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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Studying excited-state-specific perturbation theory on the Thiel set

Here, we explore the performance of a recently introduced N 5 -scaling excited-state-specific second order perturbation theory (ESMP2) on the singlet excitations of the Thiel benchmarking set. We find that, without regularization, ESMP2 is quite sensitive to π system size, performing well in molecules with small π systems but poorly in those with larger π systems. With regularization, ESMP2 is far less sensitive to π system size and shows a higher overall accuracy on the Thiel set than CC2, equation of motion-coupled cluster with singles and doubles, CC3, and a wide variety of time-dependent density functional approaches. Unsurprisingly, even regularized ESMP2 is less accurate than multi-reference perturbation theory on this test set, which can, in part, be explained by the set’s inclusion of some doubly excited states but none of the strong charge transfer states that often pose challenges for state-averaging. Beyond energetics, we find that the ESMP2 doubles norm offers a relatively low-cost way to test for doubly excited character without the need to define an active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Direct simulation Monte Carlo analysis on parallel processors

A method is presented for executing a direct simulation Monte Carlo (DSMC) analysis using parallel processing. The method is based on using domain decomposition to distribute the work load among multiple processors, and the DSMC analysis is performed completely in parallel. Message passing is used to transfer molecules between processors and to provide the synchronization necessary for the correct physical simulation. Benchmark problems are described for testing the method and results are presented which demonstrate the performance on two commercially available multicomputers. The results show that reasonable parallel speedup and efficiency can be obtained if the problem is properly sized to the number of processors. It is projected that with a massively parallel system, performance exceeding that of current supercomputers is possible.

Wilmoth, Richard G.↗
DOE OSTI2025

GPU-accelerated kinetic Hall thruster simulations in WarpX

Abstract Two-dimensional (axial-azimuthal) simulations of a Hall thruster are performed using the open-source particle-in-cell code WarpX. The simulation conditions are chosen to match those of the axial-azimuthal benchmark first reported by Charoy et al. in 2019. A range of numerical and solver parameters is investigated in order to find those which yield the best performance. It is found that WarpX completes the benchmark case in 3.8 days on an Nvidia V100 GPU, and in as low as 1.5 days on a more recent Nvidia H100 GPU. Of the numerical parameters investigated, it is determined that the field-solve tolerance and particle resampling thresholds have the largest effect on the simulation wall time and that particle resampling may artificially widen electron velocity distribution functions, leading to unphysical heating. A semi-implicit scheme for the electrostatic field solve is tested and is found to produce results consistent to within 10% of the benchmark in less than twelve hours. The scaling properties of the electrostatic solver to multiple GPUs are also assessed on a uniform plasma test problem. The results of this work are discussed in the context of advancements in GPU hardware and the suitability of kinetic Hall thruster simulations for engineering applications.

Marks, Thomas A.↗
NASA NTRS2024

Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region

Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic‐boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8‐day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re‐parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.

land data assimilation↗
NASA NTRS2006

Analytical Ion Thruster Discharge Performance Model

A particle and energy balance model of the plasma discharge in magnetic ring-cusp ion thrusters has been developed. The model follows the original work of Brophy in the development of global 0-D discharge models that utilize conservation of particles into and out of the thruster and conservation of energy into the discharge and out of the plasma in the form of charged particles to the walls and beam and plasma radiation. The present model is significantly expanded over Brophy's original work by including self-consistent calculations of the internal neutral pressure, electron temperature, primary electron density, electrostatic ion confinement (due to the ring-cusp fields), plasma potential, discharge stability, and time dependent behavior during recycling. The model only requires information on the thruster geometry, ion optics performance and electrical inputs such as discharge voltage and currents, etc. to produce accurate performance curves of discharge loss versus mass utilization efficiency. The model has been benchmarked against the NEXIS Laboratory Model (LM) and Development Model (DM) thrusters, and successfully predicts the thruster discharge loss as a function of mass utilization efficiency for a variety of thrusters. The discharge performance model will be presented and results showing ion thruster performance and stability given.

discharge chambers↗
NASA NTRS1994

Performance Metrics for Monitoring Parallel Program Executions

Existing tools for debugging performance of parallel programs either provide graphical representations of program execution or profiles of program executions. However, for performance debugging tools to be useful, such information has to be augmented with information that highlights the cause of poor program performance. Identifying the cause of poor performance necessitates the need for not only determining the significance of various performance problems on the execution time of the program, but also needs to consider the effect of interprocessor communications of individual source level data structures. In this paper, we present a suite of normalized indices which provide a convenient mechanism for focusing on a region of code with poor performance and highlights the cause of the problem in terms of processors, procedures and data structure interactions. All the indices are generated from trace files augmented with data structure information.. Further, we show with the help of examples from the NAS benchmark suite that the indices help in detecting potential cause of poor performance, based on augmented execution traces obtained by monitoring the program.

Sarukkai, Sekkar R.↗
DOE OSTI2026

Benchmarking soil moisture and its relationship to ecohydrologic variables in Earth System Models

Soil moisture (SM) is a key regulator of ecosystem biogeophysics, influencing plant water relations and land-atmosphere energy exchanges. We evaluate the representation of SM in 16 Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) using the International Land Model Benchmarking (ILAMB) framework, focusing on surface (0–5, 0–10 cm) and rootzone (0–100 cm) depths, as well as key ecohydrological variables like gross primary productivity (GPP), leaf area index (LAI), and evapotranspiration (ET), and their coupling. Models are benchmarked against multiple observational and assimilated datasets to assess both state variables and cross-variable relationships. Surface SM is generally well represented (r > 0.87), while rootzone SM variability is systematically overestimated (normalized standard deviation > 1). ET shows strong agreement with observations (r > 0.9), whereas GPP and LAI exhibit larger inter-model spread. Skill in individual variables does not guarantee realistic SM–ecohydrology coupling, which varies strongly across models and depends on the reference dataset. Köppen-based regional analyses reveal strong regime dependence, with several models performing well in Tropical and Temperate regions but degrading in Continental (high-latitude) zones. Across both global and regional benchmarks, models cluster by land surface framework, indicating that structural choices in soil hydrology and soil–plant coupling exert a first-order control on performance. These results provide process-relevant benchmarks and suggest that improving the representation of vertical soil structure, rooting depth distributions, and soil–plant hydraulic coupling will be central to advancing soil moisture realism in next-generation Earth system models.

CMIP6↗
NASA NTRS1991

Evaluation of telerobotic systems using an instrumented task board

An instrumented task board was developed at NASA Marshall Space Flight Center (MSFC). An overview of the task board design, and current development status is presented. The task board was originally developed to evaluate operator performance using the Protoflight Manipulator Arm (PFMA) at MSFC. The task board evaluates tasks for Orbital Replacement Unit (ORU), fluid connect and transfers, electrical connect/disconnect, bolt running, and other basic tasks. The instrumented task board measures the 3-D forces and torques placed on the board, determines the robot arm's 3-D position relative to the task board using IR optics, and provides the information in real-time. The PFMA joint input signals can also be measured from a breakout box to evaluate the sensitivity or response of the arm operation to control commands. The data processing system provides the capability for post processing of time-history graphics and plots of the PFMA positions, the operator's actions, and the PFMA servo reactions in addition to real-time force/torque data presentation. The instrumented task board's most promising use is developing benchmarks for NASA centers for comparison and evaluation of telerobotic performance.

Carroll, John D.↗
DOE OSTI2024

Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region

Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic-boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8-day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. Here, to further reduce the remaining bias in GPP after LAI bias correction, we re-parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.

58 GEOSCIENCES↗
DOE OSTI2020

Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool

Due to the sheer volume of data it is typically impractical to analyze the detailed performance of an HPC application running at-scale. While conventional small-scale benchmarking and scaling studies are often sufficient for simple applications, many modern workflow-based applications couple multiple elements with competing resource demands and complex inter-communication patterns for which performance cannot easily be studied in isolation and at small scale. This work discusses Chimbuko, a performance analysis framework that provides real-time, in situ anomaly detection. By focusing specifically on performance anomalies and their origin (aka provenance), data volumes are dramatically reduced without losing necessary details. To the best of our knowledge, Chimbuko is the first online, distributed, and scalable workflow-level performance trace analysis framework. We demonstrate the tool's usefulness on Oak Ridge National Laboratory's Summit system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Depletion benchmark for a high-assay low-enriched uranium fuel experiment in the advanced test reactor

Reactor physics depletion benchmarks for high-assay low-enriched uranium (HALEU) fuel are limited in number. In particular, there is limited data for HALEU benchmarks for U-10Mo (uranium-10% molybdenum) plate fuel that is being developed for use in the United States’ high performance research reactors including the Advanced Test Reactor (ATR), Advanced Test Reactor Critical Facility (ATR-C), High Flux Isotope Reactor (HFIR), Massachusetts Institute of Technology Reactor (MITR), University of Missouri Research Reactor (MURR), National Bureau of Standards Reactor (NBSR). These six reactors currently operate with highly enriched uranium dispersed fuel in an aluminum matrix. In support of conversion to a HALEU fuel, qualification of U-10Mo formed into a monolithic foil is being performed. Fuel qualification involves irradiating fuel specimens in the ATR. The irradiation tests provide an opportunity to benchmark depletion capabilities of reactor physics codes in support of the ATR operation, as well as develop benchmarks that can be used by other institutions to benchmark other reactor physics codes. This paper documents the development of a benchmark model of the irradiation of the ATR Full-size plate In center flux trap Position 7 (AFIP-7) experiment using the depletion codes MC21 and Advanced Dimensional Depletion for Engineering of Reactors (ADDER).

Nielsen, Joseph W. [Idaho National Laboratory (INL↗
DOE OSTI2025

Methods in PES-Learn: Direct-Fit Machine Learning of Born–Oppenheimer Potential Energy Surfaces

The release of PES-L EARN version 1.0 as an open-source software package for the automatic construction of machine learning models of semi-global molecular potential energy surfaces (PESs) is presented. Improvements to PES-L EARN ’s interoperability are stressed with new Python API that simplifies workflows for PES construction via interaction with QCSchema input and output infrastructure. In addition, a new machine learning method is introduced to PES-L EARN : kernel ridge regression (KRR). The capabilities of KRR are emphasized with examination of select semi-global PESs. All machine learning methods available in PES-L EARN are benchmarked with benzene and ethanol datasets from the rMD17 database to illustrate PES-L EARN ’s performance ability. Fitting performance and timings are assessed for both systems. Finally, the ability to predict gradients with neural network models is presented and benchmarked with ethanol and benzene. PES-L EARN is an active project and welcomes community suggestions and contributions.

kernel ridge regression↗
DOE OSTI2022

Efficient high-fidelity TRISO statistical failure analysis using Bison: Applications to AGR-2 irradiation testing

The ability of tri-structural isotropic (TRISO) fuel to contain fission products is largely dictated by the quality of the manufacturing process, since most of the fission product release is expected to occur due to coating layer failure in a small number of particles containing defects. The Bison fuel performance code has capabilities to predict failure in individual particles, accounting for the presence of defects, and to apply statistical analysis methods to compute the probability of failure in a set of fuel particles. Bison has recently undergone significant development both to improve its physical representations of fuel particle behavior and to improve the efficiency of its statistical failure calculations. Physical model improvements include new capabilities to account for the pressure generated by fission gases on inner pyrolytic carbon (IPyC) crack surfaces and to use local material coordinate orientation to accurately incorporate the anisotropy in the material properties in aspherical particles. To improve statistical modeling efficiency, a direct integration approach which involves directly integrating the failure probability function associated with statistically varying parameters has been developed. The direct integration approach is much more efficient than the Monte Carlo (MC) schemes commonly employed, and allows Bison to directly run high-dimensional fuel performance models, which improves the accuracy of failure probability calculations. Finally, a set of benchmark problems is considered here to compare the MC and direct integration approaches, and a statistical failure analysis of compacts in the Advanced Gas Reactor (AGR)-2 experiments is performed using the direct integration approach.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An Ensemble Approach to Computationally Efficient Radiological Anomaly Detection and Isotope Identification

Radiological source search is a challenging task involving detection and identification of weak sources in a constantly changing radiological background. As of now, many radiological source detection algorithms have been proposed; however, their computational complexity, and hence reliance on power intensive processing units inhibit low-power applications of radiological source search systems. In this work, we introduce the anomaly filter (AF) algorithm; a computationally light, yet effective time-series source detection algorithm based on exponential weighted moving average (EWMA) and Poisson deviance statistics. Then, we demonstrate that the proposed algorithm can be used in ensemble with other more computationally intensive source detection and identification algorithms to achieve both increased detection performance and reduced power consumption. The proposed AF algorithm and the ensemble algorithms were thoroughly benchmarked against several existing source detection and identification algorithms. The results show that the AF algorithm outperforms existing conventional source detection algorithms, and the ensemble approach improves the overall performance of existing source detection and isotope identification algorithms. Furthermore, the AF algorithm and the Non-negative Matrix Factorization approach based source identification (NMF-ID) algorithm were combined and implemented on a singleboard microcontroller and the power consumption was measured. This ensemble algorithm reduced the power consumption of the NMF-ID algorithm almost by a factor of 100, while improving the detection performance of the overall system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Studying the Random Number Generators in MCNP6 using an Analytic Benchmark

An analytic solution to a previously studied toy problem is derived and used as a code verification benchmark. Using various Random Number Generators (RNGs) in MCNP6, including the newest SFC64 RNG available in MCNP6.3.1, and their various properties (e.g., RNG stride), we show how these RNGs perform and how to correct or workaround potential issues with respect to the analytic benchmark problem.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Particle Engulfment and Pushing By Solidifying Interfaces - Recent Theoretical and Experimental Developments

The objective of the work on Particle Engulfment and Pushing by Solidifying Interfaces (PEP) include: 1) to obtain fundamental understanding of the physics of particle pushing and engulfment, 2) to develop mathematical models to describe the phenomenon, and 3) to perform critical experiments in the microgravity environment of space to provide benchmark data for model validation. Successful completion of this project will yield vital information relevant to a diverse area of terrestrial applications. With PEP being a long term research effort, this report will focus on advances in the theoretical treatment of the solid/liquid interface interaction with an approaching particle, experimental validation of some aspects of the developed models, and the experimental design aspects of future experiments to be performed on board the International Space Station.

Stefanescu, D. M.↗
DOE OSTI2022

Design of Critical Experiments Targeting Epithermal Cross Sections of Tantalum

Sandia National Laboratories (SNL) and Oak Ridge National Laboratory (ORNL) are collaborating to develop a capability to test the epithermal/intermediate cross sections of tantalum (Ta) at the SNL critical experiments facility using the Seven Percent Critical Experiment (7uPCX) fuel. The Sandia Critical Experiments (SCX) Program provides a specialized facility for performing water moderated and reflected critical experiments with UO 2 fuel rod arrays. A history of safe reactor operations and flexibility in reactor core configuration has resulted in the completion of several benchmark critical experiment evaluations that are published in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The critical experiments described here are scheduled to be performed at SCX in fiscal year 2023. Currently, fabrication details for the needed new equipment are being finalized for completion of the procurement process. The experiments will then be executed and documented for publication consideration by the ICSBEP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2016

Ice Accretions and Full-Scale Iced Aerodynamic Performance Data for a Two-Dimensional NACA 23012 Airfoil

This report documents the data collected during the large wind tunnel campaigns conducted as part of the SUNSET project (StUdies oN Scaling EffecTs due to ice) also known as the Ice-Accretion Aerodynamics Simulation study: a joint effort by NASA, the Office National d'Etudes et Recherches Aérospatiales (ONERA), and the University of Illinois. These data form a benchmark database of full-scale ice accretions and corresponding ice-contaminated aerodynamic performance data for a two-dimensional (2D) NACA 23012 airfoil. The wider research effort also included an analysis of ice-contaminated aerodynamics that categorized ice accretions by aerodynamic effects and an investigation of subscale, low- Reynolds-number ice-contaminated aerodynamics for the NACA 23012 airfoil. The low-Reynolds-number investigation included an analysis of the geometric fidelity needed to reliably assess aerodynamic effects of airfoil icing using artificial ice shapes. Included herein are records of the ice accreted during campaigns in NASA Glenn Research Center's Icing Research Tunnel (IRT). Two different 2D NACA 23012 airfoil models were used during these campaigns; an 18-in. (45.7-cm) chord (subscale) model and a 72-in. (182.9-cm) chord (full-scale) model. The aircraft icing conditions used during these campaigns were selected from the Federal Aviation Administration's (FAA's) Code of Federal Regulations (CFR) Part 25 Appendix C icing envelopes. The records include the test conditions, photographs of the ice accreted, tracings of the ice, and ice depth measurements. Model coordinates and pressure tap locations are also presented. Also included herein are the data recorded during a wind tunnel campaign conducted in the F1 Subsonic Pressurized Wind Tunnel of ONERA. The F1 tunnel is a pressured, high- Reynolds-number facility that could accommodate the full-scale (72-in. (182.9-cm) chord) 2D NACA 23012 model. Molds were made of the ice accreted during selected test runs of the full-scale model in the IRT. From these molds, castings were made that closely replicated the features of the accreted ice. The castings were then mounted on the full-scale model in the F1 tunnel, and aerodynamic performance measurements were made using model surface pressure taps, the facility force balance system, and a large wake rake designed specifically for these tests. Tests were run over a range of Reynolds and Mach numbers. For each run, the model was rotated over a range of angles-of-attack that included airfoil stall. The benchmark data collected during these campaigns were, and continue to be, used for various purposes. The full-scale data form a unique, ice-accretion and associated aerodynamic performance dataset that can be used as a reference when addressing concerns regarding the use of subscale ice-accretion data to assess full-scale icing effects. Further, the data may be used in the development or enhancement of both ice-accretion prediction codes and computational fluid dynamic codes when applied to study the effects of icing. Finally, as was done in the wider study, the data may be used to help determine the level of geometric fidelity needed for artificial ice used to assess aerodynamic degradation due to aircraft icing. The structured, multifaceted approach used in this research effort provides a unique perspective on the aerodynamic effects of aircraft icing. The data presented in this report are available in electronic form upon formal approval by proper NASA and ONERA authorities.

Addy, Harold E., Jr.↗