5 papers
An Agentic Orchestration of Atomistic Simulations
Rahul Somasundaram, Adela Habib, Khanh Dang +12
Atomistic simulations are central to materials design, but their execution involves complex, multi-step workflows that require significant human expertise. Here, we present an agen…
Physics-informed reservoir characterization from bulk and extreme pressure events with a differentiable simulator
Harun Ur Rashid, Mingxin Li, Aleksandra Pachalieva +2
Accurate characterization of subsurface heterogeneity is challenging but essential for applications such as reservoir pressure management, geothermal energy extraction and CO,…
Out-of-distribution transfer of PDE foundation models to material dynamics under extreme loading
Mahindra Rautela, Alexander Most, Siddharth Mansingh +9
Most PDE foundation models are pretrained and fine-tuned on fluid-centric benchmarks. Their utility under extreme-loading material dynamics remains unclear. We benchmark out-of-dis…
Differentiable multiphase flow model for physics-informed machine learning in reservoir pressure management
Harun Ur Rashid, Aleksandra Pachalieva, Daniel O'Malley
Accurate subsurface reservoir pressure control is extremely challenging due to geological heterogeneity and multiphase fluid-flow dynamics. Predicting behavior in this setting reli…
A Foundation Model for Material Fracture Prediction
Agnese Marcato, Aleksandra Pachalieva, Ryley G. Hill +14
Accurately predicting when and how materials fail is critical to designing safe, reliable structures, mechanical systems, and engineered components that operate under stress. Yet,…