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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

ATRIUM{sup TM} 11 operating experience

AREVA NP developed the ATRIUM{sup TM}11 BWR fuel assembly to address the industry need for substantial improvements in fuel reliability and economic performance. The product development effort initially consisted of analytical design assessments and out-of-pile testing of prototype fuel assemblies and components. An integral component of the development project is a comprehensive in-pile demonstration program designed to fully exercise the new fuel assembly under a variety of operating conditions and to provide performance measurements of new design features. Fuel vendors, reactor operators, and regulators have successfully relied upon irradiation feedback derived from in-pile demonstration programs to safely introduce new features in reload quantities. The primary ATRIUM{sup TM} 11 in-pile demonstration program consists of 40 lead fuel assemblies (LFA) operating among five BWR reactors globally, covering the range of operational regimes and licensing environments necessary to confirm reload applications for the product. Since the initial irradiation in 2012, multiple pool-side inspection examinations have been performed. The inspection activities primarily focused on the new design features; including the spacer, fuel rod array, upper tie plate and fuel channel. These inspections have resulted in the collection of a substantial set of visual images, dimensional measurements, and performance feedback that are of general interest to the industry. Results from the inspections are compared to the database for existing products and to predetermined acceptance criteria. This paper provides details of the global in-pile demonstration program and the characteristics of the LFAs. Results of the inspection campaigns will be presented, including a summary of the technical assessment of specific new design features and the overall performance of the ATRIUM{sup TM} 11 product. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Time-Lapse Monitoring of DNA Damage Colocalized With Particle Tracks in Single Living Cells

Purpose: Understanding the DNA damage and repair induced by hadron therapy (HT) beams is crucial for developing novel strategies to maximize the use of HT beams to treat cancer patients. However, spatiotemporal studies of DNA damage and repair for beam energies relevant to HT have been challenging. We report a technique that enables spatiotemporal measurement of radiation-induced damage in live cells and colocalization of this damage with charged particle tracks over a broad range of clinically relevant beam energies. The technique uses novel fluorescence nuclear track detectors with fluorescence confocal laser scanning microscopy in the beam line to visualize particle track traversals within the subcellular compartments of live cells within seconds after injury. Methods and Materials: We designed and built a portable fluorescence confocal laser scanning microscope for use in the beam path, coated fluorescence nuclear track detectors with fluorescent-tagged live cells (HT1080 expressing enhanced green fluorescent protein tagged to XRCC1, a single-strand break repair protein), placed the entire assembly into a proton therapy beam line, and irradiated the cells with a fluence of ∼1 × 10{sup 6} protons/cm{sup 2}. Results: We successfully obtained confocal images of proton tracks and foci of DNA single-strand breaks immediately after irradiation. Conclusions: This technique represents an innovative method for analyzing biological responses in any HT beam line at energies and dose rates relevant to therapy. It allows precise determination of the number of tracks traversing a subcellular compartment and monitoring the cellular damage therein, and has the potential to measure the linear energy transfer of each track from therapeutic beams.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Hardware-Accelerated Ray Tracing of CAD-Based Geometry for Monte Carlo Radiation Transport

Monte Carlo radiation transport (MCRT) methods have been used to simulate radiation environments for many decades by tracking individual particles through a model to accumulate statistical information. MCRT geometry is historically formed using the constructive solid geometry (CSG). Recently, significant work has been performed to support simulations using computer-aided design (CAD)-based tessellated surfaces to support highly complex geometries. Ray tracing acceleration data structures from the rendering and visualization community are applied to accelerate particle tracking in CAD-based models. Despite these efforts, CSG representations provide the superior performance in surface intersection operations during particle flight. Concurrently, pseudo Monte Carlo methods have become prevalent in rendering applications to support more realistic models for scattering media, motivating innovations that are advantageous for MCRT simulations. Finally, the authors’ work extends these innovations by employing Intel’s Embree ray tracing kernel within a geometry toolkit for Monte Carlo to improve the simulation performance using CAD-based models by factors of 1.5 to 2.

42 ENGINEERING↗
DOE OSTI2024

ECP libraries and tools: An overview

The Exascale Computing Project (ECP) Software Technology and Co-Design teams addressed the growing complexities in high-performance computing (HPC) by developing scalable software libraries and tools that leverage exascale system capabilities. As we enter the exascale era, the need for reusable, optimized software solutions that can handle the unique challenges posed by these systems becomes increasingly important. The primary challenges the ECP teams faced were to create software libraries and tools that are performant on exascale architectures and portable and usable across diverse hardware platforms. Efforts addressed issues related to concurrent execution, memory management, and the integration of heterogeneous computing resources, such as GPUs from multiple vendors. The ECP’s strategy involved a structured development process encompassing the creation, optimization, and deployment of software in collaboration with industry, academia, and national laboratories. The project was organized into several technical areas: co-design of domain-specific suites with target applications, programming models and runtimes, development tools, mathematical libraries, data and visualization tools, and software ecosystem and delivery mechanisms. ECP has successfully developed a large portfolio of software libraries and tools that demonstrate significant improvements in performance and scalability on exascale systems. These products have been integrated into the Department of Energy’s computing facilities, supporting various scientific applications and ensuring robust performance across different hardware setups. ECP advancements in software development for exascale computing highlight the importance of a collaborative and adaptive approach to handling next-generation HPC systems complexities. The lessons learned emphasize the need for continuous engagement with end-users and vendors, and the importance of maintaining a balance between innovation and practical implementation. Future efforts will focus on ensuring scalability, keeping pace with rapid hardware advancements, and further enhancing the interoperability and usability of the software ecosystem. In conclusion, subsequent articles in this special issue provide in-depth discussions and case studies into specific library and tool efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Foldy: An open-source web application for interactive protein structure analysis

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. In our manuscript, we detail Foldy’s interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy’s interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

FleetREDI Dashboard Fleet DNA Data Summaries

Developing daily duty cycle summaries for every vehicle-day within NLR’s Fleet DNA database was a key output of the FleetREDI project. This project captured second-by-second GPS and controller area network (CAN) data on in-use medium- and heavy-duty fleet vehicles and then summarized the data to provide an overview of vehicle operation throughout the United States. These data summaries were then displayed in aggregated formats on the FleetREDI dashboard, where users can explore the data within Fleet DNA. Fleet DNA’s clearinghouse of commercial fleet vehicle operating data helps vehicle manufacturers and developers optimize vehicle designs and helps fleet managers choose advanced technologies for their fleets. This online tool, which provides data summaries and visualizations similar to real-world "genetics" for medium- and heavy-duty fleet vehicles, helps users understand the broad operational range of commercial vehicles across vocations and weight classes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

COVID-19, An Exercise in Data Governance at Sandia National Laboratories

In April of 2020, Sandia National Laboratories had an urgent need to identify and manage the data that could be used to create mobile applications, models, reports, and visualizations to assist management in safely bringing the workforce onsite during the COVID-19 pandemic. Multiple divisions volunteered to design and build software solutions; meanwhile, requests for new data sources, including duplicate requests, were inundating Information Technology (IT) and data owners. The Enterprise Data Governance Team was assigned to resolve obtaining and accessing new sources of data in an accelerated timeframe. Through successful collaboration with multiple stakeholders and domain owners across Sandia, the Enterprise Data Governance Team rapidly developed a centralized data strategy and solution for use in safeguarding the Sandia workforce during the COVID-19 pandemic. This foundation enabled teams to successfully develop solutions, including reports for executives and management as well as the data for modeling and scientific analysis.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Triton Field Trials - Changes in Habitats, a Literature Review of Monitoring Technologies

Marine energy devices are installed in highly dynamic environments and have the potential to affect benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats. Selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years, as well as national and international guidelines for surveying habitats around offshore activities. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Sampling designs varied considerably among the reviewed studies but transect was the predominant design for surveying seafloor, epifauna, and pelagic habitats. The most common data analyses were univariate and multivariate statistical analyses aimed at calculating and comparing biodiversity indices, characterizing faunal assemblages or sediment classes, or modeling the distribution of animals related to abiotic parameters. Technologies and sampling methods adaptable and designed to work efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A framework and tool for designing cost-effective, resilient, and circular net-zero supply chains under uncertainty with an application to multilayer plastic films

While 55% of Fortune 500 companies have committed to achieving net-zero emissions and/or zero-waste operations by 2035, only 2% are currently on track, revealing a critical gap between ambition and action. Designing supply chains that reduce both emissions and waste is a complex non-intuitive, multi-objective challenge, compounded by the high costs of new technologies and the need for resilient, profitable solutions. This paper aims to address this challenge by presenting a generic framework and multi-objective optimization formulation for designing cost-effective, circular, and resilient supply chains under uncertainty, implemented through a user-friendly decision-support tool with intuitive data visualization capabilities, enabling communication of results to both technical and non-technical stakeholders. We demonstrate the application of this framework in the context of multilayer plastic films (barrier films), which are widely used in food packaging and composite materials. The model quantifies trade-offs across three objectives: minimizing global warming potential, maximizing circularity, and minimizing cost. A key contribution of this work is the explicit modeling of technological resilience, the ability of supply chains to maintain function under disruption. In the cost-minimization case, the resilience constraint makes the design approximately three times more expensive in the short-term metric, but shifts the system from relying on a single recovery pathway to a portfolio of four recovery pathways, improving the robustness of the optimization solution under uncertainty. Lastly, we introduce TranZero, a decision-support tool that integrates material flow analysis, hotspot identification, and optimization-based scenario planning to support net-zero and circularity decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Puck Loop Seal (Final Project Technical Report)

Sandia National Laboratories (SNL) is advancing technical capabilities used in passive loop seals. The “Puck” seal used a set of International Atomic Energy Agency (IAEA) requirements for new passive loop seals published in 2020 as a design guide. The seal is based on an oxygen-sensitive inner mixture encased in an oxygen-impermeable shell, is monolithic rather than two-part, incorporates self-capturing wire features, contains colored water beads and bubbles formed during processing as unique identifiers (UIDs), and visually indicates tamper (whether from seal body penetration or from seal wire removal) by irreversibly changing the seal body from multi-colored to black. This paper will provide details on the design, development, and testing of Puck seal prototypes.

42 ENGINEERING↗
DOE OSTI2019

Real-time visualization of impact damage in monolithic silicon carbide and fibrous silicon carbide ceramic composite

Impact resistance from foreign debris is a critical requirement for brittle ceramic and ceramic composite materials intended for use in the hot-section of gas turbine engines. A design to mitigate against such impact failures necessitates a detailed understanding of the driving failure mechanisms. The present study introduces a unique time-resolved experimental method which advances the latter effort. Specifically, a pulsed synchrotron X-ray source, in phase contrast imaging (PCI) configuration, is used as a medium, to visually characterize the evolution of damage inside the target materials during impact. As a proof of concept, two types of ceramic materials were tested: monolithic silicon carbide and fibrous silicon carbide composite. Impact was performed using a light-gas gun and 1.5 mm diameter spheres of partially stabilized zirconia (PSZ) and silicon nitride (Si 3 N 4 ). The retrieved dynamic X-ray image sequences provided clear outlines of the damage features. In the case of the monolithic ceramic, the impact by a PSZ projectile initially produced a cone crack and complete failure resulted by extension of a median crack. By contrast, the fibrous composite deformed readily prior to cone crack formation. Nearly identical damage features were observed in the monolith for the Si 3 N 4 projectile, with the exception of the added vertical tensile crack. For this same projectile, the fibrous ceramic showed very limited surface deformation and enhanced cone cracking and kinking of laminates along the crack path. The latter response is attributed to the change in projectile properties. Some of the target materials were recovered, and post-mortem analysis via scanning electron microscopy (SEM) showed correlation with observed X-ray damage profiles. Furthermore, simple Hertzian contact was used to estimate damage for the elastic portion of impact. This approach was found to yield a reasonable match with experimental results for the surface displacement near the contact interface.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Visualization for Hyper-Heuristics: Back-End Processing

Modern society is faced with increasingly complex problems, many of which can be formulated as generate-and-test optimization problems. Yet, general-purpose optimization algorithms may sometimes require too much computational time. In these instances, hyperheuristics may be used. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario, finding the solution significantly faster than its predecessor. However, it may be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address these issues by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics and an easy-to-understand scientific visualization for the produced solutions. To support the development of this GUI, my portion of the research involved developing algorithms that would allow for parsing of the data produced by the hyper-heuristics. This data would then be sent to the front-end, where it would be displayed to the end user.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Thixotropic spectra and Ashby-style charts for thixotropy

There is no universal model for thixotropy, and comparing thixotropic effects between different fluids is a subtle yet challenging problem. We introduce a generalized (model-insensitive) framework for comparing thixotropic properties based on thixotropic spectra. A superposition of exponential stress modes distributed over thixotropic time scales is used to quantify buildup and breakdown times and mode strengths in response to step-change input. This mathematical framework is tested with several experimental step-shear rate data on colloidal suspensions. Low-dimensional metrics based on moments of the distribution reveal characteristic average thixotropic properties, which are visualized on Ashby-style diagrams. This method outlines a framework for describing thixotropy across a diverse range of microstructures, supporting scientific studies as well as material selection for engineering design applications.

Mechanics↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Automated setup for magnetic hysteresis characterization based on a voltage controlled current source with 500 kHz full power bandwidth and 10 A peak-to-peak current

This paper describes the design of a system for the characterization of magnetic hysteresis behavior in soft ferrite magnetic cores. The proposed setup can test magnetic materials exciting them with controlled arbitrary magnetic field waveforms, including the capability of providing a DC bias, in a frequency bandwidth up to 500 kHz, with voltages up to 32 V peak-to-peak, and currents up to 10 A peak-to-peak. In order to have an accurate control of the magnetic field waveform, the system is based on a voltage controlled current source. The electronic design is described focusing on closed loop feedback stabilization and passive components choice. The system has real-time hysteretic loop acquisition and visualization. The comparisons between measured hysteresis loops of sample magnetic materials and datasheet available ones are shown. Results showing frequency and thermal behavior of the hysteresis of a test sample prove the system capabilities. Moreover, the B-H loops obtained with a multiple waveforms excitation signal, including DC bias, are reported. The proposal is a low-cost and replicable solution for hysteresis characterization of magnetic materials used in power electronics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗