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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 163 records · Page 9

PROTEUS: Machine Learning Driven Resilience for Extreme-scale Systems

The objective of this project is to design, develop, and evaluate scalable software to enhance resilience, data checkpointing, program restart, and analysis. The proposed tasks are to 1) develop scalable machine learning techniques to learn temporal change patterns in a scalable and in-situ manner, and to minimize data movement and maximize learning locally closest to data; 2) design a concise data representation and indexing mechanism to capture the distribution of changes in data that can guarantee point-wise user-defined tolerable errors while reducing the data storage requirements by an order of magnitude or more; 3) develop data reduction techniques as library modules; 4) exploit local SSD for minimizing data movement in storage hierarchy; 5) develop anomaly detection algorithms that can predict corruptions based on learning of emerging patterns; 6) develop software libraries to be incorporated within widely used data formats and APIs; and 7) evaluate the proposed software using DOE scientific applications. The outcomes of the proposed work are to satisfy many synergistic data reduction and resilience requirements for large-scale data intensive applications executed on extreme-scale computing systems. The developed mechanism for error-bound data approximation is directly applicable to existing scientific applications. Through machine learning from historical events and change distribution, this work will enable anomaly detection for DOE computer facility.

97 MATHEMATICS AND COMPUTING↗

Robust RF Photocathodes (Phase II Final Report)

This program addressed requirements for photocathodes with high quantum efficiency (QE) and long lifetimes. Currently, photocathodes with QEs above 1% exhibit lifetimes measured in a few hours. This is unacceptable for commercial devices using photocathodes as the electron source. This includes accelerators for industrial, medical, defense, and educational applications as well as emerging applications, such as time resolved electron microscopy. Calabazas Creek Research, Inc. (CCR) and the University of Maryland (UMD) attempted to develop reservoir photocathodes that dramatically increased lifetime and increased the ability to recover from contaminating events, such as loss of system vacuum. The Phase I program demonstrated the viability of the reservoir approach for higher QE cathodes. The Phase II program focused on design, fabrication, and delivery. This included increasing understanding of photocathode physics, investigating design options, addressing performance issues, and developing fabrication and packaging techniques leading to commercial products. The initial task identified specific photocathode materials that provide high QE and are compatible with the reservoir approach. The goal was that these photocathodes be manufacturable in a production environment, understanding that the “environment” is highly specialized. The photocathode geometry was modified to address several photogun performance issues related primarily to emittance. A goal was to reduce or eliminate thermal emittance issues arising from the reservoir heater. The program developed fabrication, handling, and transport techniques and facilities to allow commercial photocathode production for certain materials. Not only was complex chemistry involved, but practical issues of transporting and installing the cathodes into user systems were addressed. A critical goal was demonstration of reservoir photocathodes in operating RF guns, where performance could be directly measured. Success depended on clear demonstration that the cathodes could be produced, delivered, installed, and provide the required performance. The principal effort in this program was to develop reservoir cesium antimonide photocathodes. Cesium antimonide cathodes provide a work function in excess of the 1% goal, while the current generation exhibits lifetimes measured in hours. The reservoir in CCRs’ controlled porosity reservoir (CPR) cathodes provides a mechanism for replacing cesium evaporating from the surface by transporting replacement cesium from the reservoir. This is accomplished by gently heating the reservoir to induce cesium diffusion through micron-scale pores in the reservoir cap and photocathode emitter. Experiments at the UMD determined that cesium diffused from the reservoir would only react with antimony on the surface if the temperature exceeded 300C. At this temperature, however, the surface cesium evaporated faster than it could be replenished from the reservoir. Consequently, the QE decreased each time recessiation was attempted. This appears to be a fundamental problem with this approach. The sections below provide information on accomplishments for each task in the program. Once the issue with cesium antimonide cathodes was identified, CCR refocused the program to begin investigation of graphene coated photocathodes in collaboration with SLAC National Accelerator Laboratory (SLAC). The photocathode test chamber developed in the program was transferred to SLAC for use in the graphene research. This is described below in a task added to the program.

43 PARTICLE ACCELERATORS↗

SRNL Report on Vendor Solicitation and Selective Ion-Electrode Testing

Effective operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) will require information collected from sampling and/or monitoring to maintain environmental compliance, product quality, and operating efficiency. The U.S. Department of Energy (DOE) – Office of River Protection (ORP) recognizes the potential long-term benefit of developing real-time, in-line monitoring (RTIM) at the WTP to improve the current strategy of collecting tens of thousands of samples and analyzing them. In-line monitoring can decrease processing time associated with waiting for sample analysis, reduce workers’ exposure to radiation and chemical hazards, decrease secondary waste volumes, potentially improve product quality, and provide production support and enhance overall operational control. The Assistant Manager, WTP chartered an Integrated Technical Team (ITT), which includes personnel from the Savannah River National Laboratory (SRNL), Bechtel National, Inc., and DOE-ORP, to evaluate the capability and potential benefits of replacing routine sample collection requirements with real-time, in-line monitoring. The initial focus of the ITT is the Direct Feed Low Activity Waste (DFLAW) Program. This work scope is being performed in multiple phases. Phase 1 is Requirements and Opportunities Analysis, Phase 2 is Applications and Benefits Determination, and Phase 3 is Qualification and Demonstration. Phase 1 included 6 tasks and was completed by SRNL in 2017. The tasks in Phase 1 were: (1) determining the functional requirements for determining analytes and properties of streams, (2) determining the technical basis for process control, (3) determining the sampling points within the Low Activity Waste (LAW) facility and Effluent Management Facility (EMF), (4) data quality and management, (5) process control challenges, and (6) preparing a Preliminary Analysis Plan. DOE-ORP was briefed on the findings from the Phase 1 tasks and requested that Phase 2 work focus on establishing a basis for a materials balance approach that minimized process sampling. The Phase 2 work scope contains tasks to evaluate a materials balance only approach as well as continuing scoping evaluations for instruments that could be used for RTIM. The Phase 2 work scope was completed by both SRNL and Pacific Northwest National Laboratory (PNNL). The tasks performed in Phase 2 were: 1. Overall program administration and technical oversight 2. Evaluation of a Material Balance Approach, a. Evaluation of uncertainty of this approach compared to uncertainty of current methods b. Evaluation of automating the material balance within the framework of existing control software, c. Development of the methodology to obtain and evaluate data during cold commissioning to support a material balance approach, and d. Development of a framework to utilize during presentation of the revised approach to stakeholders and regulators. 3. Screening Evaluations of Instruments to Supplement the Material Balance Approach, a. AP-105 melter condensate evaluations, and b. Screening testing with simulants. 4. Evaluation of the current DFLAW feed qualification program to identify analytes that could be eliminated, a. Inorganic analytes, b. Radionuclides, and c. Organic analytes. This report describes the results of Task 3b, Screening testing with simulants. The Savannah River National Laboratory requested demonstrations of commercially available analytical instruments by the vendors or laboratory demonstration. The techniques tested included: Raman spectroscopy, Infrared spectroscopy (IR), laser induced breakdown spectroscopy (LIBS), X-Ray Fluorescence Spectroscopy (XRF), and ion-selective electrochemical probes. Additionally, the instrumentation would need to be durable enough to withstand the environment of the plant, preferably with little to no maintenance. The insertion point of the instrument would be dependent upon the instrumentation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

ROBOT: A Tool for Automating Ontology Workflows

BACKGROUND:Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats. Similar to more general software development, automation is the key to executing and managing these tasks effectively and to releasing more robust products in standard forms. For ontologies using the Web Ontology Language (OWL), the OWL API Java library is the foundation for a range of software tools, including the Protégé ontology editor. In the Open Biological and Biomedical Ontologies (OBO) community, we recognized the need to package a wide range of low-level OWL API functionality into a library of common higher-level operations and to make those operations available as a command-line tool. RESULTS:ROBOT (a recursive acronym for "ROBOT is an OBO Tool") is an open source library and command-line tool for automating ontology development tasks. The library can be called from any programming language that runs on the Java Virtual Machine (JVM). Most usage is through the command-line tool, which runs on macOS, Linux, and Windows. ROBOT provides ontology processing commands for a variety of tasks, including commands for converting formats, running a reasoner, creating import modules, running reports, and various other tasks. These commands can be combined into larger workflows using a separate task execution system such as GNU Make, and workflows can be automatically executed within continuous integration systems. CONCLUSIONS:ROBOT supports automation of a wide range of ontology development tasks, focusing on OBO conventions. It packages common high-level ontology development functionality into a convenient library, and makes it easy to configure, combine, and execute individual tasks in comprehensive, automated workflows. This helps ontology developers to efficiently create, maintain, and release high-quality ontologies, so that they can spend more time focusing on development tasks. It also helps guarantee that released ontologies are free of certain types of logical errors and conform to standard quality control checks, increasing the overall robustness and efficiency of the ontology development lifecycle.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Personalized learning via task load optimization

A method for providing task load-optimized computer-generated training experiences to a user of a training system that includes: a display, a training simulator, a prediction program (ML1), and a training optimization program (ML2). In response to receiving a predicted optimal task load, ML2 provides a first training experience recommendation related to the training content and/or training conditions that, if utilized in providing a training experience to the user, is predicted to result in the predicted actual task load of the user equaling the predicted optimal task load. In response to receiving biometric information or performance metric information, ML1 determines the predicted actual task load. If the predicted actual task load does not match the predicted optimal task load, ML2 provides a second training experience recommendation and a second training experience is provided where at least one of the training content or the training conditions is changed.

Bertolli, Michael G.↗

Examining United States Nuclear Weapon Educational Initiatives_A Quantitative Research Study on the Satisfaction of Participants Within the Nuclear Weapons Community

This study focused on a few United States nuclear weapons educational initiatives exploring six classroom environment factors that may or may not influence Satisfaction in a virtual or live classroom environment within the nuclear weapons community. The research explored Personalization, Involvement, Student Cohesiveness, Task Orientation, Innovation, and Individualization. The United States nuclear weapons community needed to attract new and talented individuals to the nuclear weapons profession. This study added to the nuclear weapons community by researching factors that may aid academic instructors, and curriculum developers create new and inventive ways of incorporating these factors into existing or new nuclear weapons educational courses. Convenience sampling was the data collection method used to gather quantitative research data. One hundred and seven voluntary participants utilized the College and University Classroom Environment Inventory with the Los Alamos National Laboratory's consent. There is not much concurrent research on Satisfaction within the live and virtual classroom environment. This research was vital for future research into how to increase participant satisfaction. The study provided the nuclear weapons community with grounded analysis to help create and guide new classes and course creation, possibly increasing Satisfaction in a live and virtual classroom environment. According to binary logistic regression, there was a statistically significant relationship among the dependent variable, Satisfaction, and two independent variables, Involvement, and Task Orientation in the classroom environment within the nuclear weapons community. Future nuclear educational programs may increase Satisfaction in the classroom environment by increasing participant Involvement and Task Orientation within a class using the CUCEI as a reference.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

ORNL Neutron Cross Section Measurements of 90 Zr

Nuclear criticality modeling and simulations rely on the quality of the existing evaluated nuclear data libraries such as Evaluated Nuclear Data File (ENDF)/B, the Joint Evaluated Fission and Fusion (JEFF) nuclear data library, or the Japanese Evaluated Nuclear Data Library (JENDL). In some cases, the cross-section evaluations of those libraries were found to be deficient in describing criticality benchmarks accurately. More than two decades ago, the US Nuclear Criticality Safety Program (NCSP) established a Nuclear Data (ND) task which encompassed experiments and evaluations. In response to this, the Oak Ridge National Laboratory (ORNL) formed a Nuclear Criticality and Data group which performed ND experiments, data analysis, and evaluations to produce ENDF files for the ND libraries as identified in the NCSP Five-Year Plan. Before being submitted to the ENDF library, files were processed and tested for performance by running benchmark calculations. This procedure was centralized in the ORNL group and is now often referred to as the ND pipeline. NCSP collaborates with the Joint Research Center (JRC) of the European Commission in Geel, Belgium, to perform high-resolution neutron-induced cross section measurements at the Geel Linear Accelerator (GELINA). The objective is to address emerging ND problems in criticality calculations. Difficulties with ND include insufficient neutron energy range, missing covariances, and previously unrecognized inaccuracies with experiments. New neutron total and capture cross sections of 90 Zr in the neutron energy range from 100 eV to several hundred keV were recently performed. These measured data will be used, together with existing high-resolution transmission data from a metallic 90 Zr sample, to improve representation of the cross sections.

97 MATHEMATICS AND COMPUTING↗

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning in the Context of Laser-Induced Breakdown Spectroscopy

The integration of machine learning (ML) with Laser-Induced Breakdown Spectroscopy (LIBS) has revolutionized the analytical capabilities of LIBS. The combi-nation of both methods enables more accurate and efficient data analysis. While LIBS itself is a powerful technique for elemental analysis, the vast amount of spectral data it generates can be hard to interpret. Machine learning addresses these challenges by leveraging algorithms that can learn from data, identify patterns, and make predictions without explicit programming for the interpretation of each specific task. In LIBS application, ML techniques are used to enhance various analytical processes. For example, ML algorithms can classify materials based on their spectral fingerprints, predict the concentration of elements in a sample, and identify underlying patterns within complex datasets. Here, this application improves the precision of LIBS analyses while significantly reducing the time required for data processing and interpretation. In this chapter, the fundamental concepts of ML will be discussed first. Following this, the process of data splitting and the importance of feature selection will be examined. Several machine learning methods will then be closely examined, exploring how each can benefit LIBS analysis and highlighting their respective advantages and shortcomings. This structured approach will provide a comprehensive understanding of the integration of ML in the context of LIBS analysis.

47 OTHER INSTRUMENTATION↗

Near-optimal routing of noisy quantum states

Placement, routing, and scheduling are essential tasks for near-optimal performance of programs for noisy quantum processors. Reliable execution of an arbitrary quantum circuit on current devices requires routing methods that overcome connectivity limitations while meeting data locality requirements. However, current devices also express highly variable noise levels in both the quantum gates and quantum registers. This requires any routing algorithm to be adaptive to both the circuit and the operating conditions. We demonstrate near-optimal routing methods of noisy quantum states that minimize the overall error of data movement while also limiting the computational complexity of routing decisions. We evaluate our methods against the noise characteristics of a 20-qubit superconducting quantum processor.

Sadlier III, Ronald↗

Lamellar

asynchronous task based runtime developed using the Rust programming language for HPC

Friese, Ryan↗

MiniMOD

SAND2025-03854O MiniMod is a user-friendly software tool designed to assess the performance of high-performance computing (HPC) systems. Researchers can use the program to test communication methods and computational tasks to understand how different setups can affect application efficiency. This software is particularly useful for optimizing network performance in scientific research, simulations, and data analysis. MiniMod‘s flexible design allows users to make informed decisions about their computing environments, which can enhance productivity and results in real-world applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Dosanjh, Matthew [Sandia National Lab. (SNL-CA), L↗

DOE/UCAR Cooperative Agreement for the Regional and Global Climate Modeling Program

This progress report describes research supported by Cooperative Agreement between the University Corporation for Atmospheric Research (UCAR) and the U.S. Department of Energy (DOE) Biological and Environmental Research (BER). The purpose of the Cooperative Agreement is to provide support for an integrated research program to address key science questions relevant to the DOE Regional and Global Climate Modeling Program as part of the U.S. Global Change Research Program (USGCRP). The Cooperative Agreement funds four tasks that address key aspects of climate science, and this report provides a summary of activities for each task during the past year. As part of the Cooperative Agreement supported science, the Climate Change Prediction (CCP) group at the National Center for Atmospheric Research (NCAR), provides leadership to the Community Earth System Model (CESM) Climate Variability and Change Working Group (CVCWG) through co-chairs Gerald Meehl and Susan Bates (with DOE-funded co-chair Peter Gleckler, along with Clara Deser and Shang-Ping Xie). Over the past year CCP has played a leadership role in performing climate change simulations and analyses with the Community Climate System Model version 4 (CCSM4) and CESM version 1. These simulations and analyses made strong contributions to the federal USGCRP in several high priority areas. We have also been involved in planning for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) which started in 2015. Simulations from CMIP6 will form the basis for ongoing U.S. National Assessment activities, and the IPCC AR6.

54 ENVIRONMENTAL SCIENCES↗

Light Water Reactor Sustainability Program Materials Research Pathway Technical Program Plan

The Materials Research (MR) Pathway within the Light Water Reactor Sustainability (LWRS) Program is charged with performing the research and development (R&D) to develop the scientific basis for understanding and predicting long-term environmental degradation behavior of materials in nuclear reactors. Furthermore, it is essential to use the mechanistic understanding of degradation phenomena in materials to develop mitigation, repair, and new material alternatives for existing components. The work will provide data and methods to assess performance of systems, structures, and components (SSCs) essential to safe and sustained reactor operations. The R&D products developed from the LWRS Program will be used by utilities, industry groups, and regulators to inform operational and regulatory requirements for materials in reactor SSCs subjected to long-term operation conditions, providing key input to both regulators and industry. The intent of this research is to help in reducing the operating costs, which may be in the form of offset maintenance costs due to better predictive models for component lifetimes, improved analysis of materials through nondestructive evaluation, reduced costs for repairs, or extended performance of plants through the selection of improved replacement materials. To best achieve this, industry experience and guidance are important as is their role in coordinated or collaborative research projects. The objectives of this report are to describe the motivation and organization of the MR Pathway within the LWRS Program, provide details on the individual research tasks within the MR Pathway, describe the outcomes and deliverables of the MR Pathway, including recent technical highlights and progress, and list the requirements for performing the research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Pursuing the Ultimate Power of Xenon Dark Matter Detectors (Annual Progress Report)

Liquid xenon-based experiments have been leading direct searches for dark matter – a cornerstone of modern cosmology and particle physics. Despite rapid improvement of experimental sensitivities in the past two decades, no definitive dark matter interactions have been observed. This project aims to expand the physics reach of existing and future xenon dark matter experiments, especially for low-mass dark matter interactions that would fall below the energy thresholds of current detectors. The main approach is to thoroughly characterize and to suppress the low-energy electron background observed in dual-phase xenon Time Projection Chambers (TPCs), which has so far prevented these detectors from achieving lower energy thresholds. Per recent discussion with and approval from the program manager, we have added a new task of experimentally measuring the Migdal effect to this project. The Migdal effect predicts that ultra-low energy dark matter interactions may produce detectable electron recoil signals in liquid xenon at the keV level in addition to much lower energy nuclear recoils. If this effect is experimentally measured, it will drastically improve xenon detectors’ sensitivity to subGeV dark matter interactions. This new task shares strong synergy with the original project goal of pursuing the ultimate power of xenon dark matter experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Light Water Reactor Sustainability Program Materials Research Pathway Technical Program Plan

The objectives of this report are to describe the motivation and organization of the MR Pathway within the LWRS program; provide details on the individual research tasks within the MR Pathway; describe the outcomes and deliverables of the MR Pathway, including recent technical highlights and progress; and describe the requirements for performing this critically important research.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Light Water Reactor Sustainability: Program Materials Research Pathway (FY22 Technical Program Plan)

The Materials Research (MR) Pathway within the Light Water Reactor Sustainability (LWRS) program is charged with performing R&D to develop the scientific basis for understanding and predicting the long-term environmental degradation behavior of materials in nuclear reactors. Furthermore, the mechanistic understanding of degradation phenomena in materials must be leveraged to develop mitigation and repair strategies and new material alternatives for existing components. This research will provide data and methods to assess the performance of systems, structures, and components essential to safe and sustained reactor operations. The R&D products developed from the LWRS program will be used by stakeholders—including utilities, industry groups, and regulators—to inform operational and regulatory requirements for materials in reactor systems, structures, and components subjected to long-term operation conditions, providing key inputs to regulators and industry. Therefore, the intent of this research is to provide options to reduce the operating costs, which may be in the form of offset maintenance costs due to better predictive models for component lifetimes, improved analyses of materials through nondestructive evaluation, reduced costs for repairs, or extended performance of plants through the selection of improved replacement materials. To provide the best options, industry experience and guidance are important because of their role in coordinated or collaborative research projects. The objectives of this report are to describe the motivation and organization of the MR Pathway within the LWRS program; provide details on the individual research tasks within the MR Pathway; describe the outcomes and deliverables of the MR Pathway, including recent technical highlights and progress; and describe the requirements for performing this critically important research.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗