Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Website Development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

Efficient computational design of two-dimensional van der Waals heterostructures: Band alignment, lattice mismatch, and machine learning

Here, we develop a computational database, website applications (web-apps), and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D) heterostructures. Using density functional theory (DFT) based lattice parameters and electronic band energies for 674 nonmetallic exfoliable 2D materials, we generate 226 779 possible bilayer heterostructures. We classify these heterostructures into type-I, -II, and -III systems according to Anderson’s rule, which is based on the relative band alignments of the noninteracting monolayers. We find that type II is the most common and type III the least common heterostructure type. We subsequently analyze the chemical trends for each heterostructure type in terms of the Periodic Table of constituent elements. The band alignment data can also be used for identifying photocatalysts and high-work-function 2D metals for contacts. We validate our results by comparing them to experimental data as well as hybrid-functional predictions. Additionally, we carry out DFT calculations of a few selected systems (MoS 2 /WSe 2 , MoS 2 /h-BN, and MoSe 2 /CrI 3 ), to compare the band-alignment description with the predictions from Anderson’s rule. We develop web-apps to enable users to virtually create combinations of 2D materials and predict their properties. Additionally, we use ML tools to predict band-alignment information for 2D materials. The web-apps, tools, and associated data will be distributed through the JARVIS-HETEROSTRUCTURE website. Our analysis, results, and the developed web-apps can be applied to the screening and design applications, such as finding alternative photocatalysts, photodetectors, and high-work-function (WF) 2D-metal contacts.

2-dimensional systems↗

Standardizing UI/UX across accelerator labs

During February 26–28, 2025, the first-ever particle accelerator user interface/user experience (UI/UX) workshop was held at SLAC. Attendees had backgrounds ranging from software development to control systems management and human factors (HF) science. The workshop began with participants discussing the current state of UI/UX procedures and practices at their respective laboratories to share experiences and learn from one another. Additional discussions focused on how to effectively integrate UI/UX best practices into actionable goals for developers, managers, and operators when working on new or existing interfaces. The goal of the working group is to create a website that will guide developers, managers, scientists, and end users at accelerator laboratories in incorporating UI/UX best practices into software development. The working group continues to meet virtually toward this goal, and is planning a second workshop for next year.

Tran, Tiffany [SLAC]↗

Sun Grant/DOE Regional Feedstock Partnership: Final Technical Report

The U.S. Department of Energy (DOE) and the Sun Grant Initiative initiated the Regional Feedstock Partnership (referred to as the Partnership) in 2007 primarily to address information gaps associated with the likelihood for realization of the sustainable and reliable production of a billion-tons of biomass annually to support the U.S. bioenergy industry by the year 2030. Publication of The Technical Feasibility of a Billion-Ton Annual Supply (Perlack et al., 2005) in 2005, with its associated yield assumptions, led to the realization that the yield goals and assumptions utilized in that analysis required careful validation. To achieve the overall goal of validating key yield assumptions, the following objectives were developed: 1. Establishment of replicated field trials across regions to determine the impact of crop residue removal (primarily corn and small grains) on future grain yields and soil health. 2. Establishment of replicated field trials of some of the most promising dedicated energy crops (herbaceous annuals and perennials, as well as woody perennials) to demonstrate the potential performance of these feedstocks across the U.S. 3. Assessment of feedstock resources to be used to estimate a sustainable national supply potential. Teams composed of representatives from Land Grant Universities, USDA ARS, DOE National Laboratories, industry, and other federal agencies were identified and assembled to address each of these objectives. For Objective 1, members of the USDA ARS’ Resilient Economic Agricultural Practices (REAP) team combined with university personnel to leverage on-going work and established new trials to determine sustainable corn residue removal rates. In addition, universities across the continental U.S. conducted surveys of published past research to define parameters for the use of cereal grain residue (primarily wheat) as a biomass feedstock. For Objective 2, and based on input from DOE, USDA, Land Grant university scientists, and others, several herbaceous and woody energy crop species were selected for new or further evaluation across wide geographic areas as cellulosic feedstock sources. Species teams were organized to assess the yield potential of candidate herbaceous feedstocks including sorghum, energycane, Miscanthus x giganteus (hereafter referred to as miscanthus), switchgrass, and mixed perennial species (primarily grasses and some legumes) on Conservation Reserve Program (CRP) land. Woody species will be critical components of the bioenergy sector; therefore, species teams were also organized for shrub willow and hybrid poplar (Populus spp.). Field trials of each species were utilized to determine yield potential across the U.S. For Objective 3, a GIS resource team was organized with representatives from each of the five Sun Grant regions. While some regional assessments were made, the multi-institutional team decided that the group from Oregon State University would utilize their PRISM ELM model to estimate national yield potential of the various species evaluated. The following are key outcomes and impacts • The Partnership demonstrated the production potential of diverse herbaceous and woody feedstocks across much of the U.S. for 5-7 consecutive growing seasons. Long-term studies such as this are not commonly possible due to limitations in funding cycles. • Long-term field trials were valuable in demonstrating the importance of agronomic management practices and genetic resources to yield of sorghum, switchgrass, miscanthus, energycane, CRP mixed perennial grasses, poplar, and willow. • National yield potential maps were developed for all species evaluated in the Partnership. • Sustainable corn stover removal rates were quantified for use by producers, harvesters, and commercial lignocellulosic biorefineries. • Data from the Partnership field trials not only validated initial Billion Ton estimates, but were instrumental in developing both the Billion Ton Update in 2011, and especially the 2016 Billion Ton Report. • The Partnership provided the opportunity to assemble and conserve a poplar germplasm collection that contains more than 20,000 clones for use in breeding programs. New clones resulting from crosses made using this germplasm collection have resulted in significantly improved cultivars that could be scaled up and deployed. • Further validation of improved yields of new varieties/cultivars of biomass sorghum, energycane, hybrid poplars, and shrub willows was produced by the Partnership. • The Partnership demonstrated the potential of energycane in northern parts of the southeastern U.S., particularly in relation to sugarcane varieties. • For certain feedstocks (e.g., CRP mixed grasses, switchgrass, willow, and poplar), production economics were ascertained through Partnership field trials. • Biomass samples collected as part of the Partnership are also being used to populate Idaho National Laboratory’s Bioenergy Feedstock Library. • Because of the size and scope of the Partnership, workforce development was a key component and outcome. Numerous undergraduate students (25), graduate students (15 MS and 8 PhD), and postdoctoral researchers (7) were trained by Partnership participants. This will help to prepare individuals for careers in the emerging fields of plant breeding, biomass production, feedstock supply logistics, and biomass conversion processes. • More than 130 scientific publications have been authored by Partnership team members. Numerous other presentations, outreach publications, book chapters, and websites have also been developed to further the continued development of the bioeconomy.

09 BIOMASS FUELS↗

NREL 25-cm2 High-Pressure Low-Temperature Electrolysis Cell Hardware (Open Source)

This data resource describes an open-source cell hardware that enables low temperature electrolysis (LTE) testing at elevated pressures. Existing commercial options have several downsides when it comes to R&D testing. They are often not designed for repeated reassembly, may not be able to accommodate porous transport layers with different thicknesses, and do not give state-of-the-art performance. Therefore, this hardware was developed specifically with LTE R&D in mind and its design is being made available to the global LTE community. This work was planned and funded by the U.S. Department of Energy's H2NEW consortium (https://h2new.energy.gov/). The hardware design package (.zip file) details the drawings, auxiliary materials, and procedures required to fabricate, assemble, and operate the National Renewable Energy Laboratory's (NREL's) high-pressure low-temperature electrolysis cells. While the hardware itself—end plates, current collectors, flow fields, bolts and washers, tube fittings—is always the same, the assembly and operating procedures may change depending on the active materials being tested, especially for the membrane. Material-specific assembly and operating procedures will be posted to the H2NEW website as they are developed and validated. Disclaimer: The documents and drawings included in this download package describe a design for a low temperature electrolysis hardware that is intended to comply with leak testing according to ASME B31.1. Safe operation at ambient and elevated pressures is the sole responsibility of the end user, which should be evaluated on a case-by-case basis for each individual cell. Factors affecting the sealing capability may depend on, for example, machining quality, cell assembly components, operating conditions, and operating history. Operation at pressure should only be performed on qualified test stands by qualified operators. NREL/ALLIANCE FOR SUSTAINABLE ENERGY, LLC/DOE DISCLAIM ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING THE WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, AND MAKES NO WARRANTY AS TO THE ACCURACY, COMPLETENESS, OR USEFULNESS OF ANY INFORMATION PROVIDED HEREIN. USE OF THIS PACKAGE IS AT THE USER’S OWN RISK.

08 HYDROGEN↗

SAM Software Quality Assurance Plan Implementation and NQA-1 Assessment

The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. As a modern-day software, SAM development included efforts to follow best practices in software development. These best practices include version control using git, independent reviews of development activities, and detailed descriptions of developments and bug fixes using the GitLab issue and merge request system. In Fiscal Year 2023 (FY23), the SAM development team set out to formalize a Software Quality Assurance (SQA) program that allowed industry partners to credit the informal steps being taken by the SAM development team to ensure the quality of the software. As part of formalizing an SQA program, a SQA Plan (SQAP) was developed, implemented, and assessed. The SAM SQAP targets compliance with NQA-1-2008/2009 Addenda. The SQAP builds on the MOOSE SQAP and the Argonne SSQAPP while accounting for the needs of the multi-organization SAM development team. Modifications to the SAM repository structure, including a new testing system, updated test cases, and the development of an internal website, facilitate the implementation of the SAM SQAP. The initial assessment of the SAM SQAP indicated that the SAM SQAP was adequately and effectively implemented and additional work was required to improve the compliance of the SAM SQAP with NQA-1 2008/2009 Addenda. Several improvements to the SQAP have already been drafted to address these assessments and future work is planned to further improve the SAM SQAP in support of end-user needs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Alternative Fuels Data Center

This presentation provides an overview of the Alternative Fuels Data Center for the 2026 Transportation Technologies Annual Merit Review, including project objectives, milestone, approach to developing and maintaining the website, project accomplishments and progress, and collaboration with other national labs and external partners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Educational Consortium for Energy-related Data Science & Computation in Building Engineering Programs

The project spearheaded by Pennsylvania State University aims to address the growing need for integrating energy-focused computation and data science into building engineering education. As the demand for energy-efficient building designs and operations increases, the educational sector must adapt to equip future engineers with the necessary skills. This initiative responds to this need by developing a consortium that unites multiple institutions to enhance curriculum development, dataset curation, and resource sharing, thereby ensuring students are well-prepared for the evolving energy sector. The primary goal of the project is to establish a consortium that will develop and disseminate educational materials and training programs focused on energy-related data science and computation. Key accomplishments include the creation of a beta website for resource sharing, the development of training programs and standalone modules, and the curation of datasets accessible to the public. This effort will culminate in a curriculum that incorporates advanced modeling technologies and data science skills into building engineering programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multimedia Solar Knowledge Library

The GW Solar Institute Multimedia Solar Knowledge Library has been a success. A Google search of “solar training library” brings our website (www.solar.gwu.edu) up as the first result. Our videos have been viewed over 8,000 times and downloaded more than 100 times since we started posting them in the summer of 2017 and these numbers only continue to increase. We have completed and published all thirteen of our videos, all of which have extremely high production value given the budget for this project. We have also completed the development of our second new website to host the videos as well as Phase II material, and uploaded all Phase II material from NREL. This site will serve as a hub for all things solar, from reports to webinars to fact sheets. The videos exist not only on this site but also on the website of our STEP partners where they are exposed directly to our target audiences. On our website there are approximately 50 previously unorganized webinars from NREL as well as over one hundred other resources, (also previously unorganized), broken up into 15 categories so students, researchers, solar employees, and members of the public can become experts on their own time without having to source or ask permission to access these resources themselves. NREL concluded its internal search for additional material that was not publicly accessible and we uploaded this new material to the Phase II website as well. Our videos have already been viewed around the world and our instructional films continue to be viewed and downloaded for probable use in classrooms and by industry professionals. We have been the most popular in California, and we are glad that the state at the vanguard of the solar industry has clearly found our resources valuable.

14 SOLAR ENERGY↗

ComStock™ 2024 Release 1 [SWR-19-33 and SWR-20-32]

ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics. This repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository. Execution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers. The dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website. ComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software. is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.

Horsey, Henry↗

An updated gene atlas for maize reveals organ-specific and stress-induced genes

Maize (Zea mays L.), a model species for genetic studies, is one of the two most important crop species worldwide. The genome sequence of the reference genotype, B73, representative of the stiff stalk heterotic group was recently updated (AGPv4) using long-read sequencing and optical mapping technology. To facilitate the use of AGPv4 and to enable functional genomic studies and association of genotype with phenotype, we determined expression abundances for replicated mRNA-sequencing datasets from 79 tissues and five abiotic/biotic stress treatments revealing 36 207 expressed genes. Characterization of the B73 transcriptome across six organs revealed 4154 organ-specific and 7704 differentially expressed (DE) genes following stress treatment. Gene co-expression network analyses revealed 12 modules associated with distinct biological processes containing 13 590 genes providing a resource for further association of gene function based on co-expression patterns. Presence–absence variants (PAVs) previously identified using whole genome resequencing data from 61 additional inbred lines were enriched in organ-specific and stress-induced DE genes suggesting that PAVs may function in phenological variation and adaptation to environment. Relative to core genes conserved across the 62 profiled inbreds, PAVs have lower expression abundances which are correlated with their frequency of dispersion across inbreds and on average have significantly fewer co-expression network connections suggesting that a subset of PAVs may be on an evolutionary path to pseudogenization. Here, to facilitate use by the community, we developed the Maize Genomics Resource website (maize.plantbiology.msu.edu) for viewing and data-mining these resources and deployed two new views on the maize electronic Fluorescent Pictograph Browser (bar.utoronto.ca/efp_maize).

59 BASIC BIOLOGICAL SCIENCES↗

Data from: An updated gene atlas for maize reveals organ-specific and stress-induced genes

Maize(Zea mays L.), a model species for genetic studies, is one of the two most important crop species worldwide.The genome sequence of the reference genotype, B73, representative of the stiff stalk heterotic group was recently updated (AGPv4) using long‐read sequencing and optical mapping technology. To facilitate the use of AGPv4 and to enable functional genomic studies and association of genotype with phenotype, we determined expression abundances for replicated mRNA‐sequencing datasets from 79 tissues and five abiotic/biotic stress treatments revealing 36,207 expressed genes. Characterization of the B73 transcriptome across six organs revealed 4,154 organ‐specific and 7,704 differentially expressed genes following stress treatment. Gene co‐expression network analyses revealed 12 modules associated with distinct biological processes containing 13,590 genes providing a resource for further association of gene function based on co‐expression patterns. Presence/absence variants (PAVs) previously identified using whole genome resequencing data from 61 additional inbred lines were enriched in organ‐specific and stress‐induced differentially expressed genes, suggesting PAVs may function in phenological variation and adaptation to environment. Relative to core genes conserved across the 62 profiled inbreds, PAVs have lower expression abundances which are correlated with their frequency of dispersion across inbreds and on average, have significantly fewer co‐expression network connections suggesting that a subset of PAVs may be on an evolutionary path to pseudogenization. To facilitate use by the community, we developed the Maize Genomics Resource website(maize.plantbiology.msu.edu) for viewing and data‐mining these resources and deployed two new views on the Maize electronic Fluorescent Pictograph Browser (bar.utoronto. ca/efp_maize)

59 BASIC BIOLOGICAL SCIENCES↗

A Collaboration Website for Muon Catalyzed Fusion and Muon Beam Production

This project sets up a website to support the nascent Muon Catalyzed Fusion collaboration including development of particle accelerators and transport beamlines for muon beams. The website is envisioned as having the general public information pages and private pages for collaboration members. Multimedia elements like images, text animations, and video lectures, covering a broad spectrum of topics will populate the educational site, covering muon facilities, to comprehensive explorations and seminal documents that define the science of Muon Catalyzed Fusion, Acceleration, Applications, Instrumentation, Beamline Design, and beam dynamics design codes. Ensuring compatibility across devices and operating systems, it also features integration with Google Docs for collaboration, a code repository (GitHub), a blog platform with comments (WordPress), the potential for ChatGPT integration and interactive graph plotting with Python Plotty to enhance data visualization. This project will maintain public and protected private pages, due to the proprietary nature of the work or research in progress. The public sections will be built to foster dissemination of information and highlight recent work within the NK Labs collaboration, including lectures, published papers, and regular blog posts with open commenting. The private section will support unpublished or nonpublic research, by facilitating collaborative efforts through integrated Google Docs and Python Plotty for shared graphing work. Ultimately, this project strives to make complex scientific knowledge more accessible to the public, foster enhanced collaboration, and serve as a platform for sharing cutting-edge research in Muon Catalyzed Fusion and Accelerators.

43 PARTICLE ACCELERATORS↗

Laboratory Directed Research and Development Program (FY 2019 Annual Summary of Completed Projects)

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory with distinctive capabilities in neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission to “ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) program. Information about the laboratory and its programs is available at the ORNL website. The Laboratory Directed Research and Development (LDRD) program at ORNL operates under the authority of the DOE Order 413.2C, “Laboratory Directed Research and Development,” which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD program funds are obtained through a charge to all laboratory programs. ORNL reports on the program status to DOE each year.

99 GENERAL AND MISCELLANEOUS↗

Laboratory Directed Research and Development Program: FY 2023 Completed Projects Report

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website. The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of the DOE Order 413.2C, Laboratory Directed Research and Development, which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and to enhance its ability to conduct cutting-edge R&D. This report provides an overview of the LDRD Program at ORNL in FY 2023 and contains summaries of all the LDRD research projects that concluded between October 1, 2022, and September 30, 2023.

99 GENERAL AND MISCELLANEOUS↗

Laboratory Directed Research and Development Program: FY 2024 Completed Projects Report

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website. The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of DOE Order 413.2C, Laboratory Directed Research and Development,3 which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and to enhance its ability to conduct cutting-edge R&D. In accordance with the DOE order, R&D projects funded through the LDRD Program at ORNL support the goals of • maintaining the scientific and technical vitality of the laboratory; • enhancing the laboratory’s ability to address future DOE missions; • fostering creativity and stimulating exploration of forefront areas of science and technology; • serving as a proving ground for new concepts in R&D; and • supporting high-risk, potentially high-value R&D. This report provides an overview of the LDRD Program at ORNL in FY 2024 and contains summaries of all the LDRD research projects that concluded between October 1, 2023, and September 30, 2024.

99 GENERAL AND MISCELLANEOUS↗

Laboratory Directed Research and Development Program: FY 2025 Completed Projects

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website. The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of DOE Order 413.2C, Laboratory Directed Research and Development, which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and enhance its ability to conduct cutting-edge R&D. In accordance with the DOE order, R&D projects funded through the LDRD Program at ORNL support the goals of • maintaining the scientific and technical vitality of the laboratory, • enhancing the laboratory’s ability to address future DOE missions, • fostering creativity and stimulating exploration of forefront areas of science and technology, • serving as a proving ground for new concepts in R&D, and • supporting high-risk, potentially high-value R&D. This report provides an overview of the LDRD Program at ORNL in FY 2025 and contains summaries of all the LDRD research projects that concluded between October 1, 2024, and September 30, 2025.

99 GENERAL AND MISCELLANEOUS↗

Comparison Study of Upper Subcritical Limits Derived Using Sensitivity/Uncertainty Tools Case Studies of Benchmarks and Applications

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP ® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. The initial comparison involves four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been: 1. modeled independently by LANL, IRSN, and ORNL based upon information provided in the ICSBEP Handbook, 2. are common in S/U libraries for LANL, IRSN, and ORNL, 3. span a range of energy spectrum and fissile material, and 4. taken as applications for the purposes of this study and therefore excluded from use as a benchmark for calculating the upper subcritical limit. Results presented in this paper have been computed using covariance data for all isotopes in ENDF/BVII.0 using a 44-group energy structure. Benchmarks in the Whisper library were run in MCNP6.2 using 100,000 neutrons per cycle, skipping 100 cycles for 500 active cycles. Reference 10 also compares the results for baseline USL with an order of magnitude greater neutrons, using the same total number of cycles with 1,000,000 neutrons per cycle. Subsequent to the results presented in Reference 10 changes were made to the benchmark library, as discussed in Reference 11. Newer results using the revised benchmark library are presented herein.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Comparison Study of Upper Subcritical Limits Derived Using Sensitivity/Uncertainty Tools: Case Studies of U233-SOL-THERM-001-001, MIX-COMP-THERM-001-001, IEU-MET-FAST-002-001, LEU-COMP-THERM-001-001, LEU-SOL-THERM-004-001

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2 [References 3-5]. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. An initial comparison involved four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been documented in References 10-13. This study extends the comparison to include cases U233-SOL-THERM-001-001, MIX-COMP-THERM-001-001, IEU-MET-FAST-002-001, LEU-COMP-THERM-001-001, LEU-SOL-THERM- 004-001.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗