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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 1,585 records · Page 88

Structural Health Monitoring: Using an Autoencoder to Identify Damage in a Bolted Joint [Capstone Project]

Los Alamos National Laboratory (LANL) is an important fixture in the United States Department of Energy’s (DOE) National Nuclear Security Agency (NNSA) complex. LANL is one of the largest national laboratories in the country, and the laboratory’s primary mission is to support the nation’s nuclear stockpile. The lab functions as a design agencies for the NNSA and performs extensive testing on weapons as part of that mission. The shock and vibration test team at LANL utilizes electrodynamic shaker systems for important qualification testing in support of the laboratory’s mission. Modern engineering relies heavily on bolted joints to connect two objects. During these shaker tests, engineers depend on bolted joints to secure the test article to a fixture and the fixture to the table. The test article may be hazardous and contain high explosives which could create a safety issue if a bolted joint failed. A loss of preload in a bolt will affect the way energy is input to the system and may introduce nonlinearities as the joint opens and closes. The loss of preload can create challenges controlling the test and make acquired signals useless. Being able to monitor preload within bolted joints during testing can improve the quality of the data and keep workers safe.

42 ENGINEERING↗

IHE DDT Qualification Tests (FY2020-FY2021)

A DDT tube test was designed to meet all requirements established in the new DOE IHE qualification standard. Ten tests were successfully executed with PBX 9502 as a demonstration of the design, assembly, heating system, and methods, and to establish a baseline set of test results with an existing IHE. The explosive response in all tests was low violence (as anticipated). This report contains detailed design drawings, assembly instructions and procedures for future execution of the qualification test series, and makes recommendations for minor improvements.

42 ENGINEERING↗

Electrochemically Stable High Energy Density Lithium-Sulfur Batteries

Lithium-Sulfur batteries (LSB) have emerged as one of the strong contenders for high energy density rechargeable batteries in the Li-ion battery domain. The LSB system is considered as the most promising to achieve the next milestone in energy density of 500 Wh/kg. However, the LSB system is plagued with problems of polysulfide formation which are soluble in the organic electrolyte leading to loss in capacity and eventual cell failure. The problem is further compounded by dendrite formation on the Li anode during electrochemical cycling leading to puncturing of the separator causing eventual short-circuiting of the cell and consequent heat generation resulting in major safety hazards of flammability of the organic liquid electrolyte and impending explosion. This chapter describes various approaches developed to combat both cathode and anode issues. These involve synthesis and characterization of complex framework materials (CFMs) for confining the polysulfides and sulfur in the LSB cathodes. The CFMs include a CFM host and a coating applied to the CFM host, which includes one or more form of an electronic conductor, a lithium-ion conductor and a functional electrocatalyst for electrocatalytically converting the soluble polysulfides to Li 2 S. Further, sulfur is infiltrated into the CFM host creating a sulfur-carbon linkage serving as effective anchors for trapping the ensuing polysulfides. The systems have been tested in coin cells and pouch cells with metallic Li anodes under lean electrolyte conditions of 3-4 μl/mg of electrolyte (E) to sulfur (S) ratios showing promise and feasibility. New emergent dendrite-free alloys have also been identified to test against pure Li and CFM cathodes in coin cell and pouch cell configurations under lean electrolyte conditions. Results of these studies are described and discussed with thoughts on future directions.

25 ENERGY STORAGE↗

Applying Waveform Correlation and Waveform Template Metadata to Aftershocks in the Middle East to Reduce Analyst Workload

Organizations that monitor for underground nuclear explosive tests are interested in techniques that automatically characterize recurring events such as aftershocks to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is a technique that is effective in finding similar waveforms from repeating seismic events. In this study, we apply waveform correlation in combination with template event metadata to two aftershock sequences in the Middle East to seek corroborating detections from multiple stations in the International Monitoring System of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization. We use waveform templates from stations that are within regional distance of aftershock sequences to detect subsequent events, then use template event metadata to discover what stations are likely to record corroborating arrival waveforms for recurring aftershock events at the same location, and develop additional waveform templates to seek corroborating detections. We evaluate the results with the goal of determining whether applying the method to aftershock events will improve the choice of waveform correlation detections that lead to bulletin-worthy events and reduction of analyst effort.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Position Papers for the ASCR Workshop on the Management and Storage of Scientific Data

The purpose of this workshop is to identify priority research directions in the area of data management for high-performance and scientific computing above and beyond HPC’s traditional "the parallel file system is the data-management system" model. Supporting the breadth of the DOE mission, including the explosion of AI uses and the growing needs of experimental and observational science, motivates revisiting our assumptions about data management. There are many facets of this topic to explore including: (1) Interfaces for accessing data that resides on traditional persistent storage as well as memory devices; (2) Storage-system architecture design that supports scientific workflows on varied hierarchical storage and networking devices; (3) Devising metadata management infrastructure to support FAIR principles (Findability, Accessibility, Interoperability, and Reusability); (4) Capturing provenance information about scientific data; (5) Utilizing AI to learn I/O patterns of emerging workloads for efficient data management; (6) Providing data management support for AI and complex workflows; and (7) Understanding the overlap between traditional storage systems and I/O (SSIO) efforts and data management. While the program committee has identified these topics as important areas for discussion, we welcome position papers from the community that propose additional topics of interest for discussion at the workshop. The workshop agenda will include breakout sessions for discussing these and selected topic areas to inform priority research directions for data management for high-performance and scientific computing.

97 MATHEMATICS AND COMPUTING↗

Applying Waveform Correlation and Waveform Template Metadata to Mining Blasts to Reduce Analyst Workload

Organizations that monitor for underground nuclear explosive tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high - quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. In this study we use waveform template event metadata to seek corroborating detections from multiple stations in the International Monitoring System of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization. We build upon events detected in a prior waveform correlation study of mining blasts in two geographic regions, Wyoming and Scandinavia. Using a set of expert analyst-reviewed waveform correlation events that were declared to be true positive detections, we explore criteria for choosing the waveform correlation detections that are most likely to lead to bulletin-worthy events and reduction of analyst effort.

47 OTHER INSTRUMENTATION↗

Analysis of Experimental Shock Propagation through a Diverse Set of Geometric Cavities Embedded in Lab-Scale Polymer Cubes

Experiments were designed and conducted to investigate the impact that geometric cavities have on the transfer of energy from an embedded explosion to the surface of the physical domain. The experimental domains were fabricated as 3-inch polymer cubes, with varying cavity geometries centered in the cubes. The energy transfer, represented as a shock wave, was generated by the detonation of an exploding bridgewire at the center of the cavity. The shock propagation was tracked by schlieren imaging through the optically accessible polymer. The magnitude of energy transferred to the surface was recorded by an array of pressure sensors. A minimum of five experimental runs were conducted for each cavity geometry and statistical results were developed and compared. Results demonstrated the decoupling effect that geometric cavities produce on the energy field at the surface.

36 MATERIALS SCIENCE↗

SuiteGoo [Slides]

SuiteGoo is a liquid product used to detect "undetectable" material traces. It is used when you need to improve detection limits, anywhere where cotton swiping is used, and anywhere where cotton swiping fails. It is also used by law enforcement to find DNA from fingerprints, used by health care to detect the presence of viruses and bacteria, used by emergency response to detect explosive traces, and used by environmental management to detect pollutant traces.

54 ENVIRONMENTAL SCIENCES↗

Management and Storage of Scientific Data

Scientific discoveries rely heavily on efficient access, search, and management of massive data sets. Data management technologies have, for decades, provided foundational capabilities for scientific computing. Just as storage, input/output (I/O), and data management have been fundamental to simulation-based science for many years, so too are capable data-management technologies key to the success of today’s scientific workflows utilizing data intensive and machine learning (ML) techniques. The Department of Energy, Office of Science, Advanced Scientific Computing Research (ASCR) program has invested broadly in data-management research focused on high-performance computing (HPC) systems, from parallel file systems that store data to application software that makes these systems more productive. Still, advances in technology combined with growing diversity of supported science strongly motivate continued investment in this area. In January 2022, ASCR convened a workshop to identify priority research directions in the area of data management for high-performance and scientific computing. Attendees were challenged to identify promising approaches that would support the breadth of the DOE mission, including the explosion of artificial intelligence (AI) uses and the growing needs of experimental and observational science. Technological and science drivers were identified and considered as they relate to key aspects of data management such as interfaces, architectural design, and FAIR principles (Findable, Accessible, Interoperable, and Reusable). The thoughts of the workshop participants were distilled into a set of four priority research directions with the potential for high impact on DOE science. These research directions are summarized in the following pages.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Report for the ASCR Workshop on the Management and Storage of Scientific Data

The purpose of this workshop is to identify priority research directions in the area of data management for high-performance and scientific computing above and beyond HPC’s traditional "the parallel file system is the data-management system" model. Supporting the breadth of the DOE mission, including the explosion of AI uses and the growing needs of experimental and observational science, motivates revisiting our assumptions about data management. There are many facets of this topic to explore including: (1) Interfaces for accessing data that resides on traditional persistent storage as well as memory devices; (2) Storage-system architecture design that supports scientific workflows on varied hierarchical storage and networking devices; (3) Devising metadata management infrastructure to support FAIR principles (Findability, Accessibility, Interoperability, and Reusability); (4) Capturing provenance information about scientific data; (5) Utilizing AI to learn I/O patterns of emerging workloads for efficient data management; (6) Providing data management support for AI and complex workflows; and (7) Understanding the overlap between traditional storage systems and I/O (SSIO) efforts and data management. While the program committee has identified these topics as important areas for discussion, we welcome position papers from the community that propose additional topics of interest for discussion at the workshop. The workshop agenda will include breakout sessions for discussing these and selected topic areas to inform priority research directions for data management for high-performance and scientific computing.

97 MATHEMATICS AND COMPUTING↗

Visualization for Scientific Discovery, Decision-Making, and Communication

Visualization–the use of visual elements to explore data, form hypotheses, or convey conclusions–is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes to the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality and AI, visualization has become increasingly essential but also ever more challenging. Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing, with a special focus on DOE-relevant applications and goals. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision-making, and communication.

97 MATHEMATICS AND COMPUTING↗

Report for the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication

Visualization—the use of visual elements to explore data, form hypotheses, or convey conclusions—is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes for the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality (VR) and artificial intelligence (AI), visualization has become increasingly essential but also ever more challenging. The Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing as well as for DOE-relevant applications and goals in general. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision making, and communication. The first three PRDs describe interconnected research themes addressing the need for new techniques to deal with complex data, uncertainty, and interpretability (PRD 1); the need for scalable and interoperable software stacks (PRD 2); and the challenges and opportunities inherent in new technologies, such as VR, cloud, or exascale computing (PRD 3). The remaining two PRDs describe foundational research themes that recognize the potential of visualizations to provide equitable access to information and to strengthen the scientific discourse (PRD 4); and the need to consider human factors when designing visualizations (PRD 5). Collectively, these PRDs form the pillars for a coherent, long-term research and development strategy in Visualization for Scientific Discovery, Decision-Making, and Communication in the context of the Office of Science’s mission scope.

97 MATHEMATICS AND COMPUTING↗

Global Security & Strategic Partnerships Programs

Serving the Nation: Our Missions include Providing the Nuclear Deterrent for our Nation and Allies; Leading Nuclear Nonproliferation and Counterterrorism / Counterproliferation efforts to make the world a safer place; Supplying Enriched Uranium Material for Reactors – Naval Propulsion, Army, NASA, Universities, Isotope Production Reactors; Providing High Explosives for the Stockpile and Strategic Partners; Delivering Solutions – Solve emerging national security challenges

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Operation Teapot

As part of Operation Teapot, reporter Joan Collin came to the Nevada Test Site in early May 1955 to narrate a Federal Civil Defense Administration motion picture film on the explosive and radioactive effects of a nuclear detonation on food supplies, houses, communication systems, and energy sources. After watching efforts to feed the many people involved in test site activities, Collin asked the question of how to mass feed people after a nuclear attack. She was one of the few persons perceptive enough to recognize the significance of this issue.

99 GENERAL AND MISCELLANEOUS↗

Advanced Inversion Algorithms for Scientific Data Analysis [Slides]

Accurate subsurface characterization is crucial for all subsurface energy exploration. Accurate characterization of uncertain subsurface properties is also critical for monitoring storage of CO 2 , estimating pathways of subsurface contaminant transport, and monitoring potential nuclear explosions for treaty verification. This research will advance our world-leading subsurface sensing capabilities that are crucial for LANL missions in energy security (geothermal energy, oil/gas resource exploration, geologic carbon storage) and nuclear security (facility monitoring, detonation detection).

47 OTHER INSTRUMENTATION↗

Surface Roughness Calculations of Additively Manufactured Cylinders via X-Ray Computed Tomography

X-ray Computed Tomography (X-ray CT) is an analytical technique used in materials science to non–destructively characterize features in variety of materials like polymers, metals, composites, and explosives. It also has the capability of imaging additively manufactured, machined and assembled parts and processes. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of material characteristics. Additionally, X-ray CT can obtain accurate measurements of dimensional and topographic variations as a result of different stimuli, and assess accuracy of material production. This study will focus on parts manufactured via metal additive manufacturing (AM). Although, AM produces parts faster and easier, the printing process can produce defects (pores and surface roughness) that undermine the part’s mechanical properties. The analysis of 3D printed objects has a strength in analysis in that the material has an STL file from which the item was printed, which is not available in many manufactured materials (i.e. foams) due to stochastic structures. For this study, the print accuracy of several 3D printed cylinders will be assessed via X-ray CT to determine optimal printing parameters for parts with less defects and stronger mechanical properties. This will be accomplished by having the original STL file serve as the baseline surface to compute difference in the CT rendering to calculate surface roughness for each cylinders.

36 MATERIALS SCIENCE↗