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At least 1,621 records · Page 90

Light Water Reactor Sustainability Program Advanced Seismic Soil Structure Modeling

Risk calculations should focus on providing best estimate results, and associated insights, for evaluation and decision-making. Specifically, seismic probabilistic risk assessments (SPRAs) are intended to provide best estimates of the various combinations of structural and equipment failures that can lead to a seismic induced core damage event. However, in some instances the current SPRA approach has large uncertainties, and potentially masks other important events (for instance, it was not the seismic motions that caused the Fukushima core melt events, but the tsunami ingress into the facility). SPRA’s are performed by convolving the seismic hazard (this is the estimate of all likely damaging earthquakes at the site of interest) with the seismic fragility (the conditional probability of failure of a structure, system, or component given the occurrence of earthquake ground motion). In this calculation, there are three main pieces to seismic risk quantification, 1) seismic hazard and nuclear power plants (NPPs) response to the hazard, 2) fragility or capacity of structures, systems and components (SSC), and 3) systems analysis. Two areas where NLSSI effects may be important in SPRA calculations are, 1) when calculating in-structure response at the area of interest, and 2) calculation of seismic fragilities (current fragility calculations assume a lognormal distribution for probability of failure of components). Some important effects when using NLSSI in the SPRA calculation process include, 1) gapping and sliding, 2) inclined seismic waves coupled with gapping and sliding of foundations atop soil, 3) inclined seismic waves coupled with gapping and sliding of deeply embedded structures, 4) soil dilatancy, 5) soil liquefaction, 6) surface waves, 7) buoyancy, 8) concrete cracking and 9) seismic isolation The focus of the research task presented here-in is on implementation of NLSSI into the SPRA calculation process when calculating in-structure response at the area of interest. The specific nonlinear soil behavior included in the NLSSI calculation presented in this report is gapping and sliding. Other NLSSI effects are not included in the calculation. The results presented in this report document initial model runs in the linear and nonlinear analysis process. Final comparisons between traditional and advanced SPRA will be presented in the September 30th deliverable.

54 ENVIRONMENTAL SCIENCES↗

Integrated Methane Monitoring Platform Extension, Volume I: Final Technical Report

The IMMPE project, DE-FE0032284, was to enhance methane monitoring technologies and their applications across various natural gas asset classes. The scope included deploying advanced methane detection and monitoring technologies to identify and mitigate fugitive methane emissions, measuring emission rates, and assessing impacts. The findings included the successful mitigation of identified emissions and quantification of emission rates. A key outcome was the development of a comprehensive template and summary of recommendations for methane emissions monitoring, which is replicable for both upstream and downstream applications. Furthermore, the project emphasized the importance of education by providing training opportunities for technicians and regulators, thereby fostering awareness and promoting the adoption of cost-effective methane emissions monitoring and management techniques.

02 PETROLEUM↗

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗

Direct normal irradiance related definitions and applications: The circumsolar issue

The direct irradiance received on a plane normal to the sun, called direct normal irradiance (DNI), is of particular relevance to concentrated solar technologies, including concentrating solar thermal plants and concentrated photovoltaic systems. Following various standards from the International Organization for Standardization (ISO), the DNI definition is related to the irradiance from a small solid angle of the sky, centered on the position of the sun. Half-angle apertures of pyrheliometers measuring DNI have varied over time, up to ≈10°. The current recommendation of the World Meteorological Organization (WMO) for this half-angle is 2.5°. Solar concentrating collectors have an angular acceptance function that can be significantly narrower, especially for technologies with high concentration ratios. The disagreement between the various interpretations of DNI, from the theoretical definition used in atmospheric physics and radiative transfer modeling to practical definitions corresponding to specific measurements or conversion technologies is significant, especially in the presence of cirrus clouds or large concentration of aerosols. Under such sky conditions, the circumsolar radiation—i.e. the diffuse radiation coming from the vicinity of the sun—contributes significantly to the DNI ground measurement, although some concentrating collectors cannot utilize the bulk of it. These issues have been identified in the EU-funded projects MACC-II (Monitoring Atmospheric Composition and Climate-Interim Implementation) and SFERA (Solar Facilities for the European Research Area), and have been discussed within a panel of international experts in the framework of the Solar Heating and Cooling (SHC) program of the International Energy Agency’s (IEA’s) Task 46 “ Solar Resource Assessment and Forecasting ”. In accordance with these discussions, the terms of reference related to DNI are specified here. The important role of circumsolar radiation is evidenced, and its potential contribution is evaluated for typical atmospheric conditions. Thus, thorough analysis of performance of concentrating solar systems, it is recommended that, in addition to the conventional DNI related to 2.5° half-angle of today’s pyrheliometers, solar resource data sets also report the sunshape, the circumsolar contribution or the circumsolar ratio (CSR).

14 SOLAR ENERGY↗

Qiita: rapid, web-enabled microbiome meta-analysis

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

microbiome, bioinformatics software, open source s↗

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. In this work, we address these challenges by leveraging distributions of per-sample errors obtained during training and employing a distance-based similarity search in the model latent space. Our method, which we call LTAU (Loss Trajectory Analysis for Uncertainty), efficiently estimates the full probability distribution function of errors for any test point using the logged training errors, achieving speeds that are 2–3 orders of magnitudes faster than typical ensemble methods and allowing it to be used for tasks where training or evaluating multiple models would be infeasible. We apply LTAU towards estimating parametric uncertainty in atomistic force fields (LTAU-FF), demonstrating that it produces well-calibrated confidence intervals and predicts errors that correlate strongly with the true errors for data near the training domain. Furthermore, we show that the errors predicted by LTAU-FF can be used in practical applications for detecting out-of-domain data, tuning model performance, and predicting failure during simulations. We believe that LTAU will be a valuable tool for uncertainty quantification in atomistic force fields and is a promising method that should be further explored in other domains of machine learning.

97 MATHEMATICS AND COMPUTING↗

AmpSuite

Seismic amplitudes offer vital information about explosion source characteristics, including discrimination and yield estimation. To take advantage of this, we developed an interactive Python package to measure, control data quality, generate broad area propagation models and perform discrimination and estimate yield. Propagation models are essential in support of transportable yield and broad area discrimination. The key benefit of this package will be its ability to continuously integrate data and new techniques. The AmpSuite framework will provide standardized, repeatable, and accurate model generation and characterization routines. The capability is crucial for monitoring agencies tasked with rapid and high-quality seismic event characterization. The AmpSuite software includes a series of independent modules to perform: • Direct Phase Amplitude Measurement and Storage • Coda Envelope Measurement and Storage • Data Quality Control • New Propagation Model Developments • Seismic Discrimination and Analysis • Yield Estimation and supporting utility software. The AmpSuite software provides comprehensive solutions for monitoring agencies seeking to optimize model generation and event analysis within a contemporary Python framework. Stakeholders (AFTAC) have begun to move towards the Python language for scientific analysis as a new workforce emerges.

Alfaro, Richard↗

Assessment of In-situ Proppant Placement in SRV Using Through-Fracture Core Sampling at HFTS

The primary aim of this study was to develop robust methods aimed at detecting and quantifying the subsurface proppant distribution as it relates to the completed wells in both the upper and the middle Wolfcamp formations at the HFTS site. There were two sources of proppant deemed useful for this task. The first source was the actual scrapings from the fracture faces that were collected during the core description work. The second sample source was the scrapings and sludge from the cut core tubes collected during core handling. This study highlights the analysis done on the second set of sludge samples. Apart from developing a method for detection and quantification of proppant and other particles contained within this sludge, the study was aimed at the following broad objectives: Determine the spatial distribution of proppant in the created SRV along the cored interval, including size distribution and proppant concentration. Determine if pay zones of interest are sufficiently propped/ stimulated. Determine if fracture and cluster spacing is optimal for thorough lateral reservoir coverage. Determine if well spacing is optimal based on propped SRV length.

Maity, Debotyam↗

Extracting Material Property Measurement Data from Scientific Articles

Machine learning-based prediction of material properties is often hampered by the lack of sufficiently large training datasets. The majority of such measurement data is embedded in scientific literature and the ability to automatically extract these data is essential to support the development of reliable property prediction methods. In this work, we describe a methodology for an automatic property extraction framework using material solubility as the target property. We create an annotated dataset containing tags for solubility-related entities using a combination of regular expressions and manual tagging. We then compare five entity recognition models leveraging both token-level and span-level architectures on the task of classifying solute names, solubility values, and solubility units. Additionally, we explore a novel pretraining approach that leverages automated chemical name and quantity extraction tools to generate large datasets that do not rely on intensive manual effort. Finally, we perform an analysis to identify the causes of classification errors.

Panapitiya, Gihan U.↗

Streamlining and Refining FEDS Loads Models (Final Report)

The Facility Energy Decision System (FEDS) software is a powerful buildings energy analysis tool developed by Battelle at the Pacific Northwest National Laboratory with support from numerous organizations including several within the U.S. Department of Energy (DOE) and U.S. Department of Defense (DoD). FEDS is used extensively throughout the federal sector to examine building energy efficiency potential and recommend energy saving retrofit projects. The focus of this CRADA was to update the foundation of the FEDS loads models, to improve the core functionality and calculation methods and position the building efficiency analysis software for continued growth. The broader intent was to increase FEDS utility and user satisfaction via improving modeling accuracy, facilitating development and making possible a wide range of new and desired capability enhancements. This report provides an summary of the various tasks performed under the CRADA.

Dahowski, Robert T.↗

Virtual tool mark generation for efficient striation analysis in forensic science

In 2009, a National Academy of Sciences report called for investigation into the scienti c basis behind tool mark comparisons (National Academy of Sciences, 2009). Answering this call, Chumbley et al. (2010) attempted to prove or disprove the hypothesis that tool marks are unique to a single tool. They developed a statistical algorithm that could, in most cases, discern matching and non-matching tool marks made at di erent angles by sequentially numbered screwdriver tips. Moreover, in the cases where the algorithm misinterpreted a pair of marks, an experienced forensics examiner could discern the correct outcome. While this research served to con rm the basic assumptions behind tool mark analysis, it also suggested that statistical analysis software could help to reduce the examiner's workload. This led to a new tool mark analysis approach, introduced in this thesis, that relies on 3D scans of screwdriver tip and marked plate surfaces at the micrometer scale from an optical microscope. These scans are carefully cleaned to remove noise from the data acquisition process and assigned a coordinate system that mathematically de nes angles and twists in a natural way. The marking process is then simulated by using a 3D graphics software package to impart rotations to the tip and take the projection of the tip's geometry in the direction of tool travel. The edge of this projection, retrieved from the 3D graphics software, becomes a virtual tool mark. Using this method, virtual marks are made at increments of 5 and compared to a scan of the evidence mark. The previously developed statistical package from Chumbley et al. (2010) performs the comparison, comparing the similarity of the geometry of both marks to the similarity that would occur due to random chance. The resulting statistical measure of the likelihood of the match informs the examiner of the angle of the best matching virtual mark, allowing the examiner to focus his/her mark analysis on a smaller range of angles. Preliminary results are quite promising. In a study with both sides of 6 screwdriver tips and 34 corresponding marks, the method distinguished known matches from known non-matches with zero false positive matches and only two matches mistaken for non-matches. For matches, it could predict the correct marking angle within 5-10 . Moreover, on a standard desktop computer, the virtual marking software is capable of cleaning 3D tip and plate scans in minutes and producing a virtual mark and comparing it to a real mark in seconds. These results support several of the professional conclusions of the tool mark analysis com- munity, including the idea that marks produced by the same tool only match if they are made at similar angles. The method also displays the potential to automate part of the comparison process, freeing the examiner to focus on other tasks, which is important in busy, backlogged crime labs. Finally, the method o ers the unique chance to directly link an evidence mark to the tool that produced it while reducing potential damage to the evidence.

42 ENGINEERING↗

Evaluation of the Computing Systems for Yucca Mountain Repository TSPA-LA Model Operational Readiness

Sandia National Laboratories (SNL) was tasked to conduct an evaluation of the legacy computing systems of the now-closed Yucca Mountain Project (YMP) to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, in the event that the License Application (LA) review by the U.S. Nuclear Regulatory Commission (NRC) is re-started and involves additional requests for information (RAIs). Six problem areas or components of the computing system were identified and subsequently resolved or improved to ensure the operational readiness of the TSPA-LA model capability on the server cluster. As part of this readiness review, the legacy TSPA computational cluster that was relocated from the SNL YMP Lead Lab Project Office in Las Vegas, Nevada to the SNL offices in Albuquerque, New Mexico was replaced with new hardware. Three floating licenses of Goldsim Version 9.60.300 were installed on the new cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software was tested and installed to support the TSPA- type analysis on the server cluster. TSPA-LA modeling cases were tested and verified for the model reproducibility on the current server cluster. All test runs were executed on multiple processors on the server cluster utilizing the Goldsim distributed processing capability, and all runs were completed successfully. The model reproducibility verification was evaluated by two approaches: numerical value comparison and graphical comparison, and the analysis demonstrated an excellent reproducibility of the TSPA-LA model runs on the server cluster. The current server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.

97 MATHEMATICS AND COMPUTING↗

Physics-Based Optical Neuromorphic Classification

Typical approaches to classify scenes from light convert the light field to electrons to perform the computation in the digital electronic domain. This conversion and downstream computational analysis require significant power and time. Diffractive neural networks have recently emerged as unique systems to classify optical fields at lower energy and high speeds. Previous work has shown that a single layer of diffractive metamaterial can achieve high performance on classification tasks. In analogy with electronic neural networks, it is anticipated that multilayer diffractive systems would provide better performance, but the fundamental reasons for the potential improvement have not been established. In this work, we present extensive computational simulations of two - layer diffractive neural networks and show that they can achieve high performance with fewer diffractive features than single layer systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗

Electrical Substation Configuration Effect on Substation Reliability

The nation’s electrical grid must be reliable because of its critical role in the economy, defense, and security of the nation. Many common tasks and industrial operations rely on proper electrical power distribution. In the design of new bus systems or evaluation of existing bus systems, the type of bus configuration affects the risk, reliability, maintenance, and cost of the system. This work utilizes Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) to perform a probabilistic risk assessment (PRA) based sensitivity study on the reliability of substations with differing bus configurations. This study examines single bus, main and transfer, breaker and a half, double bus/double breaker, and ring bus configurations applied to busses of varying number of lines. The case variances, methods, and rankings presented can provide a guide for bus configuration for future electrical grid design and analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thermal Hydraulics Safety Analyses of TRIGA Reactor Upon Fuel Reconfiguration

Safety analyses of the Training, Research, Isotope, General Atomics (TRIGA) reactor at Kansas State University(KSU) is performed using thermal hydraulic simulations based on changes to reactivity or the volumetric heat generation rate due to changes in the positioning of the enriched fuel elements in the reactor core. If the reactivity or neutronics parameters are known, then they can be used to simulate the thermal energy state of the material which is crucial to assess the safety of the nuclear fuel inside a nuclear reactor. Several thermal hydraulics models and codes have been developed in the past to assess reactor safety. RELAP (Reactor Excursion and Leak Analysis Program) is one such tool widely used throughout the world for safety analyses. Although RELAP is considered a reliable tool by regulators, vendors, and operators, it lacks the numerical fidelity provided by 3-D computational fluid dynamics (CFD) models. This work involves the critical task of assessing safety of a research reactor upon fuel reconfiguration based on models developed in RELAP and comparing them with a commercially available 3-D CFD program. The TRIGA Mark-II reactor, designed by General Atomics and located at Kansas State University, is a class of small pool type inherently safe research reactor licensed to operate at steady state power of up to 1.25 MW. It has a cylindrical core measuring 0.45 meters diametrically and 0.38 meters axially positioned in a tank measuring 1.98 meters diametrically and 6.25 meters axially. It has uranium zirconium hydride (UZrH) fuel rods housed in stainless steel cladding material arranged in five concentric rings (B,C,D,E and F rings, in that order, moving outwards from the center). TRIGA fuel is nominally 20% enriched, but the reactivity of the fuel can be changed by using burnable poisons (not used at KSU), or by varying the total weight percent of uranium in the UZrH fuel meat. The TRIGA reactor is designed to be an inherently safe reactor and is designed to be cooled by natural convection. Thus it is of paramount importance to avoid the film boiling regime; failing to do so will subject the fuel to severe conditions, possibly resulting in its failure due to fuel/clad interactions. A high DNBR ratio is a primary consideration in the reactor core design and thus any modification in the core should ensure that this criteria is always met. In order to fully utilize the capabilities of KSU TRIGA reactor facility, it should be operated at its full capacity, i.e. 1.25 MW, which requires increasing the fuel loading in some of the E- and F-ring elements from 8.5% U (nominal) to 12.0% U (nominal). Only four elements are to be switched to 12% loading, causing local power peaking in these elements. The degree of power peaking to be expected in these 12%-loaded fuel elements was calculated based on a detailed MCNP (Monte Carlo N-Particle code) model of the reactor core. Some preliminary results of the calculations are presented in this paper based on changes in peaking factors and power levels. To predict reactor thermal behavior, axial changes in the peaking factors obtained from MCNP models were used to calculate volumetric energy density functions for a single channel one dimensional RELAP model and a three dimensional COMSOL model of the TRIGA MARK-II reactor. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Regulatory Technology Development Plan - Sodium Fast Reactor. Mechanistic Source Term - Trial Calculation. Work Plan

The overall objective of the SFR Regulatory Technology Development Plan (RTDP) effort is to identify and address potential impediments to the SFR regulatory licensing process. In FY14, an analysis by Argonne identified the development of an SFR-specific MST methodology as an existing licensing gap with high regulatory importance and a potentially long lead-time to closure. This work was followed by an initial examination of the current state-of-knowledge regarding SFR source term development (ANLART-3), which reported several potential gaps. Among these were the potential inadequacies of current computational tools to properly model and assess the transport and retention of radionuclides during a metal fuel pool-type SFR core damage incident. The objective of the current work is to determine the adequacy of existing computational tools, and the associated knowledge database, for the calculation of an SFR MST. To accomplish this task, a trial MST calculation will be performed using available computational tools to establish their limitations with regard to relevant radionuclide release/retention/transport phenomena. The application of existing modeling tools will provide a definitive test to assess their suitability for an SFR MST calculation, while also identifying potential gaps in the current knowledge base and providing insight into open issues regarding regulatory criteria/requirements. The findings of this analysis will assist in determining future research and development needs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

LLNL IPD Tasks: ICSBEP and Pulsed Spheres Benchmark [Slides]

This lecture presented benchmark of the blank and polyethylene spheres at SINBAD in April 2023. In responding to comments about the building, we uncovered a large amount of additional detailed information about the building and experimental set up. We incorporated this new information into an even higher fidelity model and are working on uncertainty analysis at a low level. Scheduled to present at SINBAD meeting in April 2024.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗