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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

DOESC Remote Canister Closure System UT Inspection Couplant Solutions

The DOE Standard Canister (DOESC) Remote Canister Closure System is a remotely operated welding and inspection mechanism designed for the packaging of DOE-managed spent nuclear fuel into canisters. The ultrasonic testing (UT) inspection, included in the system, requires the use of water tanks that are opened to act as a couplant between the canister and the sensors. With the couplant, the UT inspection can guarantee accurate results determining imperfections in the weld.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2025

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗
DOE OSTI2025

THE DESIGN OF RADIAL HONEYCOMB LATTICES FOR IMPACT ENERGY ABSORPTION IN RADIOACTIVE MATERIALS PACKAGES

In this research we present a variation on the corrugation technique of honeycomb lattices, for cylindrical honeycombs, making them much easier to design for impact energy absorption in radioactive materials packages. This variation, termed radial honeycomb lattices, eliminates the residual strain and saddle effect. The use of honeycomb lattices provides advantages over the typically used foams. While foams are effective at absorbing impact energy, they can burn, their material properties are difficult to control, they can degrade over time, and procurement of raw materials can be dependent on timing of manufacturer batch runs. While the weaknesses of foam are strengths for honeycomb lattices, lattices have a different set of problems. Typically, when cylindrical honeycomb lattices are manufactured, they are manufactured flat, wrapped around a mandrel of the desired radius, and then brazed. This approach introduces residual strains, resulting in the saddle effect, which limits both the radial thickness and cylinder length. The radial honeycomb lattice approach presented here makes the design of thicker and longer cylinder honeycombs possible. To address these issues, we propose a honeycomb lattice which changes in cross-section from the inner to the outer radius of the cylinder. This causes the lattice to automatically wrap into a cylinder as it exits the corrugating gears. The theoretically bounding case, of a square cross-section at the inner radius, transitioning through a hexagon, to a diamond cross-section at the outer radius, results in a maximum thickness of approximately 41% of the inner radius. Full mathematical derivations, implemented in computer code, allow for the design of an entire radial honeycomb lattice, including the corrugating gears. To accomplish this only the radial thickness, inner cross-section shape, cell size, and nominal gear radius need to be specified, making the design of these lattices very efficient. Radial honeycomb lattice prototypes have demonstrated that the honeycomb does indeed wrap into a cylinder as intended, without the saddle effect, and can therefore be used to create thick-walled cylinders of any length. These design improvements make cylindrical honeycomb lattices much more accessible as a design element for radioactive materials packages

Johnson, William R. [Savannah River National Labor↗
DOE OSTI2022

Textile Carbon Fiber Packaging and NCF Production

This Technical Collaboration Project focused on packaging large tow (≥ 10 grams/meter) textile carbon fibers, for which currently there is no suitable method. Prior to this project, Oak Ridge National Laboratory (ORNL) used a crude packaging approach to deliver (approximately) 100-meter packages for evaluation by intermediates producers, composites fabricators and other collaborators. That packaging approach was simply a hoop wrap on a standard 75 mm (3 inch) cardboard tube, with paper interleaved between layers and little or no tension control during spooling. While this approach was very effective for initial fiber development and sample fiber and small composite sample evaluation, these packages were inadequate for larger-scale demonstrations and more extensive applications development. The paper-interleaved packages were inconsistent, wasteful, and too small for commercial utilization; they were designed as a quick and simple means to package material for delivery into prototyping operations and were never expected to satisfy industrial requirements for commercial production. This project aimed to develop a commercially relevant approach for packaging large tow textile carbon fibers for robust delivery into downstream commercial intermediates and composites production operations. The development of robust packaging equipment that delivers packages meeting industrial requirements is essential to commercial implementation. In this project, the team identified packaging requirements, created a design, and prototyped a new packaging concept at ORNL’s Carbon Fiber Technology Facility (CFTF) and resulting packages were tested in production of non-crimp fabric (NCF).

42 ENGINEERING↗
DOE OSTI2021

ARC Software Validation Work for the FFTF Reactor

Extensive efforts have been carried out at ANL for the verification and validation of the Argonne Reactor Codes (ARC) software package currently used for the design of Versatile Test Reactor (VTR). The ARC software package consists of steady state neutronics and thermal hydraulics modeling capabilities which are being used by the VTR program to develop most of the VTR reactor design details which will be part of the licensing application. It is anticipated that this software will continue to be used for the design work and for initial operations although additional software may be introduced at a later time. The validation work was focused primarily on obtaining validation data consistent with VTR and usable for the ARC software. Because no critical facilities or operating fast spectrum reactors are available to do experiments for the VTR, the next best option is to identify historical experimental data that can be used as validation data. Early on in VTR, the ZPPR-15 set of experiments was identified as good validation data because of 1) the availability and quality of the data, 2) existing staff that are already familiar with the experimental machine and measurements, 3) most of the ZPPR-15 loadings of interest have already been processed into ARC models, and 4) a full uncertainty quantification has already been done for several loadings of ZPPR-15. The FFTF startup and operations data was identified as the most consistent reactor type that has validation data usable for VTR. Finally, the EBR-II fuel depletion measurements were identified as the best available validation data for VTR. It is important to note that both the FFTF and EBR-II reactors typically come with higher uncertainties than the ZPPR. In the frame of the discussed verification and validation efforts, the present document discusses the analysis of selected FFTF measurements included in the benchmark specifications of the International Reactor Physics Experiment (IRPhE) handbook. The FFTF reactor core configurations from the benchmark specification are presented in Section 2. The analysis is performed with the use of the ARC code suite available at ANL for fast reactor studies and is discussed in Section 3. The reactor parameters from the benchmark include criticality, neutron spectra, effective delayed neutron spectra, control rod worth, isothermal temperature coefficient and low energy gamma-ray spectra. The calculated values and the comparison with the experimental data is discussed in Sections 4 to 9 for each considered reactor parameter. Finally, conclusions are presented in Section 10.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Drop Analysis of the Advanced Test Reactor Fresh Fuel Shipping Container with Heavier Low-Enriched Uranium Fuel Contents

The Advanced Test Reactor Fresh Fuel Shipping Container (ATR FFSC) is a rectangular stainless steel container used for shipping radioactive material. The container is described in the ATR FFSC Safety Analysis Report (SAR). Per the ATR FFSC SAR, the ATR FFSC is designated a Type AF-96 packaging per the definition of 10 CFR §71.4, and was originally designed to transport high enriched uranium (HEU) reactor fuel elements for the Advanced Test Reactor (ATR), the Advanced Test Reactor Critical (ATRC) facility, the Massachusetts Institute of Technology Reactor (MITR), and the University of Missouri Research Reactor (MURR). The Department of Energy, National Nuclear Security Administration’s (NNSA), Office of Material Management and Minimization (M3) is working with the Idaho National Laboratory (INL) to develop and qualify new low enriched uranium (LEU) fuels and technologies for use in the ATR, ATRC, MITR, and MURR reactors. The LEU fuel elements will weigh significantly more than the current HEU designs and, combined with their associated Fuel Handling Enclosures for packaging, some configurations will exceed the 50 lbf used in the ATR FFSC qualifying drop tests. There are LEU versions of MITR, MURR, and ATR fuel elements. However, for this evaluation, drop analysis of the ATR FFSC with only the heavier ATR Low Enrichment (LOWE) fuel element is considered in this evaluation because the LOWE fuel element is the heaviest of the considered LEU fuel elements. The ATR HEU fuel element and the ATR LOWE fuel element are identical in every design aspect except for the fuel meat inside the 19 fuel plates. The LEU fuel meats are made using a U-10Mo high-density foil rather than uranium dispersed in aluminum in the HEU fuel elements. The high density of the uranium in the LEU fuel meat increases the LOWE fuel element weight to just under 44 lbf (versus the 22.1 lbf weight of the tested ATR HEU fuel element). ATR fuel elements are placed in a thin-gauge aluminum weldment called a "Fuel Handling Enclosure" during packaging. The Fuel Handling Enclosure is used to cover and protect the element during loading and unloading operations. The ATR Fuel Handling Enclosure weighs about 15 lbf per the drawings in the ATR FFSC SAR and the weight is accounted for in this evaluation. Transporting the heavier LEU fuel elements require evaluation of two issues. The first is the effect of the increased mass of the LEU fuel elements on the survivability of the ATR FFSC package following the requisite drop qualifications. The second is the effect of the increased mass of the fuel plates on the fuel element during the same drops. The ATR FFSC containing an ATR HEU fuel element in an ATR Fuel Handling Enclosure was physically dropped multiple times to qualify the container as a Type AF-96 package. The ATR FFSC SAR describes the drop tests performed with an actual ATR HEU fuel element weighing 22.1 lbf contained in a 14.3 lbf Fuel Handling Enclosure for a total payload of 36.4 lbf. Those drop tests showed that the ATR FFSC maintained containment of the ATR HEU fuel element and the fuel element was not significantly damaged. (Containment herein is not defined as a leak tight but is retention of the radioactive contents.) The purpose of the evaluation is to analytically show that, for a similar set of tests, the ATR FFSC maintains containment of the heavier ATR LOWE fuel element and to assess the damage to the fuel element during the drops. The approach was to create finite element analysis (FEA) models that produce the same results as the physical drops. Those models were then used as the benchmarks for the follow-on analyses using the heavier contents. FEA models of the drops of ATR FFSC using up to a 115 lbf fuel element were run and evaluated. Likewise, drops of a LOWE fuel element weighing 44 lbf in the ATR FFSC were run and evaluated. It is important to note that this report was done at the quality level necessary to be included in a nuclear facility safety basis. However, it is not the intent of this report to conclude the suitability of the ATR FFSC for transporting the heavier payloads. This report only describes the results of the FEA as related to the required drop scenarios. Incorporation of the FEA into the safety basis will be evaluated by the ATR FFSC design authority. The physical drop tests of the HEU fuel element and FEA drop analysis for the LOWE fuel element showed noteworthy damage to the fuel plates. An aluminum protective block was conceived to mitigate the damage. The concept requires the blocks to be placed in the fuel element between the end boxes and fuel plates. Additional FEA drop analyses were performed using the protective block. The addition of the blocks is primarily intended to mitigate the damage to the LOWE fuel element fuel plates. However, FEA drop analyses of the ATR HEU fuel element with the blocks were also performed and included for information.

42 ENGINEERING↗
DOE OSTI2022

Residential Energy Efficiency Design Guide for Tribal Lands

Homeowners and renters on tribal lands have historically faced a disproportionate energy burden compared to the United States as a whole. The Indian Health Service (IHS), which serves these communities, strives to meet aggressive energy performance goals when constructing their residential housing. Challenges common in rural locations can hinder progress toward those goals, such as availability of materials, access to specialized labor, and budget constraints. This guide is for architects and builders who aim to incorporate energy efficiency (EE) into their residential designs. This report presents commercially viable energy efficiency packages for a variety of locations and home inputs to help guide home builders in choosing improvements for energy performance. The intention is to provide a diverse set of packages that can be used during the design phase to achieve energy savings compared to a code minimum building design. By presenting a set of diverse options with similar expected energy savings and life-cycle costs, final decisions can be left up to the building designers who can better determine the appropriate package given local costs, materials, and labor availability. Although this guide was developed for IHS projects, it can be used to help designers and construction professionals better make cost-effective choices when a detailed, project-specific building energy analysis is not possible.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling

PyApprox is a Python-based one-stop-shop for probabilistic analysis of numerical models such as those used in the earth, environmental and engineering sciences. Easy to use and extendable tools are provided for constructing surrogates, sensitivity analysis, Bayesian inference, experimental design, and forward uncertainty quantification. The algorithms implemented represent a wide range of methods for model analysis developed over the past two decades, including recent advances in multi-fidelity approaches that use multiple model discretizations and/or simplified physics to significantly reduce the computational cost of various types of analyses. An extensive set of Benchmarks from the literature is also provided to facilitate the easy comparison of new or existing algorithms for a wide range of model analyses. Here, this paper introduces PyApprox and its various features, and presents results demonstrating the utility of PyApprox on a benchmark problem modeling the advection of a tracer in groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Packages of Distributed Energy Technologies Demonstrating Demand Flexibility at Community Scale

The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

InfraSys (Infrastructure Systems) [SWR-24-42]

This package implements a data store for components and time series in support of Python-based modeling packages. While it is designed to support teams modeling transmission and distribution systems for electrical grids, it can be used by any package that needs to store components (e.g., generators and buses) that have quantities (e.g., power and voltage) which may vary over time. The package was inspired by InfrastructureSystems.jl (https://github.com/NREL-Sienna/InfrastructureSystems.jl).

Thom, Daniel↗
DOE OSTI2026

fpm-find v0.1.0

This program searches the fortran-lang community's package index (https://github.com/fortran-lang/webpage/blob/main/data/package_index.yml). The program is designed for use as a Fortran Package Manager (fpm) plugin.

Rouson, Damian [Lawrence Berkeley National Laborat↗
DOE OSTI2024

High-throughput electronic structure package

We introduce HTESP (High-Throughput Electronic Structure Package), an automated tool designed for high-throughput ab initio calculations. HTESP simplifies the entire workflow, including data extraction, input files generation, calculation submission, result collection, and plotting. The package is implemented in Python and Bash languages. In this paper, we provide detailed information about the package, its installation process and some illustrative examples to demonstrate its usage. Additionally, the package includes comprehensive online documentation on input parameters and tutorials to assist users.

Nepal, NirajK↗
DOE OSTI2022

Large-scale application of free energy perturbation calculations for antibody design

Abstract Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability. Importantly, we incorporate multiple strategies to faithfully estimate the statistical uncertainties in the FEP results. As a case study, we apply our protocols to systematically evaluate variants of the m396 antibody for their conformational stability and their binding affinity to the spike proteins of SARS-CoV-1 and SARS-CoV-2. By properly adjusting relevant parameters, the particle collapse problems in the FEP simulations are avoided. Furthermore, large statistical errors in a small fraction of the FEP calculations are effectively reduced by extending the sampling, such that acceptable statistical uncertainties are achieved for the vast majority of the cases with a modest total computational cost. Finally, our predicted conformational stability for the m396 variants is qualitatively consistent with the experimentally measured melting temperatures. Our work thus demonstrates the applicability of FEP in computational antibody design.

59 BASIC BIOLOGICAL SCIENCES↗