Computational Breakthroughs
Develop and apply computational tools that improve prediction of high-explosives behavior in full weapons stockpile-to-target-sequence (STS) regimes.
Initiatives
- Develop and gain approval for a decadal plan to ensure competitive, robust, and sustainable energy and facilities infrastructure to meet ATS-5 deployment timeframes.
- Meet performance targets for weapons simulations on Crossroads by 2023.
- Demonstrate the capabilities of the Laboratory’s next-generation code project on El Capitan by 2024.
- Demonstrate and use the capabilities of Venado to increase predictive capabilities qualitatively through improved three-dimensional (3D) multi-physics simulations and advanced machine learning techniques, enabling a broad set of science and security breakthroughs by 2024.
- Identify and field a high-performance computing (HPC) machine that executes complex multi-physics simulation workflows within a human learning cycle by 2027.
- Incorporate high-fidelity computational exploration of narrative uncertainties into programmatic mission-critical assessments.
- Document a strategy to explore, develop, deploy, and operate HPC resources and services which are robust and forward-looking to meet program needs.
- Accelerate fundamental and applied computational and data science R&D efforts to enable achievement of critical outcomes for LANL priority areas.
- Strengthen and diversify the associated pipeline across the LANL information, science, and technology community.
- Develop and apply computational tools that improve prediction of high-explosives behavior in full weapons stockpile-to-target-sequence regimes.
- Develop a computational and analytic strategy for exploring key narrative uncertainties in problems of interest.