the Machine-Ground Interaction Consortium (MaGIC), two SBEL students won a prize for the posters they presented on lab research. Alex Pletta won 1st prize with a poster on advanced control …
Chrono::GPU, Modeling and Simulation of Granular Dynamics using GPU Computing
Modeling granular system of large degree of freedom poses high computation cost. Chrono::GPU is designed to simulate granular material via the framework of Discrete Element Method (DEM) to produce realistic results. The physics-based features include …
SynChrono poster accepted to SC20
A SynChrono reinforcement learning poster was recently accepted for presentation at the SC20 supercomputing conference. The poster highlights machine-learning work with a convoy of autonomous vehicles operating cohesively on deformable off-road terrain. Several pieces of …
Chrono Integration with Cognitive Systems Lab Driving Simulator
SBEL has partnered with the Cognitive Systems Lab (CSL) and Professor Sue Ahn’s lab on an NSF-sponsored project to better understand traffic flows in the context of human takeover from autonomous vehicles. For research on …