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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 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2024

code for "Improving the QBO forcing by resolved waves with vertical grid refinement in E3SMv2"

This is all code that used in the journal article "Improving the QBO forcing by resolved waves with vertical grid refinement in E3SMv2", including: Running and post processing E3SM: Run E3SM: run_E3SM.2023.scidac.MMF.amip.py Regrid: regrid.E3SM.py post processing, diagnostics, archive: run_post.2023.scidac.MMF.py TEM calculation, including filter TEM, E3SM: calculate.TEM.v2.py calculate.TEM.monthly_mean.v1.py TEM, ERA5: ERA5_calculate_TEM_90.py merge TEM data: merge_TEM_E3SM_ERA5.py TEM, filter, E3SM: filter_TEM_E3SM.py TEM, filter, ERA5: filter_TEM_ERA5.py WK wave analysis code from (https://github.com/brianpm/wavenumber_frequency): wavenumber_frequency_functions.py calculate the wave spectra so easy to plot: wk_calculation.py Make figures some functions for plot: plot.py code for drawing paper plots: figures_for_paper.ipynb

Hannah, WalterM↗

DOE OSTI2025

Implementation of Stochastic Gradient Descent in an Automated Glow Peak Identification Software for Multiple Thermoluminescent Dosimeter Types

A glow-curve analysis code was previously developed in C++ to analyze thermoluminescent dosimeter glow curves using automated peak detection while applying a first-order kinetics model. A newer version of this code was implemented to improve the automated peak detection and curve fitting models. The Stochastic Gradient Descent Algorithm was introduced to replace the prior approach of taking first and second-order derivatives for peak detection. Additionally, early stopping mechanisms were invoked to improve the previously used Levenberg-Marquardt Algorithm employed for curve fitting. The two software versions were compared through glow curve analysis of different thermoluminescent dosimeter materials and calculation of the corresponding figures of merit. Altogether improvements were shown, namely an increase in the number of peaks detected and a reduction of the mean figure of merit by approximately 46%.

137Cs↗

DOE OSTI2017

Preliminary Development of a Nuclide Inventory Code for HTGR

Nuclide inventory calculation for a reactor core is the basis of radiation protection, shielding design and radioactive environmental impact assessment of the power plant. HTR-PM (high-temperature gas-cooled reactor pebble-bed module) under construction in China is one of the candidates for Gen-IV advanced nuclear power system.1 In the design stage of HTR-PM, KORIGEN has been utilized in the inventory calculation.2 However, the current version of KORIGEN was developed several decades ago. In order to improve the design capability of the analysis code package for HTR-PM, a new computer code for nuclide inventory calculation called NUIT (Nuclide Inventory Tool) is being developed based on the DEPTH3 code. The NUIT code tries to utilize accurate and efficient burnup solvers, incorporate well-validated and most recent nuclear data libraries, and provide user-friendly IO interface. This paper presents the preliminary work in the development of NUIT.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2014

Developing Fully Coupled Dynamical Reactor Core Isolation System Models in RELAP-7 for Extended Station Black-Out Analysis

The reactor core isolation cooling (RCIC) system in a boiling water reactor (BWR) provides makeup water to the reactor vessel for core cooling when the main steam lines are isolated and the normal supply of water to the reactor vessel is lost. It was one of the very few safety systems still available during the Fukushima Daiichi accidents after the tsunamis hit the plants and the system successfully delayed the core meltdown for a few days for unit 2 & 3. Therefore, detailed models for RCIC system components are indispensable to understand extended station black-out accidents (SBO) for BWRs. As part of the effort to develop the new generation reactor system safety analysis code RELAP-7, major components to simulate the RCIC system have been developed. This paper describes the models for those components such as turbine, pump, and wet well. Selected individual component test simulations and a simplified SBO simulation up to but before core damage is presented. The successful implementation of the simplified RCIC and wet well models paves the way to further improve the models for safety analysis by including more detailed physical processes in the near future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

International Neuroscience Initiatives through the Lens of High-Performance Computing

Neuroscience initiatives aim to develop new technologies and tools to measure and manipulate neuronal circuits. In this paper, to deal with the massive amounts of data generated by these tools, the authors envision the co-location of open data repositories in standardized formats together with high-performance computing hardware utilizing open source optimized analysis codes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Influence of protective actions on ingress-water mass in steam generator tube rupture of HTGR - 18479

Steam generator tube rupture(SGTR) accident is one characteristic accident of High Temperature Gas-Cooled Reactor (HTGR), which may cause a potential hazard to reactor system. Because the amount of water ingress into reactor core is related closely to the severity of the accident, the research on water-ingress is significant for the evaluation on inherent safety characteristics of HTGR. Both different accident scenario and the system design will have influence on the amount of the ingress-water under SGTR. In this paper, a pebble-bed high temperature gas cooled reactor is modeled by thermal-hydraulic system analysis code and the water-ingress transient under SGTR is simulated to study the influence of the protective action of emergency shutdown on the water ingress. The research indicates that the protective action has no obvious influence on the amount of the ingress-water within the current studied range. The amount of ingress-water is controlled below the design value to satisfy the demand of reactor safety. The analysis results will provide some support for the HTGR research. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2014

Initial RattleSnake Calculations of the Hot Zero Power BEAVRS

The validation of the Idaho National Laboratory's next generation of reactor physics analysis codes is an essential and ongoing task. The validation process requires a large undertaking and includes detailed, realistic models that can accurately predict the behavior of an operational nuclear reactor. Over the past few years the INL has developed the RattleSnake application and supporting tools on the MOOSE framework to perform these reactor physics calculations. RattleSnake solves the linearized Boltzmann transport equation with a variety of solution meth ods. Various traditional reactor physics benchmarks have already been performed, but a more realistic light water reactor comparison was needed to solidify the status of the code and deter mine its fidelity. The INL team decided to use the Benchmark for Evaluation and Validation of Reactor Simulations, which was made available in early 2013. This benchmark is a one of-a-kind document assembled by the Massachusetts Institute of Technology, which includes two cycles of detailed, measured PWR operational data. The results from this initial study of the hot zero power conditions show the current INL analysis procedure with DRAGON4 cross section preparation and using the low order diffusion solver in RattleSnake for the whole core calculations yield very encouraging results for PWR analysis. The radial assembly power distributions, radial detector measurements and control rod worths were computed with good accuracy. The computation of the isothermal temperature coefficients of reactivity require further study.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

MEASURING RISK IMPORTANCE IN A DYNAMIC PRA FRAMEWORK

Risk importance measures are indexes that are used to rank systems, structures and components (SSCs) using risk-informed methods. The most used/known measures are: Risk Reduction Worth (RRW), Risk Achievement Worth (RAW), Birnbaum (B) and Fussell-Vesely (FV). Once obtained from classical Probabilistic Risk Analysis (PRA) analyses, these risk measures can be effectively employed to optimize component testing and maintenance. In contrast to classical PRA methods, Dynamic PRA methods couple stochastic methods with safety analysis codes to determine risk associate to complex systems such as nuclear plants. Compared to classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. The objective of this paper is to present a series of algorithms that can be used to determine classical risk importance measures (RRW, RAW, B and FV) along with newly developed ones from a Dynamic PRA analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Integrated Security-Safety Consequence Study of a Heat Pipe Reactor

This report presents a preliminary demonstration of integrated security/safety consequence modeling to support potential physical security exemption justifications under the new Title 10 Code of Federal Regulations Part 53 licensing pathway, which allows exemptions if sabotage-induced radiological consequences do not exceed 25 rem at the site boundary two hours after release without mitigative actions. A hypothetical heat pipe microreactor subjected to direct sabotage by a 150 lbs. TNT-equivalent high-explosive device was analyzed using a simplified radionuclide release estimate based on DOE-HDBK-3010-94, implemented in the MELCOR severe accident analysis code to model release transport and attenuation through reactor/building compartments, with MELCOR outputs coupled to MACCS to compute offsite doses and the distance-to-threshold metric D 25rem . Six scenarios were evaluated to examine sensitivities to release pathway/building configuration and radionuclide form (vapor versus aerosols with different size distributions). Results show a positive correlation between leak path factor and D 25rem and indicate that reactor building compartmentalization can substantially reduce consequences (a single-story configuration reduced D 25rem by roughly an order of magnitude relative to a cavity-only configuration), while vapor versus aerosol assumptions had limited impact for the modeled two-story case on the spatial grid used.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Deciphering Degradation: Machine Learning on Real-World Performance Data

The solar investment community is in need of up-to-date and data-derived system degradation rates to use in financial models that calculate the risk and expectation of energy revenue. To date, financial models choose degradation rates from past studies that are limited and may not be representative of solar projects in development today. As the solar industry expands in all sectors (residential, commercial, and utility), there is a growing amount of energy generation data available to analyze. With the help of the open source degradation analysis code (RdTools) it is now possible to derive degradation on an ongoing basis and continuously provide up-to-date durability statistics to the investment community. Ongoing and accurate statistics of fielded photovoltaic systems allows financial stakeholders to constrain energy revenue projections, lower financial risk, and increase the bankability of solar. This presentation will provide a mid-term progress update on a 2 year SETO-funded degradation project that involves applying RdTools analysis on kWh Analytics’ industry database. With results from the RdTools analysis in hand, machine learning methods are employed to quantify how much variance of system performance degradation can be explained by predictor variables such as environmental factors, equipment bill of materials characteristics, and system design information. The goal of this presentation is to promote the usage of RdTools on an ongoing to data owners and to solicit feedback from researchers and stakeholders on how to maximize impact of the SETO-funded kWh Analytics degradation project.

14 SOLAR ENERGY↗

DOE OSTI2024

Griffin: A MOOSE-based reactor physics application for multiphysics simulation of advanced nuclear reactors

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor physics application for multiphysics simulations of advanced reactor designs jointly developed by Idaho National Laboratory and Argonne National Laboratory. This paper summarizes the motivation, significance, architecture, design, and features of Griffin. Griffin offers flexible and extensible features to address the challenges associated with advanced reactor designs. These features range from fundamental particle transport to specific reactor physics tasks. The features cover a wide range including on-the-fly and traditional two-step cross-section generation methods, steady-state and transient transport solvers suitable for both heterogeneous and homogeneous models, high-fidelity depletion where thousands of isotopes can be tracked and low-fidelity depletion characterized by burnup, etc. The most fundamental aspect that sets Griffin apart from other reactor analysis codes is that it is developed based on the MOOSE framework. A modular development approach is strongly enforced, with multiphysics being an essential element considered since the beginning of Griffin’s development. Griffin links various MOOSE physics modules and couples to other MOOSE-based applications and non-MOOSE-based applications for multiphyiscs simulations. Griffin includes three modules: ISOXML for preparing and managing multigroup cross sections, radiation transport for solving the neutron transport equation, and reactor analysis for user-oriented reactor physics analysis functionalities. Griffin uses various finite element methods for spatial discretization, multigroup approximation for energy discretization and discrete ordinates method, spherical harmonics expansion method, and diffusion approximation for streaming direction discretization to solve the neutron transport equation. Griffin’s flexibility is evidenced through Griffin’s various applications to fast reactor, high-temperature reactor, pebble bed reactor, molten salt reactor, and microreactor designs. Griffin development follows the software quality assurance procedure for MOOSE-based applications and with software requirements consistent with the ASME NQA-1 standard. Griffin has been adopted into the reactor analysis system for the U.S. NRC and is in use at U.S. companies, universities and national laboratories.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Analysis of genomic signatures associated with Variovorax endosphere colonization

This repository contains the analysis code and supporting datasets associated with the study “Genomic signatures in Variovorax enabling colonization of the Populus endosphere.” Beals DG, Carper DL, Hochanadel LH, Jawdy SS, Klingeman DM, Piatkowski BT, Weston DJ, Doktycz MJ, Pelletier DA. 2026. Genomic signatures in Variovorax enabling colonization of the Populus endosphere. mSystems 11:e01605-25. https://doi.org/10.1128/msystems.01605-25 The scripts are organized sequentially (01–07) and document the workflows used for: Sequence-read alignment and feature counting Orthogroup and KEGG Ortholog annotation Count normalization Statistical analysis and aggregation Generation of manuscript figures and tables Repository contents The uncompressed files are the finalized, formatted datasets used to generate the figures and tables reported in the study, including the supplemental CSV files referenced in the manuscript. The accompanying ZIP archive contains the complete codebase and example data_input/ and data_output/ directories illustrating the organization and execution of the analytical workflow. Individual scripts identify the corresponding manuscript analyses and figure panels. Raw sequencing data Raw sequencing reads are available through the NCBI Sequence Read Archive under BioProject accession PRJNA1322484.

Beals, Delaney [ORNL] (ORCID:0000000306274574)↗

DOE OSTI2026

Data-Driven Optimization of Pixelated CdZnTe Spectrometers for Uranium Enrichment Assay

Here, in recent work [Vavrek et al. (2025)], we developed the performance optimization framework spectre-ml for gamma spectrometers with variable performance across many readout channels. The framework uses non-negative matrix factorization (NMF) and clustering to learn groups of similarly-performing channels and sweep through various learned channel combinations to optimize the performance tradeoff of including worse-performing channels for better total efficiency. In this work, we integrate the pyGEM uranium enrichment assay code with our spectre-ml framework, and show that the U-235 enrichment relative uncertainty can be directly used as an optimization target. We find that this optimization reduces relative uncertainties after a 30 -minute measurement by an average of 20%, as tested on six different H3D M400 CdZnTe spectrometers, which can significantly improve uranium non-destructive assay measurement times in nuclear safeguards contexts. Additionally, this work demonstrates that the spect re-ml optimization framework can accommodate arbitrary end-user spectroscopic analysis code and performance metrics, enabling future optimizations for complex Pu spectra.

Gamma-ray detection↗

DOE OSTI2015

A Data Analysis Center for Electromagnetic and Hadronic Interaction. Products of the DAC members

The Data Analysis Center (DAC) of the Center for Nuclear Studies (CNS) at the George Washington University (GW) has made significant progress in its program to enhance and expand the partial-wave (and multipole) analyses of fundamental two- and three-body reactions (such as pion-nucleon, photon-nucleon, and nucleon-nucleon scattering) by maintaining and augmenting the analysis codes and databases associated with these reactions. These efforts provide guidance to experimental groups at the international level, forming an important link between theory and experiment. A renaissance in light hadron spectroscopy is underway as a continuous stream of polarization data issues from existing precision electromagnetic facilities and the coming Jefferson Lab 12 GeV Upgrade. Our principal goals have been focused on supporting the national N* resonance physics program. We have also continued to study topics more generally related to the problems associated with partial-wave analysis. On the Experimental side of the CNS DAC. Its primary goal is the enhancement of the body of data necessary for our analyses of fundamental γ - N reactions. We perform experiments that study the dynamics responsible for the internal structure of the nucleon and its excitations. Our principal focus is on the N* programs at JLab and MAMI. At JLab we study spin-polarization observables using polarized photons, protons and neutrons and yielding charged final states. Similarly at MAMI we study neutral meson photoproduction off polarized protons and neutrons. We use the Crystal Ball and TAPS spectrometers (CBT) to detect photons and neutrons to measure the photoproduction of π0, η, 2π0, π0η, and K0 off the neutron. The CBT program complements our program at JLab, which studies reactions resulting in charged final states. We are also involved in a renewed effort to make neutral pion photoproduction measurements close to threshold at Mainz. In addition to the programs underway, we are contributing to the future by participation in preparations for the coming JLab 12 GeV Upgrade. GW students are involved in tests of the detectors proposed to be used with CLAS12, i.e., for the CentralTime-of-Flight Barrel (CTOF). WJB is heavily involved in the MUSE quest at PSI to solve the Proton Radius Puzzle.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

Collated experience of the use of multi-group analysis (MGA) in non-destructive waste assay systems - 15257

The quantification of plutonium is an important aspect of non-destructive assay of Special Nuclear Material (SNM). The calculation of {sup 240}Pu{sub eff} can be done through prior knowledge of the composition of the waste but more often is done through the analysis of a measured plutonium gamma-ray spectrum performed using an isotopic analysis code. In this work, the {sup 240}Pu{sub eff} results from a variety of non-destructive waste assay systems in the UK are presented and compared using MGA v9.63C and v10. The body of the results include real measurement results of a variety of waste materials containing plutonium, the results of reanalysis of these initial waste measurements with changes to certain setup parameters and the results of reanalysis with a later version of MGA (v10). Additionally, measurements of test matrices with known source isotopics are measured and the results analysed and presented here. The use of the 'waste' flag parameter introduced to allow measurement of unusual spectra in v10 is also evaluated. When using MGA as part of the waste assay characterisation process in automatic or batch mode, results have proven to be very dependent on the quality of the spectra measured and on the setup parameters that the code is reliant upon. With a modern version of the code, the likelihood of under-reporting the total plutonium content of a 200 litre/55 gallon drum using PNCC and MGA isotopics in combination is low. Additionally, the latest 'hardened' code will also reduce the number of cases where MGA fails to run and the use of default isotopics results in an over-pessimistic evaluation of the total plutonium mass. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Emerging Jets Search, Triton Server Deployment, and Track Quality Development: Machine Learning Applications in High Energy Physics

Machine learning is becoming prevalent in high energy physics, with numerous applications in physics analyses and event reconstruction showing great improvements compared to traditional computing methods. This thesis studies three projects which each propose new avenues for machine learning applications within the high energy physics CMS experiment located at CERN. In the first project, a search for a dark matter signal called “emerging jets” is performed, using graph neural networks to greatly increase sensitivity to the signal’s signature within the data. The result of this dark matter search sets the most stringent exclusion limits to date on theoretical emerging jet models. Motivated by inefficiencies encountered when processing the emerging jet graph neural network at Fermi National Accelerator Laboratory’s computing centers, the second project re-optimizes the computing centers for machine learning inference. This re-optimization uses NVIDIA Triton Inference Servers to process users’ analysis code heterogeneously, therefore achieving high processing throughput and decreasing user time-to-insight. The last project focuses on an upgrade to the CMS experiment’s real-time event selection system which improves physics object reconstruction under harsh processing conditions. A boosted decision tree is used to quickly and efficiently quantify a reconstructed particle’s “track quality” in order to remove particle tracks reconstructed erroneously. In summary, this thesis will not only present examples of how high energy physics can greatly benefit by leveraging machine learning techniques for physics analysis and reconstruction, but will also provide guidance on how the field can prepare for the inevitable increase in machine learning applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Measuring Degradation of Fielded Systems on an Ongoing Basis with RdTools

The solar investment community needs up-to-date and data-derived system degradation rates to use in financial models that calculate the risk and expectation of energy revenue. To date, the majority of financial models choose degradation rates from past studies that are limited and may not be representative of future solar assets (systems) they are financing. As the solar industry expands in all sectors (residential, commercial, and utility), there is a growing amount of energy production available to analyze. With the help of the open source degradation analysis code (RdTools) it is now possible to derive degradation on an ongoing basis and continuously provide up-to-date durability statistics to the investment community. Ongoing and accurate statistics of fielded photovoltaic systems allows financial stakeholders to constrain energy revenue projections, lower financial risk, and increase the bankability of solar. This poster will present considerations and software engineering best practices to encourage data owners to measure degradation of their own photovoltaic assets on an ongoing basis. This poster will also preview an upcoming DOE-funded kWh Analytics degradation project which involves applying RdTools analysis on kWh Analytics’ industry database, aggregating results across variables such as weather, hardware, system configurations etc., and sharing the aggregated results with the broader community.

14 SOLAR ENERGY↗

DOE OSTI2014

DIC Challenge Sample Images Update

After the meetings at SEM and ICEM this year, which were both well attended by participants, it was decided by the participants that a first round of scoring the codes would be done using the Sample 14 and Sample 15 images. There was plenty of discussion on how we (the DIC Challenge Board) were going to score the results. What is going to be the balance between noise and filtering? And so forth. So it was decided to use a sub-group of the participants to help figure out if the submission guidelines were working, and how we would score the results. An additional benefit of this is that we can fix any submission guideline issues before getting results more broadly, and begin writing automated analysis codes. I expect that there will be a discussion on both subjects after I create a draft document of the scoring. This document is a draft of that report.

97 MATHEMATICS AND COMPUTING↗