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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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At least 415 records · Page 23

Next-Generation Simulations of the Remarkable Deaths Of Massive Stars [Slides]

3D models of stellar convection are necessary for accurate description of state of model near collapse. Convection is occurring at many scales with the large dominant mode near collapse. 3D instabilities can affect flow properties and mass entrainment. Mach number profiles show favorable conditions for explosion. 3D rotating progenitor models are ALSO necessary. The redistribution of AM diverges from the MESA model, with implications for remnant. There is turbulent transport of AM in convective shell regions. Multi-D models can provide input for successful CCSN models. Larger non-radial kinetic energy exists when using multi-D progenitor input. The 3D CCSN model showed prompt convection and asymmetric shock runaway. Explosion properties suggest robust impact on multi-messenger signals.

79 ASTRONOMY AND ASTROPHYSICS↗

Next-Generation Simulations of the Remarkable Deaths of Massive Stars [Slides]

This report discusses core-collapse of supernovae and provides this basic summary: 3D models of stellar convection are necessary for accurate description of state of model near collapse, 3D rotating progenitor models are also necessary, and multi-D models can provide input for successful CCSN models.

79 ASTRONOMY AND ASTROPHYSICS↗

Detector and Beamline Simulation for Next-Generation High Energy Physics Experiments

The success of high energy physics programs relies heavily on accurate detector simulations and beam interaction modeling. The increasingly complex detector geometries and beam dynamics require sophisticated techniques in order to meet the demands of current and future experiments. Common software tools used today are unable to fully utilize modern computational resources, while data-recording rates are often orders of magnitude larger than what can be produced via simulation. In this paper, we describe the state, current and future needs of high energy physics detector and beamline simulations and related challenges, and we propose a number of possible ways to address them.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Combining Physics and Machine Learning for the Next Generation of Molecular Simulation

Simulating molecules and atomic systems at quantum accuracy is a grand challenge for science in the 21 st century. Quantum-accurate simulations would enable the design of new medicines and the discovery of new materials. The defining problem in this challenge is that quantum calculations on large molecules, like proteins or DNA, are fundamentally impossible with current algorithms. In this work, we explore a range of different methods that aim to make large, quantum-accurate simulations possible. We show that using advanced classical models, we can accurately simulate ion channels, an important biomolecular system. We show how advanced classical models can be implemented in an exascale-ready software package. Lastly, we show how machine learning can learn the laws of quantum mechanics from data and enable quantum electronic structure calculations on thousands of atoms, a feat that is impossible for current algorithms. Altogether, this work shows that combining advances in physics models, computing, and machine learning, we are moving closer to the reality of accurately simulating our molecular world.

74 ATOMIC AND MOLECULAR PHYSICS↗