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At least 181 records · Page 10

ASC ATDM Level 2 Milestone #6015: Asynchronous Many-Task Software Stack Demonstration

This report is an outcome of the ASC ATDM Level 2 Milestone 6015: Asynchronous Many-Task Software Stack Demonstration. It comprises a summary and in depth analysis of DARMA and a DARMA-compliant Asynchronous Many-Task (AMT) runtime software stack. Herein performance and productivity of the over- all approach are assessed on benchmarks and proxy applications representative of the Sandia ATDM applications. As part of the effort to assess the perceived strengths and weaknesses of AMT models compared to more traditional methods, experiments were performed on ATS-1 (Advanced Technology Systems) test bed machines and Trinity. In addition to productivity and performance assessments, this report includes findings on the generality of DARMAs backend API as well as findings on interoperability with node- level and network-level system libraries. Together, this information provides a clear understanding of the strengths and limitations of the DARMA approach in the context of Sandias ATDM codes, to guide our future research and development in this area.

97 MATHEMATICS AND COMPUTING↗

FY19 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models and Preliminary Testing of a Selected Process Model

Sandia National Laboratories continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project. This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. The FY19 task included continued operation of the cluster; maintenance of the TSPA-LA models (with Gold Sim 9.60.300); preliminary assessment of the status of the Infiltration Model (a process model that feeds the TSPA-LA). In addition, precautionary actions were needed to extend the life of the cluster hardware. To do that, three new nodes were added to the cluster. In the event any of the original nodes fail they will be replaced with the new nodes, thereby maintaining the core capability. The 2014 cluster and supporting software systems are currently fully operational to support TSPA-LA type analysis.

97 MATHEMATICS AND COMPUTING↗

FY2021 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models and Testing of Selected Process Models

Sandia National Laboratories continued evaluation of the total system performance assessment (TSPA) for License Application (LA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. The FY21 task included continued operation of the cluster; maintenance of the TSPA-LA models (with GoldSim 9.60.300); continued assessment of the status of the Infiltration Model; (a process model that feeds the TSP -LA) and preliminary assessments of the Unsaturated Zone Flow Model and the Saturated Zone Flow and Transport Model Abstraction (process models that feed the TSPA-LA). The 2014 cluster and supporting software systems are currently fully operational to support TSPA-LA type analyses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology Using Large Language Models—A Case in Optimizing Intermodal Freight Transportation

The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. However, addressing complex urban and environmental management challenges often demands deep expertise in domain science and informatics. This expertise is essential for deriving data and simulation-driven insights that support informed decision-making. In this context, we investigate the potential of leveraging the pre-trained Large Language Models (LLMs) to create knowledge representations for supporting operations research. By adopting ChatGPT-4 API as the reasoning core, we outline an applied workflow that encompasses natural language processing, Methontology-based prompt tuning, and Generative Pre-trained Transformer (GPT), to automate the construction of scenario-based ontologies using existing research articles and technical manuals of urban datasets and simulations. From these ontologies, knowledge graphs can be derived using widely adopted formats and protocols, guiding various tasks towards data-informed decision support. The performance of our methodology is evaluated through a comparative analysis that contrasts our AI-generated ontology with the widely recognized pizza ontology, commonly used in tutorials for popular ontology software. We conclude with a real-world case study on optimizing the complex system of multi-modal freight transportation. Our approach advances urban decision support systems by enhancing data and metadata modeling, improving data integration and simulation coupling, and guiding the development of decision support strategies and essential software components.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

SAS4A/SASSYS-1 Modernization and Extension FY2014

SAS4A/SASSY-1 is a simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for non light-water reactors. This report summarizes ongoing tasks to modernize the SAS4A/SASSYS-1 code system to improve internal data management and to update several other code modules. The motivation for performing these updates stems from the relevance of SAS4A/SASSYS-1 to a number of U.S. Department of Energy programs as well as domestic and international collaborations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for “intensity modulated radiation therapy (IMRT)” as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.

60 APPLIED LIFE SCIENCES↗

The Effect of Job Performance Aids on Quality Assurance

Job performance aids (JPAs) have been studied for many decades in a variety of disciplines and for many different types of tasks, yet this is the first known research experiment using JPAs in a quality assurance (QA) context. The objective of this thesis was to assess whether a JPA has an effect on the performance of a QA observer performing the concurrent dual verification technique for a basic assembly task. The JPA used in this study was a simple checklist, and the design borrows heavily from prior research on task analysis and other human factors principles. The assembly task and QA construct of concurrent dual verification are consistent with those of a high consequence manufacturing environment. Results showed that the JPA had only a limited effect on QA performance in the context of this experiment. However, there were three important and unexpected findings that may draw interest from a variety of practitioners. First, a novel testing methodology sensitive enough to measure the effects of a JPA on performance was created. Second, the discovery that there are different probabilities of detection for different types of error in a QA context may be the most far-reaching results. Third, these results highlight the limitations of concurrent dual verification as a control against defects. It is hoped that both the methodology and results of this study are an effective baseline from which to launch future research activities.

99 GENERAL AND MISCELLANEOUS↗

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parameters gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval

59 BASIC BIOLOGICAL SCIENCES↗

Weatherization Crew Leader Job Task Analysis

The US Department of Energy's Guidelines for Home Energy Professionals project maintains job task analyses for jobs in the Weatherization Assistance Program and home performance industry. One of those jobs is Crew Leader, defined as: 'A Crew Leader is responsible for supervising and assisting in the retrofitting activities specified in the scope of work. He or she is responsible for interacting with the client plus managing personnel and materials on the job site in a safe and effective manner. The Crew Leader is responsible for quality control, testing procedures, documentation, and conducting a walk through in preparation that all work is completed in a satisfactory manner.' This document is an updated version of the Crew Leader job task analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Analysis of the ASME Code Rules for Subsection III-5-HHB (Composite Materials) for Current HTR Design Requirements

This document includes the critical analysis review of the American Society of Mechanical Engineers (ASME) Section III Division 5 Subsection HH Subpart B (HHB), including Mandatory Appendices, that was published in 2023. In the context of this document, reference to “the code” is specific to this subsection unless otherwise specified. A specific composites task group within the ASME Nonmetallic Design and Materials Working Group, with the support of external experts, was established to perform a gap analysis review. The significant findings are summarized here. The committee response with suggested action items are detailed in the body of the report.

36 MATERIALS SCIENCE↗

Evaluation of Machine Learning Models for Automated Data Analysis in In-Service Nuclear Power Plant Inspections

The commercial nuclear power industry is facing a potential shortage of certified nondestructive evaluation (NDE) analysts to meet future in-service inspection demands. Automated data analysis (ADA) currently supports human inspectors in tasks such as eddy current evaluations for steam generator examinations. Machine learning (ML) systems are nearing the capability to pass performance demonstration tests for ultrasonic testing (UT) inspections of reactor pressure vessel upper head penetrations in nuclear power plants (NPPs). Current research and development is focused on assisted analysis (AA) of ADA versus fully automated examinations. This presentation will cover assessment of ML flaw detection on dissimilar metal weld (DMW) piping joints.

36 MATERIALS SCIENCE↗

Systematic Technology Evaluation Program for SiC-based BWR Channel Box

Silicon carbide (SiC) –based accident-tolerant fuel (ATF) cladding of light water reactors (LWRs) has become a topic of great interest in nuclear material development since the Fukushima Dai-ichi Nuclear Power Plant accident. Extensive development of SiC cladding has identified benefits of the concept, including its inherent accident resistance and neutronic performance. Advancements achieved during the development of SiC-based ATF cladding have made it attractive for use in accident-tolerant cores of LWRs. In this document, we consider the use of SiC-based materials to replace the zirconium alloy used for the channel boxes of boiling water reactors. Both accident resistance and prevention of the bowing observed in current grades of channel boxes are needs driving the exploration of a new channel box system. To provide a pathway for channel box development, this document lays out (1) a current technology overview, (2) the technology gap, and (3) a systematic technology evaluation plan. The objectives of the technology evaluation plan are to address key feasibility issues revealed by the knowledge gap analysis and to contribute to advancing the technology readiness level. Further development will be required in the technology implementation phase. The technology evaluations include understanding the behavior of channel boxes under both normal and off-normal conditions, identifying potential mitigation strategies for the issues if necessary, and improving channel box performance based on the knowledge obtained. The structure of the technology evaluation plan and each task are shown in Figure S.1. The knowledge gap analysis identified key research areas, including irradiation effects, hydrothermal corrosion, accident behavior, and design and manufacture. These are common issues between SiC-based channel boxes and SiC-based fuel cladding, although technical evaluations specific for the channel box components are required. This document also describes details of the technical feasibility evaluation methods and plans.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SparseLU, A Novel Algorithm and Math Library for Sparse LU Factorization

Decomposing sparse matrices into lower and upper triangular matrices (sparse LU factorization) is a key operation in many computational scientific applications. We developed SparseLU, a sparse linear algebra library that implements a new algorithm for LU factorization on general sparse matrices. The new algorithm divides the input matrix into tiles to which OpenMP tasks are created for factorization computation, where only tiles that contain nonzero elements are computed. For comparative performance analysis, we used the reference library SuperLU. Testing was performed on synthetically generated matrices which replicate the conditions of the real-world matrices. SparseLU is able to reach a mean speedup of ~29× compared to SuperLU.

Valero Lara, Pedro↗

Environmental management system objectives & targets results summary FY 2013

Sandia National Laboratories/New Mexico s (SNL/NM) Environmental Management System is the integrated approach for members of the workforce to identify and manage environmental risks. Each Fiscal Year (FY) SNL/NM performs an analysis to identify environmental aspects, and the environmental programs associated with them are charged with the task of routinely monitoring and measuring the objectives and targets that are established to mitigate potential impacts of SNL/NM s operations on the environment. An annual summary of the results achieved towards meeting established Sandia Corporation and SNL/NM Site-specific objectives and targets provides a connection to, and rational for, annually revised environmental aspects. The purpose of this document is to summarize the results achieved and documented in FY2013.

54 ENVIRONMENTAL SCIENCES↗

Environmental Management System Objectives & Targets Results Summary - FY 2015.

Sandia National Laboratories (SNL) Environmental Management System is the integrated approach for members of the workforce to identify and manage environmental risks. Each Fiscal Year (FY) SNL performs an analysis to identify environmental aspects, and the environmental programs associated with them are charged with the task of routinely monitoring and measuring the objectives and targets that are established to mitigate potential impacts of SNL's operations on the environment. An annual summary of the results achieved towards meeting established Sandia Corporation and SNL Site-specific objectives and targets provides a connection to, and rational for, annually revised environmental aspects. The purpose of this document is to summarize the results achieved and documented in FY 2015.

54 ENVIRONMENTAL SCIENCES↗

Environmental Management System (EMS) Objectives & Targets Annual Results Summary – FY 2014

Sandia National Laboratories/New Mexico’s (SNL/NM) Environmental Management System is the integrated approach for members of the workforce to identify and manage environmental risks. Each Fiscal Year (FY) SNL/NM performs an analysis to identify environmental aspects, and the environmental programs associated with them are charged with the task of routinely monitoring and measuring the objectives and targets that are established to mitigate potential impacts of SNL/NM’s operations on the environment. An annual summary of the results achieved towards meeting established Sandia Corporation and SNL/NM Site-specific objectives and targets provides a connection to, and rational for, annually revised environmental aspects. The purpose of this document is to summarize the results achieved and documented in FY 2014.

54 ENVIRONMENTAL SCIENCES↗

Wilkins: HPC in situ workflows made easy

In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however, face challenges in handling the growing complexity and diverse computational requirements of scientific tasks. In this work, we present Wilkins, an in situ workflow system that is designed for ease-of-use while providing scalable and efficient execution of workflow tasks. Wilkins provides a flexible workflow description interface, employs a high-performance data transport layer based on HDF5, and supports tasks with disparate data rates by providing a flow control mechanism. Wilkins seamlessly couples scientific tasks that already use HDF5, without requiring task code modifications. We demonstrate the above features using both synthetic benchmarks and two science use cases in materials science and cosmology.

HPC↗

SAS4A/SASSYS-1 Code Improvements for FY2016

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced reactors. This report summarizes ongoing tasks to modernize the SAS4A/SASSYS-1 code system to improve internal data management, update several other code modules, and add new features. Code modernization activities focused on eliminating legacy data management in the balance-of-plant module, which was the only module that still used non-portable data allocation. Code extensions include the development of a new axial expansion model that can accurately account for non-uniform or heterogeneous fuel compositions. The most significant accomplishment is the addition of uncertainty quantification capabilities for transient simulations using the Dakota toolkit from Sandia National Laboratory. The motivation for performing these updates stems from the relevance of SAS4A/SASSYS-1 to a number of U.S. Department of Energy programs as well as domestic and international collaborations. External collaborations have also produced improvements in the SAS4A/SASSYS-1 code, and these are summarized in this report. SAS4A/SASSYS-1 has a growing user base that continues to strengthen the promotion of advanced reactor concepts such as sodium cooled fast reactors. Additional users will help solidify DOE’s leadership role in fast reactor safety both domestically and in international collaborations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗