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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Morphology-Based Building Use-Type Modeling: Learnability-First Schema Discovery

This technical memorandum documents an update to the building use-type classification workflow, used in LandScan Mosaic, that replaces a fixed, semantically defined class schema with a learnability-first schema discovery procedure. Historically, the target label schema was specified a priori (e.g., predicting a chosen set of use-type codes), and model training and evaluation were performed within that fixed label space. In the updated workflow, the pipeline first evaluates which non-residential distinctions are learnable under spatial generalization and then collapses ambiguous classes into data-driven groupings before finalizing the schema used for production training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High Temperature Steam Electrolysis Process Model

The code models the operation of a high temperature steam electrolysis (HTSE) plant coupled with a nuclear power plant, and provides calculations of the process energy requirements; water feed stream flow rate requirements; process cooling requirements; process conditions such as temperature, pressure, and flow rate, throughout the process; product purity and flow rate, as well as data that can be used to determine the sizing, performance, and cost specifications of individual equipment components that comprise the system.

Wendt, DanielS (0000000344914296)↗
DOE OSTI2023

Molten Salt Reactor Experiment Simulation using Shift/Griffin

The Department of Energy (DOE)’s NEAMS focuses its efforts on the development of advanced modeling and simulation (M&S) tools for light-water reactors (LWRs) and non–LWRs (i.e., molten salt reactors, high-temperature gas reactors, microreactors, and fast reactors). In the previous fiscal year, the Multiphysics Applications Driver Technical Area funded molten salt reactor (MSR) M&S at Oak Ridge National Laboratory (ORNL) to generate multigroup macroscopic cross sections with Shift for a MSRE 2D lattice model in Griffin. In addition, Shift’s capability to calculate gamma dose rates from activated components in the primary exchangers in a molten salt breeder reactor was also demonstrated. In fiscal year 2023, ORNL generated multigroup macroscopic cross sections using Shift for a 3D MSRE core model. MSRE depletion calculations using Griffin were also demonstrated in this fiscal year. For the depletion calculation, one-group microscopic cross sections for the 3D MSRE core were generated using Shift, and the decay transmutation library from ORIGEN was converted to an ISOXML file, which is required as input in Griffin. Several Monte Carlo codes, such as OpenMC and Serpent, were also used to benchmark and supplement multigroup cross sections generated by Shift. Multigroup libraries were generated with 8 and 20 group structures, and the study found the 8-group structure to be more accurate when comparing Griffin results to continuous energy (CE) Monte Carlo results. The average flux from CE Shift calculations is up to ~6% higher than the CE Serpent calculations because of different values applied for the energy released per fission (κ values). The average flux in the fuel salt calculated by Griffin using cross sections generated with Shift agrees well with the reference CE Shift solution; the same is valid for the corresponding Serpent results. The maximum relative error is ~6% and ~2% compared to the CE Shift and Serpent reference solutions, respectively. Meanwhile, the average flux calculated by Griffin in the graphite moderator shows a higher difference in the thermal range when compared to both reference Monte Carlo solutions; this result suggests a need for improvement in cross section generation for the graphite moderator in the thermal range in both Monte Carlo codes. Griffin depletion calculations using cross sections from Shift and Serpent were performed and compared against ORIGEN calculations, and the nuclide densities calculated by Griffin were found to be generally in agreement with those of ORIGEN. Because a different approach was taken to calculate the energy released per fission ( κ values) in Shift and Serpent, a difference in nuclide densities from differences in the average flux was observed between Griffin using Serpent and Shift cross sections. Griffin calculations with Shift cross sections produced higher average flux in the salt than with Serpent cross sections, leading to higher consumption of 235 U and higher production of 135 Xe. For time-dependent depletion calculations, cross sections were generated with Serpent, and Griffin’s results using these cross sections were compared to CE Serpent depletion results, demonstrating good agreement. The average difference in keff between Serpent and Griffin as a function of burnup is about 155 pcm. Similarly, good agreement with small differences up to ~0.5% was also noticed in the nuclide density of 235 U and 135 Xe. More details regarding the methodologies invoked to generate the cross section to make code-to-code comparisons are discussed further in this report. User feedback on Griffin and Shift capabilities that will enhance these calculations is provided in this report for future consideration. The work performed this fiscal year can be extended further for multiphysics coupling of Griffin-Pronghorn/SAM with Mole to study precursor flow and salt chemistry.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

An efficient numerical model for predicting residual stress and strain in parts manufactured by laser powder bed fusion

Abstract Computational modeling of additively manufactured structures plays an increasingly important role in product design and optimization. For laser powder bed fusion processes, the accurate modeling of stress and distortion requires large amount of computational cost due to very localized heat input and evolving complex geometries. The current study takes advantage of a graphics processing unit accelerated explicit finite element analysis code and approximated heat conduction analysis to predict the macroscopic thermo-mechanical behavior in laser selective melting. Adjacent layers and tracks were lumped to reduce the number of time steps and elements in the finite element model. The effects of track and layer grouping on prediction accuracy and solution efficiency are investigated to provide a guidance for a cost-effective simulation. Thin-wall builds from Inconel alloy 625 (IN625) powders were simulated by applying the developed modeling approach to get the detailed residual stress and distortion at a computational speed 50 times higher than conventional approach. Under repeated heating and cooling cycles, a high tensile stress was produced near surfaces of a build due to a larger shrinkage on surface than that in central area. It is also shown that horizontal stresses concentrate near the root and top layers of the IN625 build. The predicted residual elastic strain distribution was validated by the experimental measurement using x-ray synchrotron diffraction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measurement of 139 La(p,x) cross sections from 35–60 MeV by stacked-target activation

A stacked-target of natural lanthanum foils (99.9119% 139 La) was irradiated using a 60 MeV proton beam at the LBNL 88-Inch Cyclotron. 139 La(p,x) cross sections are reported between 35–60 MeV for nine product radionuclides. The primary motivation for this measurement was the need to quantify the production of 134 Ce. As a positron-emitting analogue of the promising medical radionuclide 225 Ac, 134 Ce is desirable for in vivo applications of bio-distribution assays for this emerging radio-pharmaceutical. Finally, the results of this measurement were compared to the nuclear model codes TALYS, EMPIRE and ALICE (using default parameters), which showed significant deviation from the measured values.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Genome-based analysis for the bioactive potential of Streptomyces yeochonensis CN732, an acidophilic filamentous soil actinobacterium

Background: Acidophilic members of the genus Streptomyces can be a good source for novel secondary metabolites and degradative enzymes of biopolymers. In this study, a genome-based approach on Streptomyces yeochonensis CN732, a representative neutrotolerant acidophilic streptomycete, was employed to examine the biosynthetic as well as enzymatic potential, and also presence of any genetic tools for adaptation in acidic environment. Results: A high quality draft genome (7.8Mb) of S. yeochonensis CN732 was obtained with a G+C content of 73.53% and 6549 protein coding genes. The in silico analysis predicted presence of multiple biosynthetic gene clusters (BGCs), which showed similarity with those for antimicrobial, anticancer or antiparasitic compounds. However, the low levels of similarity with known BGCs for most cases suggested novelty of the metabolites from those predicted gene clusters. The production of various novel metabolites was also confirmed from the combined high performance liquid chromatography-mass spectrometry analysis. Through comparative genome analysis with related Streptomyces species, genes specific to strain CN732 and also those specific to neutrotolerant acidophilic species could be identified, which showed that genes for metabolism in diverse environment were enriched among acidophilic species. In addition, the presence of strain specific genes for carbohydrate active enzymes (CAZyme) along with many other singletons indicated uniqueness of the genetic makeup of strain CN732. The presence of cysteine transpeptidases (sortases) among the BGCs was also observed from this study, which implies their putative roles in the biosynthesis of secondary metabolites. Conclusions: This study highlights the bioactive potential of strain CN732, an acidophilic streptomycete with regard to secondary metabolite production and biodegradation potential using genomics based approach. The comparative genome analysis revealed genes specific to CN732 and also those among acidophilic species, which could give some insights into the adaptation of microbial life in acidic environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multispectral and thermal surface imagery and surface elevation mosaics - SGP July 2022

This data set contains high-resolution image products (orthomosaics) acquired from midsized uncrewed aerial systems that have been processed for value-added quality. The instrument itself, a multispectral imager, the Altum by Micasense, captures six spectral bands (red, green blue, NIR, red edge, and LWIR/thermal1) as radiance, which is converted to reflectance via custom code. The code used to develop these images first uses tools from the Micasense Python library2 to apply dark level corrections, row gradient corrections, and radiometric corrections. Next, it uses the processing API from Agisoft Metashape software to align and mosaic the processed imagery, following the processes developed by the USGS' structure from motion workflow documentation.3 Captures at different altitudes (recorded in MSL) produce an orthomosaic, a tif image containing information related to the six spectral bands, and a digital elevation model (DEM), a tif image containing information related to the elevation of the surveyed terraine. Metadata included in every image can be used to extract lat, lon, and reflectance values. 1 https://www.arm.gov/publications/tech_reports/handbooks/doe-sc-arm-tr-281.pdf 2 https://micasense.github.io/imageprocessing/MicaSense%20Image%20Processing%20Setup.html 3 https://pubs.usgs.gov/of/2021/1039/ofr20211039.pdf

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Photonuclear Physics in SCALE

Radiation shielding modeling involves a wide range of applications, such as power reactors, critical experiments, portable sources, linear accelerators, and fusion systems. Particle energy ranges vary from thermal energies to fast energy spectra. MAVRIC, as the radiation shielding sequence of the SCALE code system [1] developed and maintained by Oak Ridge National Laboratory, is capable of modeling both neutron and photon interactions in matter and is widely used by the US Nuclear Regulatory Commission, Department of Energy, the National Nuclear Security Administration, and radiation shielding practitioners all around the world. Although most applications don’t involve highly energetic photons that can cause photonuclear reactions and create coupled chains of high energy, ionized electrons and bremsstrahlung radiation within a material medium, when present, these reactions can have a significant impact upon the downstream particle fluxes from incident photons above 20 MeV. For example, linear accelerators used for medical isotope production are examples of applications in which high-energetic photons are generated and used for driving or controlling other components of a complex facility. Radiation shielding analyses of such a facility would require accounting for any and all significant sources of radiation. Unfortunately, MAVRIC included no data and methods to model either photonuclear reactions or the bremsstrahlung photons until this work, which enabled accounting for both. Photonuclear reaction cross sections were imported from the Evaluated Nuclear Data File libraries, and corresponding methods were implemented in the SCALE code system; see Section 2 for how the nuclear data are imported and used. Bremsstrahlung photons were modeled by assuming thick-target approximation whereby all generated electrons and positrons due to photon interactions are assumed to be absorbed within the same material in which they were born, yielding a quick particle transport simulation method by using fast lookup tables for generating subsequent gammas; see Section 4 for details. A suite of verification models was used to test implemented methods and associated data. Tests yielded satisfactory results for the new features. Enhancements will be released as part of the next major SCALE release (v7.0), which is anticipated to be deployed in 2025, with beta releases available in the interim.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Jet-veto resummation at N 3 LL p + NNLO in boson production processes

Vetoing energetic jet activity is a crucial tool for suppressing backgrounds and enabling new physics searches at the LHC, but the introduction of a veto scale can introduce large logarithms that may need to be resummed. We present an implementation of jet-veto resummation for color-singlet processes at the level of N 3 LL p matched to fixed-order NNLO predictions. Our public code MCFM allows for predictions of a single boson, such as Z/γ*, W ± or H, or with a pair of vector bosons, such as W + W – , W ± Z or ZZ. The implementation relies on recent calculations of the soft and beam functions in the presence of a jet veto over all rapidities, with jets defined using a sequential recombination algorithm with jet radius R. However one of the ingredients that is required to reach full N 3 LL accuracy is only known approximately, hence N 3 LL p . We describe in detail our formalism and compare with previous public codes that operate at the level of NNLL. Our higher-order predictions improve significantly upon NNLL calculations by reducing theoretical uncertainties. We demonstrate this by comparing our predictions with ATLAS and CMS results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

CMS Full Simulation for Run 3

We report the status of the CMS full simulation for Run 3. During the long shutdown of the LHC a significant update has been introduced to the CMS code for simulation. The CMS geometry description is reviewed. Several important modifications were needed. CMS detector description software is migrated to the DD4Hep community developed tool. We will report on our experience obtained during the process of this migration. Geant4 10.7 is the CMS choice for Run 3 simulation productions. We will discuss arguments for this choice, the strategy of adaptation of a new Geant4 version, and will report on the physics performance of the CMS simulation. A special Geant4 Physics List configuration FTFP_BERT_EMM will be described, which provides a compromise between simulation accuracy and CPU performance. A significant fraction of time for simulation of CMS events is spent on tracking of charged particles in a magnetic field. In the CMS simulation a dynamic choice of Geant4 parameters for tracking in field is implemented. A new method is introduced into simulation of electromagnetic components of hadronic showers in the electromagnetic calorimeter of CMS. For low-energy electrons and positrons a parametrization of GFlash type is applied. Results of tests of this method will be discussed. In summary, we expect about 25% speedup of the CMS simulation production for Run 3 compared to the Run 2 simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Designing a Framework for Solving Multiobjective Simulation Optimization Problems

Multiobjective simulation optimization (MOSO) problems are optimization problems with multiple conflicting objectives, where evaluation of at least one of the objectives depends on a black-box numerical code or real-world experiment, which we refer to as a simulation. Whereas an extensive body of research is dedicated to developing new algorithms and methods for solving these and related problems, it is challenging and time-consuming to integrate these techniques into real-world production-ready solvers. This is partly because of the diversity and complexity of modern state-of-the-art MOSO algorithms and methods and partly because of the complexity and specificity of many real-world problems and their corresponding computing environments. The complexity of this problem is only compounded when introducing potentially complex and/or domain-specific surrogate-modeling techniques, problem formulations, design spaces, and data acquisition functions. Here, this paper carefully surveys the current state of the art in MOSO algorithms, techniques, and solvers, as well as problem types and computational environments where MOSO is commonly applied. We then present several key challenges in the design of a parallel multiobjective simulation optimization framework (ParMOO) and how they have been addressed. Finally, we provide two case studies demonstrating how customized ParMOO solvers can be quickly built and deployed to solve real-world MOSO problems.

engineering design optimization↗
DOE OSTI2025

Heating effects on jack pine pyrogenic organic matter properties from a pyrocosm study in 2022

This dataset contains data associated with the preprint “Fire removes preexisting pyrogenic organic matter from the ecosystem through the mechanisms of both direct combustion and increasing mineralizability” (Luo et al., 2025b), which is the complementary study to the published paper “Reburning pyrogenic organic matter: a laboratory method for dosing dynamic heat fluxes from above” (Luo et al., 2025a). We designed a full-factorial experiment with different burial depths of jack pine (Pinus banksiana Lamb) pyrogenic organic matter (PyOM) (Surface, 1 cm, and 5 cm) and different heat-flux profiles (High, Low, and Control) to examine how subsequent fires affect the properties of preexisting PyOM. We measured total carbon (C), pH, dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and mineralized C (as CO₂-C, from a 12-week incubation).We found that high heat flux and/or surface placement resulted in substantial direct C losses through combustion. Intermediate heat exposure produced both combustion losses and increases in DOC and mineralizability, which may have complex long-term implications: an increased dissolved fraction of PyOM may promote downward transport into mineral soils and potentially contribute to deeper, longer-term C storage, but it may also make PyOM more susceptible to microbial decomposition. Under the lowest heat flux and deepest burial, most PyOM was retained, and changes in DOC and C mineralization were minimal. Finally, PyOM pH, an important chemical property, decreased under low-temperature heating but increased under higher temperatures.We uploaded pH data for all samples (“pH_of_all_samples.csv”); pH and temperature-related data (peak temperature and degree hours) for samples in High and Low heat-flux treatments (“pH_vs_peakT_and_degree_hours_only_for_heated_samples.csv”); total C data (“CN_pct_C_stock_C_loss_in_samples.csv”); DOC and DIC data (“doc_dic.csv”); and mineralized C (CO₂-C) data (“CO2-C_all_original.csv”). Additional details can be found in the Methods & Sampling section.All datasets uploaded to ESS-DIVE are clearly labeled, cleaned, and include both raw and derived data, ready for reuse in other analyses. All analysis code and raw datasets are also available on GitHub: https://github.com/MengmengLuo/Fire-removes-preexisting-pyrogenic-organic-matter-from-the-ecosystem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Preliminary Investigation of Target keff Search for Fuel Feed in MSRs

Fluid fuel molten salt reactor (MSR) concepts may achieve continuous-at-power operation with continuous or batch fresh fuel feed to counter reactivity loss from fuel burnup and fission product buildup. Accurate modeling and simulation of MSRs requires consideration of online fuel feed during depletion as well as a capability to determine the required feed amount to maintain a target multiplication factor (keff). As a first step supporting a full implementation of a new search capability into the SCALE code system’s TRITON reactor physics and depletion sequence, a preliminary investigation was performed to identify the best approach for a critical feed search capability considering computation time and accuracy. Using a simple iterative approach in which initial feed amounts were guessed based on previous depletion steps, the main drivers of computation time were found as the Monte Carlo neutron transport settings and the applied tolerance for the target keff. In the applied model, with tight convergence criteria (keff convergence to 8 pcm and a tolerance of ±15 pcm), the critical search calculation required twice the number of neutron transport calculations compared to a depletion calculation without critical search. In contrast, with a relaxed tolerance of ±50 pcm, the overall computation time for the critical search for merely increased by 30-40%. Further studies will be performed before implementing the critical search capability into TRITON.

Faulkner, Jonathon [ORNL]↗
DOE OSTI2023

GOOML (Geothermal Operational Optimization with Machine Learning) [SWR-23-01]

The Geothermal Operational Optimization with Machine Learning (GOOML) is a partnership between NREL and Upflow, NZ, awarded in response to the U.S. Department of Energy's Geothermal Technologies Office's Funding Opportunity Announcement (FOA) to expand the role of advanced analytics and automation in geothermal operations through machine learning. Partnering with industry (Contact Energy Limited ("Contact"), Ngati Tuwharetoa Geothermal Assets Limited ("NTGA"), Ormat Technologies Inc. ("Ormat") and Flow State Solutions Limited ("FSS"), GOOML was created to improve the operational efficiency of geothermal power plant steam fields through the analysis of historical operational data and the application of custom machine learning algorithms. NREL's contributions include machine learning, coding, and data management expertise as well as access to high-performance compute solutions. GOOML can increase geothermal operational efficiency through development of a digital system twin that can be utilized to provide optimal geothermal operating conditions for real-world geothermal fields. GOOML allows users to analyze field production histories in detail, develop models, and train machine learning algorithms to identify opportunities for increased geothermal efficiency, detect potential trouble, and allow predictive scenario modeling. Preliminary experiments have demonstrated a potential to increase total generation by as much as 12% through ML optimization of the utilization of existing steam field resources.

Buster, Grant↗
DOE OSTI2025

Prediction of neutron production and energy spectrum by the inverse kinematic reaction between an incident 7 Li 3+ beam and a proton target in PHITS

A neutron source using the inverse kinematic reaction between lithium and proton, p( 7 Li, n) 7 Be, achieves forward-directed neutrons, potentially enhancing neutron yield in the forward direction. Despite the advantage, no evaluated-cross-section data for this reaction can be used in Monte Carlo simulation codes, such as PHITS. To solve this problem, this study aims to evaluate the applicability of the user-defined cross-section data, Frag data, for p ( 7 Li, n) 7 Be in PHITS. The simulations reproduced collisions between 7 Li 3+ ions and polypropylene targets. The Frag data was edited based on the JENDL-5 by utilizing the two-body collision kinematics. The neutron yield and angular distribution were investigated in the simulation. As a result, the forward neutron convergence with a reasonable neutron yield and energy spectrum was observed. The expected neutron yield in the forward 1-steradian area is 2.46 × 10 10 n/s when lithium-ion energy and current are 16.45 MeV and 0.1 mA.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Conceptual Spacer Design for the ATR GEN I Target for Pu-238 Production in the Advanced Test Reactor at Idaho National Laboratory

The initial target design used for Pu-238 production at Idaho National Laboratory was designed by Oak Ridge National Laboratory to optimize the production of Pu-238 in the High Flux Isotope Reactor (HFIR) and are referred to as HFIR GEN II targets. To take advantage of the Advanced Test Reactor’s (ATR) taller active core region a redesign of the HFIR GEN II targets was needed. It was proposed to stack two HFIR GEN II targets nose to nose about the core center line; however, this resulted in excessive neutron and photon heating in the pellets located in the center. This peak heating was not desirable so three alternative designs were investigated for the ATR GEN I targets. The python-based code, MCNP to ORIGEN2 in Python (MOPY), was used to calculate the heating rates after 40 days of irradiation to capture the effects of each configuration. The purpose of this paper is to document the details of these conceptual design calculations and comparisons for the ATR GEN I targets.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin

This dataset is part of an effort to highlight the advantages of incorporating low-temperature (< 150 C) geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). For this Denver Basin example, resource favorability maps were created to identify potentially favorable areas for further geothermal exploration and are provided here. Favorability was based on three types of data: (1) geologic, (2) economic, and (3) risk. This raw data is also provided below. Geologic data include bottom-hole temperatures (BHT) from oil and gas wells, water co-production volumes from oil and gas wells, well groundwater levels, hot spring locations, temperatures, and chemistries, faults, and earthquakes. Economic feasibility data include population, thermal energy demand, infrastructure, and roads. Risk data (which includes data on excluded areas) include flood plains, protected lands (e.g. wildlife conservation areas, national parks). The included report describes this project in detail, covering workflows, relevant datasets, Python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The figures in this report include: maps of the original datasets; maps of transformed data and derived parameters (such as the geothermal gradient or thermal conductivity); results of uncertainty analyses; results of data completeness (using the GeoRePORT tool); examples of the data combination and processing (using the geoPFA Python library, which is introduced in the attached report); favorability maps for each criteria; and a final combined favorability map. This project is designed to facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Providing performance portable numerics for Intel GPUs

Summary With discrete Intel GPUs entering the high‐performance computing landscape, there is an urgent need for production‐ready software stacks for these platforms. In this article, we report how we enable the Ginkgo math library to execute on Intel GPUs by developing a kernel backed based on the DPC++ programming environment. We discuss conceptual differences between the CUDA and DPC++ programming models and describe workflows for simplified code conversion. We evaluate the performance of basic and advanced sparse linear algebra routines available in Ginkgo's DPC++ backend in the hardware‐specific performance bounds and compare against routines providing the same functionality that ship with Intel's oneMKL vendor library.

97 MATHEMATICS AND COMPUTING↗