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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Risk-Adaptive Experimental Design for High-Consequence Systems: LDRD Final Report

Constructing accurate statistical models of critical system responses typically requires an enormous amount of data from physical experiments or numerical simulations. Unfortunately, data generation is often expensive and time consuming. To streamline the data generation process, optimal experimental design determines the 'best' allocation of experiments with respect to a criterion that measures the ability to estimate some important aspect of an assumed statistical model. While optimal design has a vast literature, few researchers have developed design paradigms targeting tail statistics, such as quantiles. In this project, we tailored and extended traditional design paradigms to target distribution tails. Our approach included (i) the development of new optimality criteria to shape the distribution of prediction variances, (ii) the development of novel risk-adapted surrogate models that provably overestimate certain statistics including the probability of exceeding a threshold, and (iii) the asymptotic analysis of regression approaches that target tail statistics such as superquantile regression. To accompany our theoretical contributions, we released implementations of our methods for surrogate modeling and design of experiments in two complementary open source software packages, the ROL/OED Toolkit and PyApprox.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

NGEE Arctic LANL Overview [Slides]

The Next-Generation Ecosystem Experiments (NGEE Arctic) project has a goal to "deliver a process-rich ecosystem model, extending from bedrock to the top of the vegetative canopy/atmospheric interface, in which the evolution of Arctic ecosystems in a changing climate can be modeled at the scale of a high resolution Earth System Model (ESM) grid cell." LANL works across multiple NGEE Arctic science questions, such as: Q1. How does the structure and organization of the landscape control permafrost evolution and associated carbon and nutrient fluxes in a changing climate? Q5. Where, when, and why will the Arctic become wetter or drier, and what are the implications for climate forcing? and Q6. What controls the vulnerability of Arctic ecosystems to disturbance, and how do disturbances alter the structure and function of these ecosystems? This report features LANL's research summaries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Algorithmic and GPU enhancements for molecular dynamics in Cabana and LAMMPS

The focus of this milestone was to implement and test new algorithms and optimizations for improved GPU performance by molecular dynamics (MD) and related particle codes. The work was done in the CoPA Cabana library, the CabanaMD mini-app which uses Cabana to implement and benchmark prototypical MD models, and the LAMMPS MD code which is used by the ECP EXAALT project as well as for materials modeling generally. Efforts included (a) implementation of new or optimized algorithms for fundamental MD kernels like neighbor-list building and FFTs which are also widely used in other particle methods, (b) performance testing of data structure layouts for both simple pairwise and computationally intense neural network potentials, (c) optimizations aimed at improving GPU performance for models with small atom counts, and (d) optimizations specific to the SNAP interatomic potential due to its importance for the EXAALT project.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Large-Scale Atomistic Simulations: Investigating Free Expansion

The experiment investigates free expansion of a supercritical fluid into a two-phase liquid-vapor coexistence region. A huge molecular dynamics simulation (6 billion Lennard-Jones atoms) was run on 5760 GPUs (33% of LLNL Sierra) using LAMMPS/Kokkos software. This improved visualization workflow and started preliminary simulations of aluminum using SNAP machine learning potential.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Fusion Energy Sciences Network Requirements Review. Final Report, April - October 2021

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all of its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. Throughout 2021, ESnet and the Office of Fusion Energy Sciences (FES) of the DOE SC organized an ESnet requirements review of FES-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about their relationship to the FES program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Large-Scale Atomistic Simulations [Slides]

This report investigates free expansion of Aluminum and provides a take home message of "The physically realistic SNAP machine-learning potential captures liquid-vapor coexistence behavior for free expansion of aluminum at a level not generally accessible to hydrocodes".

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Strengthening Connections Between Research and Deployment [Slides]

This slide deck provides a high-level review of Clean Cities, Clean Energy to Communities, and Technologists in Communities and the ways these DOE-funded efforts work to translate research into deployment opportunities across the United States through community engagement, industry partnerships, and collaborative project teams.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Integrated Boiler Management through Advanced Condition Monitoring and Component Assessment

The objective of this project, supported by the U.S. Department of Energy (USDOE) under DEFE0031683, is to develop, demonstrate, and support technology transfer of an integrated boiler management system inclusive of distributed sensing and near real-time damage assessment tools to provide for the first highly accurate condition monitoring system for boiler components.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

NSTX-U liquid metal core-edge facility (LMCE)

NSTX-U/LMCE will provide a unique and world-leading research facility to address the primary challenge to delivering economic and timely magnetic fusion energy, namely the need to develop a power and particle exhaust and first-wall system that can withstand very high edge heat fluxes, maximize energy confinement, and avoid the production of large masses of solid eroded first-wall material. The NSTX-U/LMCE facility will assess the ability of liquid metals (LMs) – especially liquid lithium – to provide a new boundary condition for magnetic fusion systems, to extend the lifetime of the plasma facing components (PFCs) and improve core plasma confinement. Such capability is needed to establish the basis for next-step fusion facilities including fusion pilot plants, and to maintain U.S. world leadership in core-edge integration research. NSTX-U/LMCE will leverage the ability to generate very high divertor perpendicular heat flux q⊥ ~ 100MW/m 2 , extensive diagnostics, and liquid-metal-applicable infrastructure of NSTX-U. NSTX-U/LMCE will provide access to a high-confinement plasma core with majority self-driven plasma current, the flexibility to test a range of liquid metal divertor concepts, access to a range of separatrix collisionalities (from high to very low), and the ability to controllably vary the first-wall temperature to vary the plasma- wall interaction physics on liquid lithium components. Further, NSTX-U/LMCE will utilize more reactor-relevant high-Z refractory-metal PFC substrates. With these capabilities the NSTX-U/LMCE facility will explore the full continuum of core-edge solutions ranging from high core radiated power, to conditions with radiative losses concentrated in the scrape-off layer (SOL), and ultimately low recycling conditions. The low collisionality SOL that may be accessible in the low recycling regime is relatively unexplored and will require a kinetic treatment of the edge, which can be addressed theoretically, and with experiments in LTX-β. Additional smaller-scale preparatory R&D facilities will be required to reduce the risk of premature technical/engineering failure of liquid metal systems implemented in NSTX-U. The NSTX-U/LMCE facility aligns very well with recommendations in the FESAC Long-Range Plan and NASEM Pilot Plant reports and the Bold Decadal Vision, will be unique in the world program throughout the next decade, and is garnering private company interest in utilizing NSTX-U/LMCE for development of LM PFCs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Milestone 49 Report: Batched Sparse LA Phase 5 Implementation

Batched sparse linear algebra operations in general, and solvers in particular, have become the major algorithmic development activity and foremost performance engineering effort in the numerical software libraries work on modern hardware with accelerators such as GPUs. Many applications, ECP and non-ECP alike, require simultaneous solutions of many small linear systems of equations that are structurally sparse in one form or another. In order to move towards high hardware utilization levels, it is important to provide these applications with appropriate interface designs to be both functionally efficient and performance portable and give full access to the appropriate batched sparse solvers running on modern hardware accelerators prevalent across DOE supercomputing sites since the inception of ECP. To this end, we present here a summary of recent advances on the interface designs in use by HPC software libraries supporting batched sparse linear algebra and the development of sparse batched kernel codes for solvers and preconditioners. We also address the potential interoperability opportunities to keep the corresponding software portable between the major hardware accelerators from AMD, Intel, and NVIDIA, while maintaining the appropriate disclosure levels conforming to the active NDA agreements. The presented interface specifications include a mix of batched band, sparse iterative, and sparse direct solvers with their accompanying functionality that is already required by the application codes or we anticipated to be needed in the near future. This report summarizes progress in Kokkos Kernels and the xSDK libraries MAGMA, Ginkgo, hypre, PETSc, and SuperLU.

97 MATHEMATICS AND COMPUTING↗