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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Benchmark study of a new simplified DFN model for shearing of intersecting fractures and faults

It is challenging to quantitatively predict shearing of intersecting fractures/faults because of dynamic frictional contacts accompanied by possible nonlinear rock deformation. To address such challenges, a new conceptual model—the simplified DFN model—was proposed and validated by Hu et al. 46 to use major paths (MPs) to represent complicated DFNs for calculation of shearing. In this work, we conducted a benchmark study for three examples that involve different levels of complexity of intersecting fractures, and correspondingly different numbers of MPs. The codes and software that were used in the benchmark cover a range of continuum, discontinuum and hybrid numerical methods: NMM (LBNL), FLAC3D (LBNL), GBDEM (KIGAM), FRACOD (DynaFrax), and CASRock (CAS). The general consistency between DFN and MP cases as predicted by all the codes/software demonstrates that major paths can be used to simplify the geometry of DFNs in a wide range of software. Disagreement in results made by some software and potential future improvements are discussed. We show that (1) shearing of one or multiple major fractures can be reduced if there are multiple smaller intersecting fractures in that area, which is a useful basis for understanding and controlling induced seismicity and merits further analysis, and (2) the agreement achieved in the benchmark examples provide confidence that the simplified DFN model is a promising conceptual model that can be used for different types of numerical approaches and software for simplifying the analysis of the shearing of intersecting fractures and faults.

58 GEOSCIENCES↗
NASA NTRS2017

Benchmarking the Collocation Stand-Alone Library and Toolkit (CSALT)

This paper describes the processes and results of Verification and Validation (VV) efforts for the Collocation Stand Alone Library and Toolkit (CSALT). We describe the test program and environments, the tools used for independent test data, and comparison results. The VV effort employs classical problems with known analytic solutions, solutions from other available software tools, and comparisons to benchmarking data available in the public literature. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results for a broad range of problems, and detailed comparisons for selected problems.

trajectory optimization↗
DOE OSTI2020

Design and Operability of a Pressurized Oxy Combustion System

Fossil fuel powers more than two-thirds of the world’s electricity, a significant share of which is derived from coal power plants. Despite coal being an abundant and energy-rich fuel, the major halt to its progress is greenhouse gas emissions. Pressurized oxy-combustion cycles can achieve theoretically high thermal efficiencies along with a 90% carbon capture rate. Additionally, the high energy density allows smaller turbomachinery and save capital cost. Thus, the primary objective of this dissertation is to present the design and operability of a pressurized oxy-combustor system. The initial part of the dissertation investigates different thermodynamic cycles and presents a model that can be adapted for existing power plants. The thermodynamic model will be used in the later part to design the proposed combustor. The two cycles analyzed are ENEL and TIPS. This study focuses on qualitative analyses of the cycles using a commercially available software called Aspen Plus®. A detailed benchmark study has been performed to validate the modeling process. ENEL and TIPS cycles are designed in the software, adopting the same principles. Recirculation ratio and pressures are varied to find the efficiency range of the cycles. Power calculations are done to find overall and net efficiency for a fixed recirculation ratio. The efficiencies of the cycles are compared to select an optimum cycle. A recirculation ratio of 50% is selected for implementation. The comparison shows that ENEL is marginally efficient over TIPS, at the cost of a pressure difference of about 70bars. Technology Readiness Level analysis is performed to present the availability of the specialized equipment for the cycles. From the TRL analysis, it is seen that the cost and availability of high viii pressure equipment surmount the edge of TIPS over ENEL. Thus, ENEL is chosen as the better cycle for investigating a scaled experiment considering efficiency and viability. The later part of the dissertation focuses on developing the combustor's design for a pressurized oxy-combustion cycle. The proposed combustor is a powerhead-mounted design aimed to produce 1MW of thermal outputThe different aspects of the design of a down-fired pressurized swirl combustor are presented in this dissertation.

Chowdhury, Mehrin↗
NASA NTRS2017

Benchmarking the Collocation Stand-Alone Library and Toolkit (CSALT)

This paper describes the processes and results of Verification and Validation (V&V) efforts for the Collocation Stand Alone Library and Toolkit (CSALT). We describe the test program and environments, the tools used for independent test data, and comparison results. The V&V effort employs classical problems with known analytic solutions, solutions from other available software tools, and comparisons to benchmarking data available in the public literature. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results for a broad range of problems, and detailed comparisons for selected problems.

optimal control↗
DOE OSTI2025

Binder-benchmarking

SAND2025-07593O Binder-benchmarking evaluates the speed and memory impacts of C++, Python, and Matlab code binders. As a repository, it provides a way to locally run computation-based and memory-based benchmark suites on pybind11 and nanobind-based code in a Docker image. The software runs simple-speed and memory benchmarks on primitive navigation and integration exemplar algorithms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Walker II, Michael [Sandia National Lab. (SNL-CA),↗
DOE OSTI2025

Generalizable, fast, and accurate DeepQSPR with fastprop

Abstract Quantitative Structure–Property Relationship studies (QSPR), often referred to interchangeably as QSAR, seek to establish a mapping between molecular structure and an arbitrary target property. Historically this was done on a target-by-target basis with new descriptors being devised to specifically map to a given target. Today software packages exist that calculate thousands of these descriptors, enabling general modeling typically with classical and machine learning methods. Also present today are learned representation methods in which deep learning models generate a target-specific representation during training. The former requires less training data and offers improved speed and interpretability while the latter offers excellent generality, while the intersection of the two remains under-explored. This paper introduces , a software package and general Deep-QSPR framework that combines a cogent set of molecular descriptors with deep learning to achieve state-of-the-art performance on datasets ranging from tens to tens of thousands of molecules. provides both a user-friendly Command Line Interface and highly interoperable set of Python modules for the training and deployment of feedforward neural networks for property prediction. This approach yields improvements in speed and interpretability over existing methods while statistically equaling or exceeding their performance across most of the tested benchmarks. is designed with Research Software Engineering best practices and is free and open source, hosted at github.com/jacksonburns/fastprop.

Burns, Jackson W. (ORCID:0000000206579426)↗
DOE OSTI2025

Benchmark Tracking System for Performance Monitoring

Benchmarking is essential for high-performance software development, particularly for monitoring performance across code iterations. This project focused on enhancing the benchmarking process for Lamellar, an asynchronous runtime for High-Performance Computing (HPC) systems developed at Pacific Northwest National Laboratory. Prior to this work, benchmark results were difficult to track and compare across code versions, presenting significant challenges in identifying performance regressions and long-term trends. The primary objective was to establish a systematic, reproducible approach for measuring performance and detecting regressions following code commits. Our methodology involved three key components: standardizing benchmark outputs, implementing data versioning, and developing analysis tools. We standardized the benchmark output format to JSON Line records containing specific fields (execution time, hardware specifications, and environmental variables). To address data management challenges, we evaluated several options and eventually chose a git repository dedicated to benchmark data. We developed a suite of Python tools that processed benchmark results, enriched them with metadata, and facilitated search in the repository. The resulting system enables more efficient filtering and comparison of performance metrics across commit histories, hardware configurations, and benchmark variants through a unified query interface. Our implementation reduces computational overhead by first checking for existing results through configuration matching before initiating new benchmark runs, thereby conserving resources. The system has been validated by Lamellar developers. It organizes results by benchmark type and build configurations for efficient retrieval. Future developments include a planned Large Language Model interface for predicting benchmark performance, incorporating the criterion package for statistical analysis, which will enable automated detection of statistically significant performance changes, and integration with continuous integration pipelines. Despite these enhancements being reserved for future work, this project has successfully provided the Lamellar development team with a framework for maintaining consistent performance standards and identifying optimization opportunities across workloads and hardware environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Fractional occupation numbers and self-interaction correction-scaling methods with the Fermi-Löwdin orbital self-interaction correction approach

In this work, we present a new assessment of the Fermi-Löwdin orbital self-interaction correction (FLO-SIC) approach with an emphasis on its performance for predicting energies as a function of fractional occupation numbers (FONs) for various multielectron systems. Our approach is implemented in the massively parallelized NWChem quantum chemistry software package and has been benchmarked on the prediction of total energies, atomization energies, and ionization potentials of small molecules and relatively large aromatic systems. Within our study, we also derive an alternate expression for the FLO-SIC energy gradient expressed in terms of gradients of the Fermi-orbital eigenvalues and revisit how the FLO-SIC methodology can be seen as a constrained unitary transformation of the canonical Kohn–Sham orbitals. Finally, we conclude with calculations of energies as a function of FONs using various SIC-scaling methods to test the limits of the FLO-SIC formalism on a variety of multielectron systems. We find that these relatively simple scaling methods do improve the prediction of total energies of atomic systems as well as enhance the accuracy of energies as a function of FONs for other multielectron chemical species.

fractional occupation number↗
DOE OSTI2025

Development, validation, and verification of multi-pass thermo-mechanical welding simulations using the open-source MOOSE framework: NeT TG4 benchmark weldment

This study develops and validates a sequentially coupled thermo-mechanical welding simulation for the three-pass 316L stainless steel NeT TG4 benchmark weldment using the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) and the Nuclear Engineering Material model Library (NEML). A diffused ellipsoidal heat source was calibrated against thermocouple data and weld macrographs to accurately model the fusion zone geometry and transient thermal fields. Material hardening is represented using the Lemaitre-Chaboche mixed isotropic-kinematic hardening model, while four annealing models - no annealing, single-stage at 1050 °C and 1300 °C, and two-stage at 800 °C/1300 °C - were implemented to assess the impact of annealing models on the accuracy of the predicted welding-induced plasticity, distortions, and residual stresses. The predictions were validated against experimental measurements and benchmarked against results from commercial software, demonstrating that thermo-mechanical MOOSE welding simulations achieve comparable accuracy with enhanced computational efficiency. This work highlights the potential of using open-source finite element frameworks like MOOSE for advanced manufacturing simulations.

Ji, Wendy [Australian Nuclear Science and Technolo↗
DOE OSTI2026

Reassessment of PHDS Fulcrum40h High Purity Germanium (HPGe) Detector System Performance

This report presents a comprehensive evaluation of the updated PHDS Fulcrum40h High Purity Germanium (HPGe) detector system, benchmarking its performance, usability, and software capabilities against the current National Nuclear Security Administration (NNSA) Nuclear Emergency Support Team (NEST) HPGe Detector System Requirements Document. Systematic measurements were conducted using a single Fulcrum40h detector to assess key parameters including gamma efficiency and resolution, neutron detection efficiency, gamma pulse-pileup response, and gamma-to-neutron crosstalk. The Fulcrum40h system, acquired in August 2022, has undergone recent updates by PHDS to address deficiencies identified following the initial NEST requirements release. The results provide critical insights into the detector’s operational capabilities and compliance with NNSA NEST standards.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

Technology Transfer Plan: LuNaMaps Project

The main contribution of this project is the combined knowledge of terrain relative navigation experts and lunar scientists who are familiar with both the lunar orbital imagery and the instruments that collected the data as well as how a TRN system utilizes map data. This knowledge comes in the form of published technical papers, benchmark map data sets, and software tools that can help others automate the process of creating the necessary maps for their own landing sites in the future. This document represents the project's plans to share all the lessons learned, processes developed, and applicable software tools with the public.

optical navigation↗
NASA NTRSDate not supplied

Tutorial on LuNaMaps Developed Tools andProcesses for Mapping the Lunar Surface

The main contribution of this project is the combined knowledge of terrain relative navigation experts and lunar scientists who are familiar with both the lunar orbital imagery and the instruments that collected the data as well as how a TRN system utilizes map data. This knowledge comes in the form of published technical papers, benchmark map data sets, and software tools that can help others automate the process of creating the necessary maps for their own landing sites in the future. This presentation provides a brief overview of the tools and processes developed by the project.

optical navigation↗
DOE OSTI2021

Sensitivity-based Similarity Metrics for New Experiment Design Optimization

The nuclear data used in advanced reactor simulations requires validation. Data from nuclear criticality experiments can provide this validation. New nuclear criticality experiment design requires extensive knowledge and expert judgement such that the experimental design parameters are selected in such a way to keep the experiment subcritical. To aide in this experimental design process, professionals can utilize sensitivity and uncertainty analysis. Sensitivity and uncertainty analysis relies on matching new application experiments with currently existing benchmark experiments. Currently, there is functionality in the Whisper 1.1 software package to calculate a similarity metric based on neutron multiplication factor sensitivity coefficients between a new application designed by the user and existing International Criticality Safety Benchmark Experiment Project (ICSBEP) benchmarks. The Whisper 1.1 software package is included in Monte Carlo N-Particle ® Code Version 6.21 (MCNP ® 6.2). This work is geared toward expanding this capability to new similarity metrics based on beta-effective sensitivity coefficients and reactivity coefficient sensitivity coefficients. While the investigation of these sensitivity coefficients is presented in detail in separate works at this same conference, this work will be primarily focused on studying the similarity metrics in more detail. These similarity metrics will then be incorporated into the optimization algorithms used for experiment design in EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data), which is a Los Alamos National Laboratory (LANL) project designed to constrain nuclear data of interest, such that adjustments can be made to possible inaccuracies. A more detailed optimization can be subsequently performed by breaking down these similarity metrics by isotope, reaction, and energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

Defect measurement and analysis of JPL ground software: a case study

Ground software systems at JPL must meet high assurance standards while remaining on schedule due to relatively immovable launch dates for spacecraft that will be controlled by such systems. Toward this end, the Software Quality Improvement (SQI) project's Measurement and Benchmarking (M&B) team is collecting and analyzing defect data of JPL ground system software projects to build software defect prediction models. The aim of these models is to improve predictability with regard to software quality activities. Predictive models will quantitatively define typical trends for JPL ground systems as well as Critical Discriminators (CDs) to provide explanations for atypical deviations from the norm at JPL. CDs are software characteristics that can be estimated or foreseen early in a software project's planning. Thus, these CDs will assist in planning for the predicted degree to which software quality activities for a project are likely to deviation from the normal JPL ground system based on pasted experience across the lab.

defects↗
DOE OSTI2026

Intern-Artificial Intelligence Benchmarking

Benchmarks provide a standardized method for evaluating different AI models, enabling reproducibility and comparison between models, and facilitating scientific progress. As AI models continue to develop rapidly, incorporating new datasets, capabilities, and architectures becomes more complicated. Therefore, the current static benchmarks become increasingly irrelevant. The MLCommons team argues that to make AI benchmarks more relevant, it involves making the benchmarks themselves more dynamic, as well as technical innovations that make it easier for scientists and researchers at all levels to use and contribute to the benchmarks. The current progress in technical innovation is a software that allows for a detailed view of a collection of AI benchmarks to be output in various formats that are easily readable and accessible.

Krishnan, Anjay [Fermilab]↗
NASA NTRS2019

The Arctic-Boreal vulnerability experiment model benchmarking system

NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) integrates field and airborne data into modeling and synthesis activities for understanding Arctic and Boreal ecosystem dynamics. The ABoVE Benchmarking System (ABS) is an operational software package to evaluate terrestrial biosphere models against key indicators of Arctic and Boreal ecosystem dynamics, i.e.: carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance. The ABS utilizes satellite remote sensing data, airborne data, and field data from ABoVE as well as collaborating research networks in the region, e.g.: the Permafrost Carbon Network, the International Soil Carbon Network, the Northern Circumpolar Soil Carbon Database, AmeriFlux sites, the Moderate Resolution Imaging Spectroradiometer, the Orbiting Carbon Observatory 2, and the Soil Moisture Active Passive mission. The ABS is designed to be interactive for researchers interested in having their models accurately represent observations of key Arctic indicators: a user submits model results to the system, the system evaluates the model results against a set of Arctic-Boreal benchmarks outlined in the ABoVE Concise Experiment Plan, and the user then receives a quantitative scoring of model strengths and deficiencies through a web interface. This interactivity allows model developers to iteratively improve their model for the Arctic-Boreal Region by evaluating results from successive model versions. We show here, for illustration, the improvement of the Lund–Potsdam–Jena-Wald Schnee und Landschaft (LPJwsl) version model through the ABoVE ABS as a new permafrost module is coupled to the existing model framework. The ABS will continue to incorporate new benchmarks that address indicators of Arctic-Boreal ecosystem dynamics as they become available.

ABoVE↗
DOE OSTI2025

qcal v0.0.1

qcal is a software package for calibration, characterization, and benchmarking of quantum gates. It was developed to operate full-stack superconducting quantum systems at the Advanced Quantum Testbed.

Hashim, Akel [Lawrence Berkeley National Laborator↗