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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗
DOE OSTI2016

Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced order models for the compressible Navier–Stokes equations

For a projection-based reduced order model (ROM) of a fluid flow to be stable and accurate, the dynamics of the truncated subspace must be taken into account. This paper proposes an approach for stabilizing and enhancing projection-based fluid ROMs in which truncated modes are accounted for a priori via a minimal rotation of the projection subspace. Attention is focused on the full non-linear compressible Navier–Stokes equations in specific volume form as a step toward a more general formulation for problems with generic non-linearities. Unlike traditional approaches, no empirical turbulence modeling terms are required, and consistency between the ROM and the Navier–Stokes equation from which the ROM is derived is maintained. Mathematically, the approach is formulated as a trace minimization problem on the Stiefel manifold. As a result, the reproductive as well as predictive capabilities of the method are evaluated on several compressible flow problems, including a problem involving laminar flow over an airfoil with a high angle of attack, and a channel-driven cavity flow problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Contribution of IAEA coordinated research projects to light water reactors advanced technology fuel testing and simulation

The Fukushima-Daiichi accident in 2011 highlighted the pressing need for enhanced design and safety analysis of nuclear fuels, especially under accident conditions in nuclear power plants (NPPs). To address this need, the international nuclear fuel community has developed several concepts of Accident Tolerant and Advanced Technology Fuels (ATFs) for light water reactors. The International Atomic Energy Agency (IAEA), at the request of its Member States, has initiated a series of three Coordinated Research Projects (CRPs) to aid in the development and testing of these ATFs. Further, these projects, known as FUMAC, ACTOF, and ATF-TS, focus on the experimentation and simulation of ATFs under various accident conditions, including design basis accidents and design extension conditions. This paper provides a comprehensive overview of the main activities, as well as the achieved or anticipated results of these three CRPs. The insights and advancements gained from these projects will enable IAEA Member States to further refine nuclear fission technology, thereby contributing to efforts aimed at mitigating climate change.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Crustal Deformation and Gravitational Effects From Dynamic Ocean Mass Redistribution Impact Projected Sea‐Level Change

As the climate warms, associated changes in ocean dynamics will redistribute sea‐water mass within the ocean, contributing to relative sea‐level change. This mass redistribution will cause additional sea‐level changes due to gravitational self‐attraction, deformation of the solid Earth, and shifts in the Earth's rotation axis (GRD), which are not incorporated in sea‐level projections. Using CMIP6 climate model output, we quantify relative sea‐level changes induced by GRD from ocean‐dynamic mass loading through 2100. These effects act to amplify projected ocean‐dynamic sea‐level patterns, causing sea‐level rise in coastal regions, particularly along wide continental shelves and at high latitudes. On average, the magnitude of such GRD‐induced sea‐level change is equivalent to ∼15% of the signal due to dynamic ocean mass redistribution. Although our results show substantial inter‐model spread, they reveal that GRD‐induced relative sea‐level changes from ocean mass redistribution represent a non‐negligible component of regional sea‐level change and should be considered in projections.

58 GEOSCIENCES↗
DOE OSTI2022

Machine learning-based observation-constrained projections reveal elevated global socioeconomic risks from wildfire

Reliable projections of wildfire and associated socioeconomic risks are crucial for the development of efficient and effective adaptation and mitigation strategies. The lack of or limited observational constraints for modeling outputs impairs the credibility of wildfire projections. Here, we present a machine learning framework to constrain the future fire carbon emissions simulated by 13 Earth system models from the Coupled Model Intercomparison Project phase 6 (CMIP6), using historical, observed joint states of fire-relevant variables. During the twenty-first century, the observation-constrained ensemble indicates a weaker increase in global fire carbon emissions but higher increase in global wildfire exposure in population, gross domestic production, and agricultural area, compared with the default ensemble. Such elevated socioeconomic risks are primarily caused by the compound regional enhancement of future wildfire activity and socioeconomic development in the western and central African countries, necessitating an emergent strategic preparedness to wildfires in these countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Robust projection of East Asian summer monsoon rainfall based on dynamical modes of variability

Abstract The Asian monsoon provides the freshwater that a large population in Asia depends on, but how anthropogenic climate warming may alter this key water source remains unclear. This is partly due to the prevailing point-wise assessment of climate projections, even though climate change patterns are inherently organized by dynamics intrinsic to the climate system. Here, we assess the future changes in the East Asian summer monsoon precipitation by projecting the precipitation from several large ensemble simulations and CMIP6 simulations onto the two leading dynamical modes of internal variability. The result shows a remarkable agreement among the ensembles on the increasing trends and the increasing daily variability in both dynamical modes, with the projection pattern emerging as early as the late 2030 s. The increase of the daily variability of the modes heralds more monsoon-related hydrological extremes over some identifiable East Asian regions in the coming decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Robustness and uncertainties in global multivariate wind-wave climate projections

Understanding climate-driven impacts on the multivariate global wind-wave climate is paramount to effective offshore/coastal climate adaptation planning. However, the use of single-method ensembles and variations arising from different methodologies has resulted in unquantified uncertainty amongst existing global wave climate projections. Here, assessing the first coherent, community-driven, multi-method ensemble of global wave climate projections, we demonstrate widespread ocean regions with robust changes in annual mean significant wave height and mean wave period of 5–15% and shifts in mean wave direction of 5–15°, under a high-emission scenario. Approximately 50% of the world’s coastline is at risk from wave climate change, with ~40% revealing robust changes in at least two variables. Finally, we find that uncertainty in current projections is dominated by climate model-driven uncertainty, and that single-method modelling studies are unable to capture up to ~50% of the total associated uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Capturing convection essential for projections of climate change in African dust emission

The summertime Sahara and Sahel are the world’s largest source of airborne mineral dust. Cold-pool outflows from moist convection (‘haboobs’) are a dominant source of summertime uplift but are essentially missing in global models, raising major questions on the reliability of climate projections of dust and dust impacts. Here we use convection-permitting simulations of pan-African climate change, which explicitly capture haboobs, to investigate whether this key limitation of global models affects projections. We show that explicit convection is key to capturing the observed summertime maximum of dust-generating winds, which is missed with parameterised convection. Despite this, future climate changes in dust-generating winds are more sensitive to the effects of explicit convection on the wider meteorology than they are to the haboobs themselves, with model differences in the change in dust-generating winds reaching 60% of current values. The results therefore show the importance of improving convection in climate models for dust projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Neutronics Calculation Advances at Los Alamos: Manhattan Project to Monte Carlo

The history and advances of neutronics calculations at Los Alamos during the Manhattan Project through the present are reviewed. Substantial improvements to neutron diffusion methods and the invention of both the Monte Carlo neutron transport methods in 1947 and deterministic discrete ordinates Sn in 1953 were all made at Los Alamos just after the Manhattan Project. We briefly summarize early simpler and more approximate neutronics methods and then describe the need to better predict neutronics behavior through consideration of theoretical equations, models and algorithms, experimental measurements, and available computing capabilities and their limitations. This paper briefly covers key advances in deterministic methods during the Manhattan Project. These capabilities, coupled with increasing postwar defense needs and the invention of electronic computing with the Electronic Numeric Integrator and Computer, known as ENIAC, and the Mathematical Analyzer Numerical Integrator and Automatic Computer Model, known as MANIAC, led to the creation of Monte Carlo and deterministic discrete ordinates neutronics transport methods. We note the important role that the scientific comradery between the Los Alamos scientists played in the process. This paper briefly covers the early methods, algorithms, computers, and electronic and women pioneers that enabled Monte Carlo to spread to all areas of science. We focus heavily on these early developments and the subsequent creation of the MCNP® code, advances in its associated nuclear data, and its applications to problems of national defense at Los Alamos.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Nuclear states projected from a pair condensate

Atomic nuclei exhibit deformation, pairing correlations, and rotational symmetries. To meet these competing demands in a computationally tractable formalism, we revisit the use of general pair condensates with good particle number as a trial wave function for even-even nuclei. After minimizing the energy of the condensate, allowing for general triaxial deformations, we project out states with good angular momentum with a fast projection technique. To show applicability, we present example calculations from pair condensates in several model spaces and compare against angular-momentum projected Hartree-Fock and full configuration-interaction shell-model calculations. This approach successfully generates spherical, vibrational, and rotational spectra, demonstrating potential for modeling medium- to heavy-mass nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Projection of angular momentum via linear algebra

Projection of many-body states with good angular momentum from an initial state is usually accomplished by a three-dimensional integral. Here, we show how projection can instead be done by solving a straightforward system of linear equations. We demonstrate the method and give sample applications to $^{48}$Cr and $^{60}$Fe in the $pf$ shell. This new projection scheme, which is competitive against the standard numerical quadrature, should also be applicable to other quantum numbers such as isospin and particle number.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Remark on Algorithm 1012: Computing Projections with Large Datasets

In ACM TOMS Algorithm 1012, the DELAUNAYSPARSE software is given for performing Delaunay interpolation in medium to high dimensions. When extrapolating outside the convex hull of the training set, DELAUNAYSPARSE calls the nonnegative least squares solver DWNNLS to compute projections onto the convex hull. However, DWNNLS and many other available sum-of-squares optimization solvers were not intended for usage with many variable problems, which result from the large training sets that are typical in machine learning applications. Thus, a new PROJECT subroutine is given, based on the highly customizable quadratic program solver BQPD. This solution is shown to be as robust as DELAUNAYSPARSE for projection onto both synthetic and real-world datasets, where other available solvers frequently fail. Although it is intended as an update for DELAUNAYSPARSE, due to the difficulty and prevalence of the problem, this solution is likely to be of external interest as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A survey of software implementations used by application codes in the Exascale Computing Project

The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis

An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different case studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Idaho National Laboratory’s Analysis of ARRA-Funded Plug-in Electric Vehicle and Charging Infrastructure Projects: Final Report

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s (DOE) Idaho National Laboratory (INL), is the lead laboratory for U.S. Department of Energy’s Advanced Vehicle Testing Activity (AVTA). INL’s conduct of the AVTA resulted in a significant base of knowledge and experience in the area of testing light-duty vehicles that reduced transportation-related petroleum consumption. Due to this experience, INL was tasked by DOE to develop agreements with companies that were the recipients of The American Recovery and Reinvestment Act of 2009 (ARRA) grants, that would allow INL to collect raw data from light-duty vehicles and charging infrastructure. INL developed non-disclosure agreements (NDAs) with several companies and their partners that resulted in INL being able to receive raw data via server-to-server connections from the partner companies. This raw data allowed INL to independently conduct data quality checks, perform analysis, and report publicly to DOE, partners, and stakeholders, how drivers used both new vehicle technologies and the deployed charging infrastructure. The ultimate goal was not the deployment of vehicles and charging infrastructure, cut rather to create real-world laboratories of vehicles, charging infrastructure and drivers that would aid in the design of future electric drive transportation systems. The five projects that INL collected data from and their partners are: • ChargePoint America - Plug-in Electric Vehicle Charging Infrastructure Demonstration • Chrysler Ram PHEV Pickup - Vehicle Demonstration • General Motors Chevrolet Volt - Vehicle Demonstration • The EV Project - Plug-in Electric Vehicle Charging Infrastructure Demonstration • EPRI / Via Motors PHEVs – Vehicle Demonstration The document serves to benchmark the performance science involved the execution, analysis and reporting for the five above projects that provided lessons learned based on driver’s use of the vehicles and recharging decisions made. Data is reported for the use of more than 25,000 vehicles and charging units.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Iowa Hill Pumped Storage Project Investigations - Final Technical Report

This Final Technical Report is a summary of the activities and outcome of the Department of Energy (DOE) Assistance Agreement DE-EE0005414 with the Sacramento Municipal Utility District (SMUD). The Assistance Agreement was created in 2012 to support investigations into the Iowa Hill Pumped-storage Project (Project), a new development that would add an additional 400 MW of capacity to SMUD’s existing 688MW Upper American River Hydroelectric Project (UARP) in the Sierra Nevada mountains east of Sacramento, California.

13 HYDRO ENERGY↗
DOE OSTI2015

The EV Project Price/Fee Models for Publicly Accessible Charging

As plug-in electric vehicles (PEVs) are introduced to the market place and gain more consumer acceptance, it is important for a robust and self-sustaining non-residential infrastructure of electric vehicle supply equipment (EVSE) to be established to meet the needs of PEV drivers. While federal and state financial incentives for electric vehicles were in place and remain so today, future incentives are uncertain. In order for PEVs to achieve mainstream adoption, an adequate and sustainable commercial or publicly available charging infrastructure was pursued by The EV Project to encourage increased PEV purchases by alleviating range anxiety, and by removing adoption barriers for consumers without a dedicated overnight parking location to provide a home-base charger. This included determining a business model for publicly accessible charge infrastructure. To establish this business model, The EV Project team created a fee for charge model along with various ancillary offerings related to charging that would generate revenue. And after placing chargers in the field the Project rolled out this fee structure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Community Solar Value Project

The Community Solar Value Project (CSVP) is designed to assist electric utilities in designing better community solar programs. Better programs seek new sources of value to promote “win-win” solutions between utilities and their customers. The CSVP focused on five “challenge areas” in identifying new sources of value: - Strategic solar design for community solar projects (including technology choices, siting, orientation, and related issues) - Market research and targeted marketing approaches (for program design and for customer recruitment) - Procurement and financing (for establishing best practices that can bring economies of scale and economies of expertise) - Integration of “companion measures” (such as storage and demand-response options that can benefit customer and utility net load shapes) - Pricing in program design (including best practices for integration of identified value in program prices or credits) The CSVP directly engaged the Sacramento Municipal Utility District (SMUD), the Public Service Company of New Mexico (PNM), and more than a dozen other utilities to develop improved community solar program designs. The outcomes include a plan at SMUD for over 100 MW or more of community and shared solar and support for new or expanded programs at 15 other utilities so far. Resulting best-practice solutions have not only informed program applications, but also have generated discussion among experts and industry associations about the new opportunities and challenges CSVP has brought forth. In these ways, the CSVP has impacted community solar programs and DER plans, competitive innovations and policies nationwide. The CSVP team has been led by Extensible Energy under John Powers, President and CEO. Jill Cliburn, of Santa Fe, NM-based Cliburn and Associates, has served as Principal Investigator. The team also benefitted from expertise from Navigant, Olivine Inc. and Millennium Energy, LLC, in addition to the collaborative and cost-sharing contributions of its utility partners. The CSVP team participated fully in the Solar Market Pathways Program, which was initiated under the U.S. Department of Energy SunShot program and reports to the U.S. Department of Energy Solar Energy Technologies Office. This report summarizes a multi-disciplinary project that took place over 33 months from January, 2015 through September, 2017.

14 SOLAR ENERGY↗