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At least 829 records · Page 46

Dynamic Validation of CNN-Based Surrogate Models for Inverter-Based Resources in Open-Source Solvers

Traditionally, distribution system planning has focused on steady-state analyses, with limited consideration of dynamic behavior. However, as large or medium-scale inverter-based resources (IBRs), particularly grid-following (GFL) inverters in commercial or industry buildings, become more prevalent, understanding their dynamic impact is essential for grid planning and operation. This article presents an innovative deep-learning (DL)-approach using convolutional neural networks technique to model the GFL inverters. Developed from real grid-tied commercial IBR transient data, these dynamic DL models overcome proprietary constraints by requiring minimal knowledge of internal converter physics while maintaining high accuracy and flexibility. To demonstrate their applicability, the models were incorporated into GridLAB-D, an open-source, three-phase distribution analysis tool. This integration enables dynamic simulations of large-scale distribution networks with high IBR penetration stability analysis. Rigorous testing and validation, aligned with industry standards, confirmed the reliability and efficiency of this approach, paving the way for enhanced planning and operational assessments of modern power systems.

Deep-learning↗

Rapid depletion analysis of flowing-pebble reactor systems at equilibrium using SCALE

Several high-temperature gas-cooled reactor concepts (and more recently, salt-cooled designs such as the fluoride salt-cooled high-temperature reactor) feature core designs employing continuously circulating fuel pebbles. These reactor designs permit both continuous online refueling of fuel elements as well as higher overall achievable discharge burnups. However, rapid calculation of time-dependent fuel isotopic inventories proves challenging for this class of dynamic systems with current analysis tools. While iterative approaches employing coupled neutron transport have been developed to solve this issue, rapid depletion analysis techniques are needed to calculate time-dependent inventories for individual pebbles and batches (and thus the construction of full- core inventory at equilibrium). We propose a depletion analysis strategy for this type of system for cores at equilibrium. Drawing upon previous neutronic analysis of the PBMR-400 equilibrium core, we demonstrate the viability of developing collapsed one-group cross section libraries suitable for performing rapid depletion analyses with SCALE. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

An interactive environment for the analysis of large Earth observation and model data sets

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X Data Slice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

Bowman, Kenneth P.↗

An interactive environment for the analysis of large Earth observation and model data sets

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X DataSlice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

Bowman, Kenneth P.↗

A Method of Integrating Aeroheating into Conceptual Reusable Launch Vehicle Design: Evaluation of Advanced Thermal Protection Techniques for Future Reusable Launch Vehicles

A method for integrating Aeroheating analysis into conceptual reusable launch vehicle (RLV) design is presented in this thesis. This process allows for faster turn-around time to converge a RLV design through the advent of designing an optimized thermal protection system (TPS). It consists of the coupling and automation of four computer software packages: MINIVER, TPSX, TCAT, and ADS. MINIVER is an Aeroheating code that produces centerline radiation equilibrium temperatures, convective heating rates, and heat loads over simplified vehicle geometries. These include flat plates and swept cylinders that model wings and leading edges, respectively. TPSX is a NASA Ames material properties database that is available on the World Wide Web. The newly developed Thermal Calculation Analysis Tool (TCAT) uses finite difference methods to carry out a transient in-depth 1-D conduction analysis over the center mold line of the vehicle. This is used along with the Automated Design Synthesis (ADS) code to correctly size the vehicle's thermal protection system (TPS). The numerical optimizer ADS uses algorithms that solve constrained and unconstrained design problems. The resulting outputs for this process are TPS material types, unit thicknesses, and acreage percentages. TCAT was developed for several purposes. First, it provides a means to calculate the transient in-depth conduction seen by the surface of the TPS material that protects a vehicle during ascent and reentry. Along with the in-depth conduction, radiation from the surface of the material is calculated along with the temperatures at the backface and interior parts of the TPS material. Secondly, TCAT contributes added speed and automation to the overall design process. Another motivation in the development of TCAT is optimization. In some vehicles, the TPS accounts for a high percentage of the overall vehicle dry weight. Optimizing the weight of the TPS will thereby lower the percentage of the dry weight accounted for by the TPS. Also, this will lower the cost of the TPS and the overall cost of the vehicle.

Olds, John R.↗

Accuracy Analysis for Finite-Volume Discretization Schemes on Irregular Grids

A new computational analysis tool, downscaling test, is introduced and applied for studying the convergence rates of truncation and discretization errors of nite-volume discretization schemes on general irregular (e.g., unstructured) grids. The study shows that the design-order convergence of discretization errors can be achieved even when truncation errors exhibit a lower-order convergence or, in some cases, do not converge at all. The downscaling test is a general, efficient, accurate, and practical tool, enabling straightforward extension of verification and validation to general unstructured grid formulations. It also allows separate analysis of the interior, boundaries, and singularities that could be useful even in structured-grid settings. There are several new findings arising from the use of the downscaling test analysis. It is shown that the discretization accuracy of a common node-centered nite-volume scheme, known to be second-order accurate for inviscid equations on triangular grids, degenerates to first order for mixed grids. Alternative node-centered schemes are presented and demonstrated to provide second and third order accuracies on general mixed grids. The local accuracy deterioration at intersections of tangency and in flow/outflow boundaries is demonstrated using the DS tests tailored to examining the local behavior of the boundary conditions. The discretization-error order reduction within inviscid stagnation regions is demonstrated. The accuracy deterioration is local, affecting mainly the velocity components, but applies to any order scheme.

Diskin, Boris↗

Propagating neutronic uncertainties for FFTF LOFWOS Test #13

The safety evaluation conducted for licensing a Sodium-cooled Fast Reactor (SFR) may require modeling transients with best-estimate calculation tools that must first be validated against real-world measurements. To provide the community with a valuable benchmarking opportunity for validating SFR analysis tools and methods, the International Atomic Energy Agency (IAEA) initiated a coordinated research project (CRP) in 2018 for the analysis of the Fast Flux Test Facility (FFTF) Loss of Flow Without Scram (LOFWOS) Test #13. The impact of nuclear data uncertainties on neutronics parameters was previously investigated based on the COMMARA-2.0 covariance matrix. Since the transient simulation results are very sensitive to certain reactivity coefficients, it was decided to employ rigorous uncertainty propagation methods to quantify the impact of nuclear data uncertainties on the best-estimate predication of FFTF LOFWOS Test #13. The DAKOTA code is used to propagate neutronic uncertainties through SAS4A/SASSYS-1 transient simulations, while taking into account spatial and reaction-wise correlations within these uncertainties. This study shows that the remaining discrepancies observed between the Argonne National Laboratory (ANL) best-estimate results and the experimental measurements can be partly explained by the uncertainty associated with Gas Expansion Module (GEM) worth, which contributes the majority of the overall nuclear data uncertainty on the output from the FFTF LOFWOS Test #13 transient simulation. This study also confirmed the importance of including spatial and reaction-wise correlations of nuclear data uncertainties on feedback coefficients in the uncertainty propagation to avoid under-estimating their impact during the transient simulations.

42 ENGINEERING↗

GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics

Data package for Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the below citations for the data packages and associated manuscript. Please cite as: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics. [Data Set] PNNL DataHub. doi: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. MSV000097435: GLBRC soil yearlong incubation 13C-SIP-Lipidomics [Data Set] MassIVE. doi:10.25345/C57659T3K Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon. In Prep This data package consists of compound-specific 13C SIP-lipidomics data from a yearlong tracer incubation experiment designed to investigate microbial lipid persistence in switchgrass bioenergy crop soils. In order to explore how lipid structure may modulate the persistence of C in soil lipids, we leveraged soils from two sites (Michigan - sandy texture, Wisconsin - silty texture) operated by the U.S. Department of Energy-funded Great Lakes Bioenergy Research Center (GLBRC). These sites had comparable climates, identical management practices, but contrasting soil textures, allowing us to assess the variability of lipid accrual or degradation in soils as well as provide insight regarding the degree to which edaphic properties may regulate the retention of soil lipids. Untargeted lipidomics analyses were performed to identify 13C-labeled lipids in the soil microbiome after long-term incubation. Soils were supplemented with 100 micrograms glucose per gram dry soil (99 atom % 13C or natural abundance for paired control) and incubated; samples were collected two months and one year after glucose addition. Lipid extracts (MPLEx) were analyzed by LC-MS/MS and identified using LIQUID. Calculation of isotopic enrichment of lipids was performed by targeted approach using TarMet to quantify lipid isotopologues and IsoCorrectoR to correct for natural abundance isotopes. Contents: Data package contents reported here are the first version and contain downstream analysis files for the raw LC-MS mass spectrometry files (.mzXML) deposited at the MassIVE database repository under accession MSV000097435 (80 experimental runs; 5.85 GB) | MassIVE DOI: 10.25345/C57659T3K. Support files include the additional data download 'Read Me' file containing data descriptor information. Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. Data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location. Available Data Downloads (0.3 GB): "GLBRC soil yearlong incubation 13C-SIP-Lipidomics_readme.txt" - 'Read Me' data package content file (txt) "GLBRC_DataPackage_analysis files" - Data processing files (Rmd) and saved intermediate data processing outputs (rds, csv, xlsx) "GLBRC_13C_lipidomics_dataset.xlsx" - processed data in tabular format (xlsx) Linked Software: LIQUID LC-MS Analysis Software | 10.5281/zenodo.6459462 Lipid Mini-On Software Tools | 10.5281/zenodo.1492803 pmartR Omics Statistical Software | 10.5281/zenodo.6108667 xcms (v4.3.3) TarMet (v1.1.1) IsoCorrectoR (1.24.0) Funding Acknowledgments: This research was supported by an Early Career Research Program award funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (OBER) Genomic Science program under FWP 68292, FWP 07880 and EMSL Exploratory Research Project 51095. A portion of this work was performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by OBER and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated by Battelle for the DOE under Contract DE-AC05-76RLO1830.

Rempfert, Kaitlin R [Pacific Northwest National La↗

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

The Digital Engineering Vision for DOME: Facilitating Design, Deployment, and Operations [Poster]

DOME is a planned microreactor test facility at INL’s Materials and Fuels Complex. It is a complex system with several interdependent sub-systems such as the reactor (up to 20 MWth), radioactive confinement, temperature and pressure regulation system, ventilation system, etc. The engineering design process for such a system traditionally involves several documents from various sources and the system information is scattered across these documents. Digital engineering represents a paradigm shift through which systems are designed using digital models and integrated data. The digital engineering vision for DOME utilizes a model-based systems engineering (MBSE) approach. The system architecture, physical components, control logic, and verification experiments are all designed using MathWorks MATLAB and Simulink. This hierarchical model can combine data from multiple sources at various levels of abstraction. It can be used to simulate the facility’s operations and to test the system using different sets of parameters. Its capabilities can be expanded by interfacing it with high-fidelity multi-physics models, risk analysis tools, etc. The same model can evolve into a digital twin that can monitor operations and conduct predictive analysis using real-time sensor data from the facility. The eventual goal of this effort is to transform the end-to-end engineering of nuclear facilities in every phase of their lifecycle, including design, deployment, and operations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SinhaRoy_TechPresentation_2024 [Slides]

DOME is a planned microreactor test facility at INL’s Materials and Fuels Complex. It is a complex system with several interdependent sub-systems such as the reactor (up to 20 MWth), radioactive confinement, temperature and pressure regulation system, ventilation system, etc. The engineering design process for such a system traditionally involves several documents from various sources and the system information is scattered across these documents. Digital engineering represents a paradigm shift through which systems are designed using digital models and integrated data. The digital engineering vision for DOME utilizes a model-based systems engineering (MBSE) approach. The system architecture, physical components, control logic, and verification experiments are all designed using MathWorks MATLAB and Simulink. This hierarchical model can combine data from multiple sources at various levels of abstraction. It can be used to simulate the facility’s operations and to test the system using different sets of parameters. Its capabilities can be expanded by interfacing it with high-fidelity multi-physics models, risk analysis tools, etc. The same model can evolve into a digital twin that can monitor operations and conduct predictive analysis using real-time sensor data from the facility. The eventual goal of this effort is to transform the end-to-end engineering of nuclear facilities in every phase of their lifecycle, including design, deployment, and operations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A piloted comparison of elastic and rigid blade-element rotor models using parallel processing technology

A piloted comparison of rigid and aeroelastic blade-element rotor models was conducted at the Crew Station Research and Development Facility (CSRDF) at Ames Research Center. FLIGHTLAB, a new simulation development and analysis tool, was used to implement these models in real time using parallel processing technology. Pilot comments and quantitative analysis performed both on-line and off-line confirmed that elastic degrees of freedom significantly affect perceived handling qualities. Trim comparisons show improved correlation with flight test data when elastic modes are modeled. The results demonstrate the efficiency with which the mathematical modeling sophistication of existing simulation facilities can be upgraded using parallel processing, and the importance of these upgrades to simulation fidelity.

Hill, Gary↗

Evaluation of Advanced Thermal Protection Techniques for Future Reusable Launch Vehicles

A method for integrating Aeroheating analysis into conceptual reusable launch vehicle RLV design is presented in this thesis. This process allows for faster turn-around time to converge a RLV design through the advent of designing an optimized thermal protection system (TPS). It consists of the coupling and automation of four computer software packages: MINIVER, TPSX, TCAT and ADS. MINIVER is an Aeroheating code that produces centerline radiation equilibrium temperatures, convective heating rates, and heat loads over simplified vehicle geometries. These include flat plates and swept cylinders that model wings and leading edges, respectively. TPSX is a NASA Ames material properties database that is available on the World Wide Web. The newly developed Thermal Calculation Analysis Tool (TCAT) uses finite difference methods to carry out a transient in-depth I-D conduction analysis over the center mold line of the vehicle. This is used along with the Automated Design Synthesis (ADS) code to correctly size the vehicle's thermal protection system JPS). The numerical optimizer ADS uses algorithms that solve constrained and unconstrained design problems. The resulting outputs for this process are TPS material types, unit thicknesses, and acreage percentages. TCAT was developed for several purposes. First, it provides a means to calculate the transient in-depth conduction seen by the surface of the TPS material that protects a vehicle during ascent and reentry. Along with the in-depth conduction, radiation from the surface of the material is calculated along with the temperatures at the backface and interior parts of the TPS material. Secondly, TCAT contributes added speed and automation to the overall design process. Another motivation in the development of TCAT is optimization.

Olds, John R.↗

An Automatic Medium to High Fidelity Low-Thrust Global Trajectory Toolchain; EMTG-GMAT

Solving the global optimization, low-thrust, multiple-flyby interplanetary trajectory problem with high-fidelity dynamical models requires an unreasonable amount of computational resources. A better approach, and one that is demonstrated in this paper, is a multi-step process whereby the solution of the aforementioned problem is solved at a lower-fidelity and this solution is used as an initial guess for a higher-fidelity solver. The framework presented in this work uses two tools developed by NASA Goddard Space Flight Center: the Evolutionary Mission Trajectory Generator (EMTG) and the General Mission Analysis Tool (GMAT). EMTG is a medium to medium-high fidelity low-thrust interplanetary global optimization solver, which now has the capability to automatically generate GMAT script files for seeding a high-fidelity solution using GMAT's local optimization capabilities. A discussion of the dynamical models as well as thruster and power modeling for both EMTG and GMAT are given in this paper. Current capabilities are demonstrated with examples that highlight the toolchains ability to efficiently solve the difficult low-thrust global optimization problem with little human intervention.

low thrust↗

A Noise and Emissions Assessment of the N3-X Transport

Analytical predictions of certification noise and exhaust emissions for NASA's N3-X - a notional, hybrid wingbody airplane - are presented in this paper. The N3-X is a 300-passenger concept transport propelled by an array of fans distributed spanwise near the trailing edge of the wingbody. These fans are driven by electric motors deriving power from twin generators driven by turboshaft engines. Turboelectric distributed hybrid propulsion has the potential to dramatically increase the propulsive efficiency of aircraft. The noise and exhaust emission estimates presented here are generated using NASA's conceptual design systems analysis tools with several key modifications to accommodate this unconventional architecture. These tools predict certification noise and the emissions of oxides of nitrogen by leveraging data generated from a recent analysis of the N3-X propulsion system.

Berton, Jeffrey J.↗

Modeling of the Influence of a Damaged Thermally Grown Oxide (TGO) Layer in an Environmental Barrier Coating System

Environmental barrier coatings (EBC) are an enabling technology for the successful application of ceramic matrix composites (CMCs) in air-breathing gas turbine engines. EBCs are susceptible to a number of failure modes including oxidation/delamination, recessions, chemical attack and dissolution, thermomechanical degradation, erosion, and foreign object impact damage in a combustion environment. Spallation of environmental barrier coating (EBC), induced by a thermally grown oxide (TGO) layer, is a key EBC failure mode. The TGO layer, resulting from steam oxidation, grows either from a silicon bond coat layer (if present) or from a silicon carbide (SiC) based substrate itself. The TGO layer evolves (i.e., thickness increases with time) as water vapor and oxygen gradually diffuse through the EBC, and the EBC spalls off once the TGO layer reaches some critical thickness. The critical thickness of the TGO layer for failure is in the range of 20-30 microns, but it can vary due to exposure temperature, microstructure etc. Current work at NASA Glenn Research Center, under the Revolutionary Tools and Methods (RTM) subproject is aimed at addressing associated failure modes in EBC systems and developing robust analysis tools to aid in the design/analysis of these systems. The objective of the current work is to conduct a sensitivity study to examine the influence of uniformly and non-uniformly grown oxide layers on the associated driving forces leading to spallation of the EBC when subjected to isothermal loading. The effect of damage in the TGO layer on the resulting stress states is also assessed both in uniform and non-uniform TGO layers.

Mital, Subodh K.↗

Influence of Thermally-Grown Oxide (TGO) Layer on the Driving Forces Associated with Failure in Environmental Barrier Coating (EBC) Systems

Environmental barrier coatings (EBC) is an enabling technology for the successful application of ceramic matrix composites (CMCs) in air-breathing gas turbine engines. Spallation of environmental barrier coating (EBC) induced by thermally grown oxide (TGO) layer is a key EBC failure mode. The TGO layer, resulting from steam oxidation, grows either from a silicon bond coat layer (if present) or from the silicon carbide (SiC) based substrate itself. Critical thickness of the TGO layer for failure is in the range of 20-30 microns but it can vary due to exposure temperature, microstructure etc. Current work at NASA Glenn Research Center, under the Revolutionary Tools and Methods (RTM) project is aimed at addressing associated failure modes in EBC systems and developing robust analysis tools to aid in the design/analysis of these systems. The objective of the current work is to conduct a sensitivity study to examine the influence of uniformly and non-uniformly grown oxide layers with or without damage on the associated driving forces leading to spallation of the EBC when subjected to isothermal loading. Initial results indicate that the presence of damage (vertical cracks caused by in-plane stresses) enhances the stresses that are present due to non-uniformity. However, the presence of non-uniformity itself is still the main factor influencing the magnitude of peel and shear stresses in the TGO layer.

Mital, Subodh K.↗

Modeling of the Influence of Thermally Grown Oxide (TGO) Layers on the Driving Forces in Environmental Barrier Coating Systems

Environmental barrier coatings (EBC) are an enabling technology for the successful application of ceramic matrix composites (CMCs) in air-breathing gas turbine engines. EBCs are susceptible to several failure modes including oxidation/delamination, recession, chemical attack and dissolution, thermomechanical degradation, erosion, and foreign object impact damage in a combustion environment. Spallation of environmental barrier coating (EBC), induced by a thermally grown oxide (TGO) layer, is a key EBC failure mode. The TGO layer, resulting from steam oxidation, grows either from a silicon bond coat layer (if present) or from a silicon carbide (SiC) based substrate itself. The TGO layer evolves (i.e., thickness increases with time) as water vapor and oxygen gradually diffuse through the EBC, and the EBC spalls off once the TGO layer reaches some critical thickness. The critical thickness of the TGO layer for failure is in the range of 20-30 microns, with the actual value depending upon exposure temperature, microstructure, etc. Current work at NASA Glenn Research Center, under the Transformative Tools and Technology (TTT) subproject is aimed at addressing associated failure modes in EBC systems and developing robust analysis tools to aid in the design/analysis of these systems. The objective of the current work is to conduct a sensitivity study to examine the influence of uniformly and non-uniformly grown oxide layers on the associated driving forces leading to spallation of the EBC when subjected to isothermal loading. The effect of damage in the TGO layer on the resulting stress states is also assessed both in uniform and non-uniform TGO layers.

Coatings↗