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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

AXEAP (ARGONNE X-RAY EMISSION PACKAGE)

Argonne X-ray Emission Package (AXEAP), a singular purpose software package for processing X-ray emission (XES) images collected with a 2-dimensional position sensitive pixel array detector, has been developed. AXEAP can rapidly convert XES image files into a spectral form by applying parallel computation and unsupervised machine learning to compute vast amount of image data. Special focus has been placed on designing user-friendly-interface for processing multiple edges, non-resonant and resonant x-ray emission image analysis, in order to make data processing quick and easy. AXEAP is free software and is written in MATLAB, armed with powerful libraries and toolboxes. The software runs on all common operating systems such as Linux, Window, and Mac.

SUN, CHENGJUN↗
DOE OSTI2024

Steric and Electronic Influence of Excited-State Decay in Cu(I) MLCT Chromophores

For the past eleven years, a dedicated effort in our research group focused on fundamentally advancing the photophysical properties of cuprous bis-phenanthroline-based metal-to-ligand charge transfer (MLCT) excited states. We rationalized that by gaining control over the numerous factors limiting the more widespread use of Cu I MLCT photosensitizers, they would be readily adopted in numerous light-activated applications given the earth-abundance of copper and the extensive library of 1,10-phenanthrolines developed over the last century. Significant progress has been achieved by recognizing valuable structure-property concepts developed by other researchers in tandem with detailed ultrafast and conventional time-scale investigations, in-silico-inspired molecular designs to predict spectroscopic properties, and applying novel synthetic methodologies. Ultimately, we achieved a plateau in exerting cooperative steric influence to control Cu I MLCT excited state decay. This led to combining sterics with π-conjugation and/or inductive electronic effects to further exert control over molecular photophysical properties. The lessons gleaned from our studies of homoleptic complexes were recently extended to heteroleptic bis(phenanthrolines) featuring enhanced visible light absorption properties and long-lived room-temperature photoluminescence. Furthermore, this Account navigates the reader through our intellectual journey of decision-making, molecular and experimental design, and data interpretation in parallel with appropriate background information related to the quantitative characterization of molecular photophysics using Cu I MLCT chromophores as prototypical examples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

State Indicators for Advancing Demand Flexibility and Energy Efficiency in Buildings - Part I [Slides]

This slide deck report identifies objectives and key indicators for state activities that advance demand flexibility in buildings — legislation, utility regulatory proceedings, executive orders and programs. It also illustrates progress to date and identifies trends, gaps, and opportunities. Part I of the report focuses on (1) demand response and (2) energy efficiency targeted to reduce peak demand or integrate with demand response. This section covers building energy codes, appliance and equipment standards, resource standards, utility planning, utility programs, advanced metering infrastructure and meter data, rate design, state programs, state energy planning, and related state policies and regulations. Part II of the report addresses traditional energy efficiency indicators, including utility and state programs, codes, and standards that support annual energy savings. See the additional links for an infographic, library of cited state documents on demand flexibility, and presentation to the NASEO-NARUC Grid-Interactive Efficient Buildings Working Group.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Microreactor Core Transportation Cask Model Description for Criticality Safety Validation Basis Assessment (Rev. 1)

Criticality safety analyses are completed on transportation casks used for microreactor whole core shipment to provide examples of models and analyses to industry, regulators, and nuclear community at large to be used in verification and validation analyses of similar applications. The microreactors considered are based on a Gas-Cooled Microreactor (GCMR) and a Heat-Pipe Microreactor (HPMR), both utilize HALEU fuel in the form of TRISO particles and various other design options considered in industry microreactor designs. Variant design options of GCMR and HPMR were also investigated to provide a wider application range for each technology. Criticality safety analyses for the GCMR and HPMR packages were performed using the CSAS6 sequence of SCALE 6.3.2 with the ENDF/B-VII.1-based continuous energy neutron libraries. Different scenarios were investigated, including normal operation and water flooded conditions to represent nominal and hypothetical accident scenarios. Sensitivity and similarity analyses are also performed using the TSUNAMI sequence of SCALE 6.3.2, and the similarity analysis uses all the experiments from the ICSBEP Handbook with Intermediate and mixed Enriched Uranium (IEU) and Low Enriched Uranium (LEU) systems, together with additional experiments that are sponsored by the DNCSH program. Many experiments were found marginally similar to the GCMR and HPMR models, with similarity index (ck) values greater than 0.8 but less than 0.9. Among all the experiments analyzed, no case has a ck value greater than 0.9, indicating that additional critical experiments might be needed to further validate the criticality safety models for microreactors transport packages.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Microreactor Core Transportation Cask Model Description for Criticality Safety Validation Basis Assessment (Rev. 2)

Criticality safety analyses are completed on transportation casks used for microreactor whole core shipment to provide examples of models and analyses to industry, regulators, and nuclear community at large to be used in verification and validation analyses of similar applications. The microreactors considered are based on a Gas-Cooled Microreactor (GCMR) and a Heat-Pipe Microreactor (HPMR), both utilize HALEU fuel in the form of TRISO particles and various other design options considered in industry microreactor designs. Variant design options of GCMR and HPMR were also investigated to provide a wider application range for each technology. Criticality safety analyses for the GCMR and HPMR packages were performed using the CSAS6 sequence of SCALE 6.3.2 with the ENDF/B-VII.1-based continuous energy neutron libraries. Different scenarios were investigated, including normal operation and water flooded conditions to represent nominal and hypothetical accident scenarios. Sensitivity and similarity analyses are also performed using the TSUNAMI sequence of SCALE 6.3.2, and the similarity analysis uses all the experiments from the ICSBEP Handbook with High Enriched Uranium (HEU), Intermediate and mixed Enriched Uranium (IEU) and Low Enriched Uranium (LEU) systems. Many ICSBEP experiments were found marginally similar, with similarity index (ck) values greater than 0.8, to the GCMR and HPMR cask models, especially in flooded conditions that may be more constraining due to reduced reactivity margins. Some experiments using TRISO fuel particles and graphite moderator, including the recent THETA and Deimos experiments from LANL, together with some IRPhEP experiments, were also used for the similarity analyses. These TRISO-fueled and graphite moderated experiments behaved similarly to the GCMR models, with maximum ck value greater than 0.9, but they are less similar to the HPMR models. This observation indicates that additional critical experiments might be needed to further validate the criticality safety models, especially for heat-pipe based microreactor transport packages and for non-flooded transportation configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Rational design of Lewis base molecules for stable and efficient inverted perovskite solar cells

Lewis base molecules that bind undercoordinated lead atoms at interfaces and grain boundaries (GBs) are known to enhance the durability of metal halide perovskite solar cells (PSCs). Using density functional theory calculations, we found that phosphine-containing molecules have the strongest binding energy among members of a library of Lewis base molecules studied herein. Experimentally, we found that the best inverted PSC treated with 1,3-bis(diphenylphosphino)propane (DPPP), a diphosphine Lewis base that passivates, binds, and bridges interfaces and GBs, retained a power conversion efficiency (PCE) slightly higher than its initial PCE of ~23% after continuous operation under simulated AM1.5 illumination at the maximum power point and at ~40°C for >3500 hours. DPPP-treated devices showed a similar increase in PCE after being kept under open-circuit conditions at 85°C for >1500 hours.

14 SOLAR ENERGY↗
DOE OSTI2024

Democratizing uncertainty quantification

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulation codes. It breaks down the technical complexity of advanced UQ applications and enables separation of concerns between experts. UM-Bridge democratizes UQ by allowing effective interdisciplinary collaboration, accelerating the development of advanced UQ methods, and making it easy to perform UQ analyses from prototype to High Performance Computing (HPC) scale. In addition, we present a library of ready-to-run UQ benchmark problems, all easily accessible through UM-Bridge. These benchmarks support UQ methodology research, enabling reproducible performance comparisons. We demonstrate UM-Bridge with several scientific applications, harnessing HPC resources even using UQ codes not designed with HPC support.

Benchmarks↗
DOE OSTI2024

Real-time High-resolution X-Ray Computed Tomography

Computed Tomography (CT) serves as a key imaging technology that relies on computationally intensive filtering and back-projection algorithms for 3D image reconstruction. While conventional high-resolution image reconstruction (> 2K3) solutions provide quick results, they typically treat reconstruction as an offline workload to be performed remotely on large-scale HPC systems. The growing demand for post-construction AI-driven analytics and the need for real-time adjustments call for high-resolution reconstruction solutions that are feasible on local computing resources, i.e. a multi-GPU server at most. In this paper, we propose a novel approach that utilizes Tensor Cores to optimize image reconstruction without sacrificing precision. We also introduce a framework designed to enable real-time execution of end-to-end distributed image reconstruction in a multi-GPU environment. Evaluations conducted on a single Nvidia A100 and H100 GPU show performance improvements of 1.91 × and 2.15 × compared to highly optimized production libraries. Furthermore, our framework, when deployed on 8-card Nvidia A100 GPU system, demonstrates the ability to reconstruct real-world datasets into 20483 volumes (32 GB) in slightly more than one minute and 40963 volumes (256 GB) in 7 minutes.

Wu, Du↗
DOE OSTI2020

Parallel algorithms for finding connected components using linear algebra

Finding connected components is one of the most widely used operations on a graph. Optimal serial algorithms for the problem have been known for half a century, and many competing parallel algorithms have been proposed over the last several decades under various different models of parallel computation. This paper presents a class of parallel connected-component algorithms designed using linear-algebraic primitives. These algorithms are based on a PRAM algorithm by Shiloach and Vishkin and can be designed using standard GraphBLAS operations. Here, we demonstrate two algorithms of this class, one named LACC for Linear Algebraic Connected Components, and the other named FastSV which can be regarded as LACC’s simplification. With the support of the highly-scalable Combinatorial BLAS library, LACC and FastSV outperform the previous state-of-the-art algorithm by a factor of up to 12x for small to medium scale graphs. For large graphs with more than 50B edges, LACC and FastSV scale to 4K nodes (262K cores) of a Cray XC40 supercomputer and outperform previous algorithms by a significant margin. This remarkable performance is accomplished by (1) exploiting sparsity that was not present in the original PRAM algorithm formulation, (2) using high-performance primitives of Combinatorial BLAS, and (3) identifying hot spots and optimizing them away by exploiting algorithmic insights.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Concurrent Relaxation through Accelerated Deep Learning

CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics codes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may select the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a pretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.

Zieb, KristoferJ.↗
DOE OSTI2022

Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems

Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes without flowing groundwater. While detailed simulation tools for subsurface heat and mass transfer exist, these fall short in simulating above-surface energy systems. To support the design and operation of such systems, the study developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the subsurface. For the first, it uses the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, it uses the TOUGH simulator. The TOUGH family of codes can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. The study validated the coupled modeling approach by comparing the simulation results with one from the g-function based ground response model. It then looked into effects when the water table and the regional groundwater flow are considered in the ground, from the perspective of heat exchange between borehole and ground, and the electrical consumption of the district heating and cooling systems. To access the simulation models, please find the links in the submission: -- For coupled approach validation: see model Buildings.Fluid.Geothermal.Borefields.Examples.BorefieldsWithTough and Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from the "Modelica Building Library" resource, branch issue1495_tough_interface, commit a2667c0. -- For the study of the effect of water table: see model Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO, commit 760de49. -- For the study of the effect of regional groundwater flow: see Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO_3D, commit c2a2d2a. The coupling interface script "GrounResponse.py" can be found from the above links in the folder Buildings/Resources/Python-Sources. Also, the needed files for TOUGH simulation are in the folder Buildings/Resources/Python-Sources/ToughFiles that can be accessed through the above links. A brief description of these files is given below; detailed specifications for the first three files may be found in the TOUGH3 Users Guide (Jung et al., 2018) https://tough.lbl.gov/documentation/tough-manuals/. (1) INCON - initial conditions for each grid block (2) INFILE - main input file with material properties and control parameters (3) MESH - description of the computational grid (4) readsave - Modelica/TOUGH interface program: read the final output of TOUGH simulation after TOUGH time step and prepare for transfer to Modelica for next Modelica time step (5) readsave.inp - input parameters for program readsave (6) writeincon - Modelica/TOUGH interface program: write the output of Modelica after Modelica time step and prepare for transfer to TOUGH as initial conditions for the next TOUGH step (7) writeincon.inp - input parameters for program writeincon

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Coupling subsurface and above-surface models for optimizing the design of borefields and district heating and cooling systems in the presence of varying water-table depth. In: Proceedings, 46th Workshop on Geothermal Reservoir Engineering

Dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes, without flow of groundwater. On the other hand, detailed simulation tools for subsurface heat and mass transfer exist, but these fall short in simulating above-surface energy systems. To support the design and operation of such systems, we have developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the ground. For the first, we use the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, we use the TOUGH simulator. TOUGH can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. In previous work, we described the coupling of these software packages, including how time-dependent boundary conditions for the borehole walls are synchronized for use in Modelica and TOUGH. We verified that the coupled Modelica/TOUGH code produced consistent results with the original Modelica code for an idealized problem in which heat transfer was purely by conduction in a uniform geologic medium. Here, we examine less idealized problems for which TOUGH’s advanced capabilities for modeling fluid flow are required. The first problem has a shallow vadose zone, and the second problem has a thicker vadose zone with a water-table depth that varies in time, which requires a fine vertical grid discretization for the TOUGH model.

Doughtry, Christine↗
DOE OSTI2024

QSpace - An open-source tensor library for Abelian and non-Abelian symmetries

This is the documentation for the tensor library QSpace (v4.0), a toolbox to exploit ‘quan tum symmetry spaces’ in tensor network states in the quantum many-body context. QSpace permits arbitrary combinations of symmetries including the abelian symmetries $\mathbb{Z}_n$ and U(1), as well as all non-abelian symmetries based on the semisimple classical Lie algebras: A n , B n , C n , and D n , or respectively, the special unitary group SU(n), the odd orthogonal group SO(2n+1), the symplectic group Sp(2n), and the even orthogonal group SO(2n). The code (C++ embedded via the MEX interface into Matlab) is available open source as of QSpace v4.0 on bitbucket under the Apache 2.0 license. QSpace is designed as a bottom-up approach for non-abelian symmetries. It starts from the defining representation and the respective Lie algebra. By explicitly comput ing and tabulating generalized Clebsch-Gordan coefficient tensors, QSpace is versatile in the type of operations that it can perform across all symmetries. At the level of an ap plication, much of the symmetry-related details are hidden within the QSpace C++ core libraries. Hence when developing tensor network algorithms with QSpace, these can be coded (nearly) as if there are no symmetries at all, despite being able to fully exploit general non-abelian symmetries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗
DOE OSTI2021

SCALE 6.2.4 Validation for Light Water Reactor Decay Heat Analysis

Energy release from the decay of radionuclides in nuclear fuel after its discharge from reactor is a critical parameter for design, safety, and licensing analyses of used nuclear fuel storage, transportation, and repository systems. Well-validated computational tools and nuclear data are essential for decay heat prediction. This paper summarizes the validation of the SCALE nuclear analysis code system version 6.2.4, used with ENDF/B-VII.1 libraries, for decay heat analysis of light water reactor used fuel. The experimental data used for validation include full-assembly decay heat measurements that cover assembly burnups of 5 to 51 GWd/tonne U, cooling times after discharge in the 2- to 27-year range, and initial fuel enrichments up to 4 wt% 235U. The comparison between calculated (C) and experimental (E) decay heat showed very good agreement, with an average C/E over all considered measurements of 1.006 (σ = 0.016) for pressurized water reactor and 0.984 (σ = 0.077) for boiling water reactor assembly measurements. The effect of using assembly-average versus axially varying modeling data on the calculated decay heat, important to thermal analyses for used fuel transportation and storage systems, is discussed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Generic National Nuclear Forensics Library Implementation

This document provides instructions for the database implementation for national nuclear forensic library (NNFL) using a relational database. While there are many software options that can be used to implement an NNFL database, in this document we reference an Oracle database for the implementation. The principles related here can be applied to any relational database structure. The design revolves around two main types of data: Samples and Results. Samples are materials or descriptions of materials; results are the results of analyses of those samples. All additional tables exist as a result of the normalization process. The remaining tables/entities have keys that are referenced by the Result/Sample tables via foreign key constraints. This allows for the enforcement of different relationships between the tables such as one-to-one, one-to-many, many-to-many. This process helps to ensure that valid data is entered, optimizes database performance and avoids data redundancies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗
DOE OSTI2024

Adaptive Mesh Refinement Simulations for Turbulent Reacting Flow

With the increased availability of exascale computing hardware, detailed simulations of realistic devices can be performed at practically relevant time and length scales. Insights into the multiscale driving mechanisms in compressible reacting flow systems with complex geometry, such as combustors, can be used for design optimization and technology improvements. However, to effectively perform these simulations, advanced numerical algorithms must be used to maintain solution accuracy without incurring undue computational costs. PeleC, part of the Pele suite of codes, leverages block-structured adaptive mesh refinement (AMR) through the AMReX library to capture fine-scale flow features in compressible reacting flows. In this talk, we discuss recent improvements to the numerical algorithms, particularly in regard to describing flows at complex boundary structures, and PeleC's performance on exascale computing hardware. We will demonstrate that PeleC is well-suited for modern, extreme-scale, heterogenous compute platforms.

combustion↗