SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Develop an efficient parallel implementation and assess the performance of local time-stepping (LTS) schemes for the shallow water equations in the Model for Prediction Across Scales (MPAS).
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Simulation and Computation plays a pivotal role in maintaining confidence in the stockpile as the approach to underwrite that confidence has changed. The need for resolution and fidelity at scale drives our need for increased computing capability. DOE/NNSA Advanced Simulation and Computing (ASC) program provides the computational surrogate for testing. ASC provides simulation-based confidence in the U.S. stockpile.
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Topics in this presentation are: IBEX, Nuclei Modeling, Tropical Cyclones, and Earth to Mars.
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HPC Monitoring is tasked with the understanding of everything that happens in the Data Center. They get to that understanding by: collecting logs and metrics, processing data, analyzing data, displaying information, and receiving alerts on events. Their ultimate (and probably unreachable) goal is a holistic view of the Data Center and an understanding of how everything is correlated.
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Future radiographic facilities for the U.S. defense program will be required to provide more information as simulation codes improve in both physics’ fidelity and resolution. A possible approach is to use more types of probe beams in addition to, or instead of X-rays, generated by 20-MeV electron accelerators from a small number of directions. High power short-pulse laser systems can generate beams of protons, neutrons and electrons, as well as X-rays. The cost of these systems is falling rapidly. So, it can be imagined that deploying multiple short-pulse lasers along with other, more traditional probes, will become feasible. In this project, we are following three paths to determine if such an approach will succeed for cm-scale objects. The first is an experimental one to determine if the presence of multiple short-pulse probes cause interference with each other, especially while radiographing dynamic objects. The second leg of this project is to determine if having multiple types of probes really does give more information on composition. Finally, an overall assessment of the viability of this approach will be made. Examples from recent experiments at the Omega EP laser will be presented. The initial approach to evaluating radiographs with multiple probes using the Bayesian Inference Engine (BIE) also will be given.
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Hydrocarbon production from shale reservoirs is inherently inefficient and challenging since these are low permeability plays. In addition, there is a limited understanding of the fundamentals and the controlling mechanisms, further complicating how to optimize these plays. Herein, we summarize our experimental and computational efforts fully and partially supported by the fundamental shale portfolio to reveal unconventional shale fundamentals and devise development strategies to enhance extraction efficiency with a minimal environmental footprint. Integrating these fundamentals with machine learning, we outline a pathway to improve the predictive power of our models, which enhances the forecast quality of production, thereby improving the economics of operations in unconventional reservoirs. For instance, we have developed science informed workflows and platforms for optimizing pressure-drawdown at a site, which allow operators to make reservoir-management decisions that optimize recovery in consideration of future production. Recently, our work relies on the hybridization of physics-based prediction and machine learning, whereby accurate synthetic data (combined with available site data) can enable the application of machine learning methods for rapid forecasting and optimization. Consequently, the workflow and platform are readily extendable to operations at other sites, plays, and basins.