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LSAFE: a Lightweight Static Analysis Framework for binary Executables

Static analysis is a widely used technique for analyzing various aspects of programs. However, as programs become more complex, static analysis tools require larger resources, such as CPU time and memory, to perform the same tasks. Moreover, the source code of programs may not always be accessible, requiring static analysis to be performed on the binary executable code directly. To overcome these challenges, we propose a lightweight static analysis framework called LSAFE, which constructs control flow graphs (CFGs) and data dependency graphs (DDGs) of target programs with optimized performance in terms of CPU and memory usage. We evaluated the proposed framework using both Spec benchmark programs and real-world industrial applications, and found that it outperformed Angr, an existing state-of-the-art static analysis tool. Additionally, we demonstrate a case study that utilizes the CFG generated by LSAFE to detect memory leaks.

Qu, Guangzhi↗

Tank 49H Solids Disturbance Analysis

Tank 49H will serve as the feed tank for the Salt Waste Processing Facility (SWPF). Transfers into Tank 49H may disturb solids that have settled to the bottom of the tank, resulting in feed that may exceed the insoluble solids content limit of 1,200 mg/L from the SWPF Waste Acceptance Criteria (WAC). During a transfer into Tank 49H, material that free falls into Tank 49H through a downcomer and passes through the supernate could potentially disturb the solids on the bottom of the tank and scour or suspend solids from a settled solids layer or turbid region. A previous analysis and report evaluated the potential to disturb solids when transferring into Tank 49H through the B4 riser and recommended a minimum tank level of 120 inches to prevent disturbing any solids in the bottom of the tank. The scope of this task is to perform additional fluid flow analysis to determine the impact of a “plunging jet” through the C3 downcomer on solids in Tank 49H and to determine a minimum liquid level to be maintained in Tank 49H prior to transfers that will minimize disturbing the solids and exceeding the SWPF WAC limits for insoluble solids carryover to SWPF since the C3 riser downcomer is at a lower elevation and farther away from the B5 transfer pump than the B4 downcomer.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Tank 49H Solids Disturbance Analysis

Tank 49H will serve as the feed tank for the Salt Waste Processing Facility (SWPF). Transfers into Tank 49H may disturb solids that have settled to the bottom of the tank, resulting in feed that may exceed the insoluble solids content limit of 1,200 mg/L from the SWPF Waste Acceptance Criteria (WAC). During a transfer into Tank 49H, material that free falls into Tank 49H through a downcomer and passes through the supernate could potentially disturb the solids on the bottom of the tank and scour or suspend solids from a settled solids layer or turbid region. A previous analysis and report evaluated the potential to disturb solids when transferring into Tank 49H through the B4 riser and recommended a minimum tank level of 120 inches to prevent disturbing any solids in the bottom of the tank. The scope of this task is to perform additional fluid flow analysis to determine the impact of a “plunging jet” through the C3 downcomer on solids in Tank 49H and to determine a minimum liquid level to be maintained in Tank 49H prior to transfers that will minimize disturbing the solids and exceeding the SWPF WAC limits for insoluble solids carryover to SWPF since the C3 riser downcomer is at a lower elevation and farther away from the B5 transfer pump than the B4 downcomer.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Tank 49H solids disturbance analysis

Tank 49H serves as the feed tank for the Salt Waste Processing Facility (SWPF). Transfers into Tank 49H may disturb any solids that have settled to the bottom of the tank, resulting in feed that may exceed the insoluble solids content limit of 1,200 mg/L of the SWPF Waste Acceptance Criteria (WAC). During a transfer into Tank 49H, material that free falls into Tank 49H through a downcomer could potentially disturb any solids on the bottom of the tank and scour or suspend solids from a settled solids layer or turbid region. A previous analysis and report evaluated the potential to disturb solids when transferring into Tank 49H through the B4 riser and recommended a minimum tank level of 120 inches to prevent disturbing any solids in the bottom of the tank. The scope of this task is to perform additional fluid flow analysis to determine whether accounting for disturbed particle settling and particle mixing and dispersion during transfer could allow the minimum liquid level to be reduced below 120 inches. The analysis utilized models from the technical literature to calculate the size and shape of the “plunging jet” as a function of input parameters such as initial velocity, initial jet diameter, elevation of the initial jet, liquid level in the tank, and solids depth. The analysis relied on the M-Star® simulations performed for the previous analysis to provide bounding estimates of the amount of solid particles disturbed and used the MStar® software to calculate the dispersion and mixing of the disturbed solids with other liquid in the tank as the solids are transported to the transfer pump. The analysis showed that with a solid particle size of 5 micron or less, a liquid level of 120 inches should be maintained to prevent significant disturbance of the solid layer at the bottom of Tank 49H.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Well Integrity for Natural Gas Storage in Depleted Reservoirs and Aquifers

Introduction Motivation The 2015-2016 Aliso Canyon/Porter Ranch natural gas well blowout emitted approximately 100,000 tonnes of natural gas (mostly methane, CH 4 ) over four months. The blowout impacted thousands of nearby residents, who were displaced from their homes. The high visibility of the event has led to increased scrutiny of the safety of natural gas storage at the Aliso Canyon facility, as well as broader concern for natural gas storage integrity throughout the country. Federal Review of Well Integrity In April of 2016, the U.S. Department of Energy (DOE), in conjunction with the U.S. Department of Transportation (DOT) through the Pipeline and Hazardous Materials Safety Administration (PHMSA), announced the formation of a new Interagency Task Force on Natural Gas Storage Safety. The Task Force enlisted a group of scientists and engineers at the DOE National Laboratories to review the state of well integrity in natural gas storage in the U.S. The overarching objective of the review is to gather, analyze, catalogue, and disseminate information and findings that can lead to improved natural gas storage safety and security and thus reduce the risk of future events. The “Protecting our Infrastructure of Pipelines and Enhancing Safety Act of 2016’’ or the ‘‘PIPES Act of 2016,’’which was signed into law on June 22, 2016, created an Aliso Canyon Natural Gas Leak Task Force led by the Secretary of Energy and consisting of representatives from the DOT, Environmental Protection Agency (EPA), Department of Health and Human Services, Federal Energy Regulatory Commission (FERC), Department of Commerce and the Department of Interior. The Task Force was asked to perform an analysis of the Aliso Canyon event and make recommendations on preventing similar incidents in the future. The PIPES Act also required that DOT/PHMSA promulgate minimum safety standards for underground storage that would take effect within two years. Background on the DOE National Laboratories Well Integrity Work Group One of the primary areas that the Task Force is studying is integrity of natural gas wells at storage facilities. The DOE Office of Fossil Energy (FE) took the lead in this area and asked scientists and engineers from the National Energy Technology Laboratory (NETL), Lawrence Livermore National Laboratory (LLNL), Sandia National Laboratories (SNL), and Lawrence Berkeley National Laboratory (LBNL)) to form a Work Group to address this area. This Work Group is an expansion of the original “Lab Team” comprising scientists and engineers from SNL, LLNL, and LBNL which was formed to support the State of California’s response to the Aliso Canyon incident and operated under the Governor of California’s Aliso Canyon Emergency Order (1/6/2016). The Lab Team played a key role in advising the State of California’s Department of Conservation (DOC) in its oversight of SoCalGas during and after the incident.

03 NATURAL GAS↗

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Home Energy Professionals Certifications ISO/IEC 17024: 2021 Policies and Procedures Manual

The U.S. Department of Energy (DOE) enlisted its National Renewable Energy Laboratory (NREL) to coordinate the development of a framework for new certifications in the weatherization and home performance industry. The Home Energy Professional certifications support DOE's Weatherization Assistance Program (WAP) and the broader residential home performance industry through the credentialing process of defined job task analysis for energy auditors and quality control inspectors. The HEP certifications are not intended to supplant or infringe upon any existing industry-recognized credentials, however, the WAP and the home performance industry have utilized the advanced HEP certifications to promote quality work and standardized job task analysis since 2010. On an ongoing basis, NREL brings industry practitioners and subject matter experts together to develop, review, and revise the certification schemes in accordance with the International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) 17024 standard, "Conformity assessment - General requirements for bodies operating certification of persons" (ISO/IEC 17024). This handbook covers the policies and procedures for the process of developing, maintaining, and validating the certification schemes. Each policy and procedure includes the relevant ISO/IEC 17024 section at the beginning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Demystifying the Resilience of Large Language Models: An End-to-End Perspective

Deep neural networks are known to be resilient to random bit-wise faults in their parameters. However, this resilience has primarily been established through evaluations of classification models. The extent to which this claim holds for large-language models remains underexplored. In this work, we conduct an extensive measurement study on the impact of random bitwise faults in commercial-scale language models. We perform an in-depth analysis of the resulting generation outputs. We first expose that these language models are not truly resilient to random bit-flips. While aggregate metrics such as accuracy may suggest resilience, an in-depth inspection of the generated outputs shows significant degradation in text quality. Our analysis also shows that tasks requiring more complex reasoning suffer more from performance and quality degradation. Moreover, we extend our analysis to models with augmented reasoning capabilities, such as Chain-of-Thought or Mixture of Experts architectures, and characterize their failure scenarios under random bit-flips.

Sun, Yu↗

Gamma Spectrometry Code Rodeo for Uranium Enrichment—FY 2022 Report

In the first two quarters of FY22, data acquisition continued at ORNL and LLNL using uranium sources of known enrichments. This was an FY21 task which could not be completed in FY21 because of problems encountered with the ORNL M400 CZT in Q4 of FY21, and the subsequent repairs. The detector was received back from H3D in the first of September 2021 , and the measurements resumed . Measurements using the repaired detector were completed in Q1 of FY22. The spectra were distributed by ORNL to the analyzing labs. Analysis results were received in Q2 of FY2022. The results from the various codes were intercompared and an ANOVA analysis was performed. Random and systematic uncertainties were established for each code. The ANOVA results and discussions were included in a revised version of FY21Annual Report issued in March 2022. A paper was presented at the INMM 2022Annual Conference, with the analysis results from the various isotopic codes, and the ANOVA table with random and systematic uncertainties. The Project Work Plan (PWP) for FY22 included a task to perform field testing of the M400 CZT and the analysis codes using UF 6 cylinder measurements at the Framatome Fuel Fabrication Facility in Richland, WA. PNNL was the lead for the field testing task. PNNL drafted a Field Test Plan, and refined it based on comments received from the team. PNNL coordinated with Framatome facility, the logistics of carrying out the field testing . A collimator and shield made out of TFlex (tungsten impregnated polymer) was designed and professionally manufactured. The collimators were used in the field test measurements. The measurements at Framatome were completed on April 21, 2022. A total of 34 Type 30B cylinders were measured using three M400 detectors (PNNL, LLNL, and ORNL detectors). Measurements using M400 were taken at two locations on the side of each cylinder and from the end-on bottom location. Additionally, HPGe measurements were taken at the end-on location to establish ground truth. Cylinder wall thickness measurements were also made at all three locations. To gain a better understanding of the effect of background from surrounding cylinders, the same five cylinders measured individually in low background locations were measured again in the cylinder storage yards. Due to inclement weather, manufacturer delays, shipping delays, and equipment failure, the measurement campaign spanned twice as long compared to the original timeline. Gamma-ray spectra from M400 and HPGe detectors, along with the cylinder data and photographs were organized and shared with the collaborators for further analysis. Spectra were analyzed by the participating laboratories. FY22 PWP also consists of tasks related to plutonium source measurements, adapting the codes to analyze plutonium spectra, and inter-comparison of the results from various codes. Plutonium spectra are being acquired at LANL, ORNL, and LLNL. LANL, SNL and LLNL are in the process of modifying FRAM, GADRAS, and CZTU, respectively. The plutonium related tasks will be completed in Q2 of FY23.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Accelerator Neutrino Neutron InteractionExperiment: Design, Construction and Preparationfor First Physics

This thesis covers work performed for the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) between 2015 and 2020. ANNIE is a beamline neutrino experiment located at the Fermi National Accelerator Laboratory in Chicago. Its primary physics goals are the measurement of neutrino interaction cross-sections on oxygen, and a measurement of the multiplicity of final state neutrons from these interactions, both as functions of final state kinematics. In order to achieve these goals ANNIE will be pioneering the use of Large Area Picosecond Photodetectors and the use of gadolinium doping to enhance neutron visibility in a water Cherenkov detector. Over the time period of this thesis the ANNIE detector was constructed, an initial 'Phase I' background run was completed, the detector was decommissioned and then substantially upgraded in preparation for the main 'Phase II' physics run. At the time of writing ANNIE is being re-commissioned, with Phase II data taking anticipated to begin in 2021. During this time I spent 21/2 years on-site contributing to almost all aspects of hardware work, while performing software development for the simulation and analysis frameworks. As my first software task I developed Monte Carlo simulations of the detector response, based on the WCSim framework. While thismore » framework provided a starting point for the tank simulation significant modifications were required to implement the complete ANNIE detector system. This included a rewrite of the geometry, along with modifications to the photosensor definitions, hit collections, digitization, triggering, input and output interfaces, etc. To take advantage of improved modelling of neutrons in Geant4.10 the physics lists were also reimplemented in the new version format. As part of this work I determined performance metrics based on the output files, calculating kinematic acceptance, detector efficiency and expected event rates. My contributions on reconstruction focused primarily on the MRD, for which I implemented two track reconstruction algorithms, specialised for high and low energy muons. The high energy algorithm achieves >90% efficiency for tracks with at least 8 hits, and is robust against dead paddles and unrelated hits. The low energy algorithm performs a search in combination with tank information to provide sensitivity down to a single MRD hit. Early data handling work for the Phase I background run included writing the code for handling TDC hits and performing studies on neutron detection without the requirement of multi-hit coincidence. As the collaboration moved to a new framework for the Phase II analysis I performed a substantial amount of work to develop the codebase, implementing tools to perform tasks such as file IO, data parsing, waveform processing, event building, timestamp alignment, time clustering, hit residual calculation, event visualisation etc. I helped develop the python API for integrating multi-language tools, and ported the framework into a Singularity container to provide a self-contained environment that…« less

43 PARTICLE ACCELERATORS↗

Semi-Annual Report for Modular Integrated Gas High Temperature Reactor Development during Performance Period April 2022 - September 2022

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multidisciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary coolant system to ensure temperatures within the core remain below safety margins during steady-state and potential accident scenarios. This second semi-annual report summarized the progress made at Argonne on the two tasks during the second half of FY22. As a part of the RCCS design task, a scoping calculation in estimating HVAC capability for the HC-HTGR reactor building was performed. A water panel modeling study was first performed with the test case, which confirms the capability of the RELAP5-3D modeling approach to explore various design options of the HC-HTGR RCCS under consideration. Then, a reference RELAP5-3D model for the unit geometry of the preliminary design of the HC-HTGR RCCS was developed. A preliminary performance analysis was conducted to evaluate the performances of a single-phase natural circulation and panel conduction in various operating conditions. For the primary coolant system analysis task, preliminary thermal hydraulic analysis of the HC-HTGR core design was performed with a high resolution 1D fluid-3D solid coupled model using the System Analysis Module (SAM) to assess the assembly coolant channel and bypass flow mass flow rate distribution. Some preliminary work on the development of a full core reduced order model was discussed following the assembly level model to predict the core wide coolant flow distribution and to model certain operational and accidental transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Big Data Analysis of Massive PMU Datasets: A Data Platform Perspective

The discovery of `event signatures' and useful insights from very large historical Phasor Measurement Unit (PMU) datasets is predicated on offline Big Data analysis approaches that rely on the generation of predictive features on a massive scale. This paper presents lessons learned from a data platform perspective towards reducing barriers to adoption of Big Data analytics against a real dataset of almost half a trillion data points drawn from over 400 PMUs distributed across the North American power grid. We demonstrate software abstractions and targeted performance optimizations that can lead to significant productivity gains for power systems researchers seeking to perform offline exploratory temporal analysis and modeling tasks, with a focus on feature generation. We describe how our optimized approach goes beyond a naive application of mainstream Big Data technologies, enabling feature generation tasks, that previously took days or even weeks, to now be completed in just a few hours.

Kumar, Vijay S.↗

wastewater_virus

This repo contains software used to clean and assemble high-throughput sequencing data containing viruses. The input is raw illumina sequencing reads and the output is a database of high-quality viral genomes. The specific application is to wastewater viral concentrates but it is not restricted to that sample type. The software is composed of Nextflow workflows and a set of custom Python and bash scripts that call publicly available bioinformatics tools to accomplish obvious tasks in data analysis in a high performance computing environment. For detailed information, please see the repo's README file.

Kantor, Rose [Lawrence Livermore National Laborato↗

Radiological Operations Support Specialist (ROSS) Pilot Course Summary and Recommendations

In support of the Department of Homeland Security / Science and Technology Directorate’s (DHS/S&T) creation of a new position called the Radiological Operations Support Specialist (ROSS), Lawrence Livermore National Laboratory (LLNL) in Sub-task 1.1 and 1.2 has assisted in the development of the ROSS skills, knowledge, and abilities (SKAs); identified potentially relevant training; cross-mapped the training to the SKAs; and identified gaps in the training related to the SKAs, as well as their respective level of training knowledge - current versus desired. In the follow on task, Sub-task 1.3, a 5 day ROSS Pilot Training course was developed to fill the priority gaps identified in Sub-Task 1.2. Additionally, in Sub-Task 1.5, LLNL has performed a gap analysis of electronic tools, handbooks, and job-aides currently available to the ROSS and developed recommendations for additional and next generation tools to ensure the operational effectiveness of the ROSS position. This document summarizes the feedback received from the instructors and pilot course observers on what worked in the course and what could be improved as well as an assessment of the Pre- and Post-Test administered to the students.

61 RADIATION PROTECTION AND DOSIMETRY↗

Documentation for Python Automation in CYME for DER Hosting Capacity Analysis of Different Feeder Configurations

This file provides the documentation for several Python scripts that were developed by Sandia National Laboratories to enhance the automation and customization capabilities for performing various distribution system planning and analysis tasks in CYME. Specifically, these scripts (.py files detailed in Figure 1) enable the user to evaluate different distribution system configurations and the resulting impacts on hosting capacity results and other metrics. In general, these scripts—and the accompanying documentation—provide the foundation upon which future customized tools can be created. For example, the scripts show how to extract and modify parameters of various circuit components, set up and run analyses using built-in CYME tools (iteratively), and export reports for further evaluations and comparisons. Thus, the capabilities and syntaxes used in the scripts can be adapted and leveraged for countless other objectives.

97 MATHEMATICS AND COMPUTING↗

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental Data Curation at Large Instrument Facilities with Open Source Software

The National Synchrotron Light Source II operating at Brookhaven National Laboratory since 2014 for the US Department of Energy is one of the newest and brightest storage-ring synchrotron facility in the world. NSLS-II, like other facilities, provides pre-processing of the raw data and some analysis capabilities to its users. We describe the research collaborations and open source infrastructure developed at large instrument facilities such as NSLS-II for the purpose of curating high value scientific data along the early stages of the data lifecycle. Data acquisition and curation tasks include storing experiment configuration, detector metadata, raw data acquisition with infrastructure that converts proprietary instrument formats to industry standards. In addition, we describe a specific effort for discovering sample information at NSLS-II and tracing the provenance of analysis performed on acquired images. We show that curation tasks must be embedded into software along the data life cycle for effectiveness and ease of use, and that loosely defined collaborations evolve around shared open source tools. Finally we discuss best practices for experimental metadata capture in such facilities, data access and the new challenges of scale and complexity posed by AI-based discovery for the synthesis of new materials.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies

This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory---identifying useful workflows and methods for ROM generation---and not meant to be a catch-all analysis of HTGR ROM generation and usage for optimization. This report summarizes three tasks performed in Fiscal Year 2022: 1) the creation of HTGR model, 2) the sensitivity analysis of model design parameters, and 3) an introduction to ROM generation techniques. The representative HTGR model created in this work is a multiphysics equilibrium-core using the BlueCRAB (comprehensive reactor analysis bundle) reactor analysis application, coupling four physical phenomena: neutronics, streamline depletion, porous flow thermal hydraulics, and pebble heat conduction. Part of the model creation was identifying some design parameters and quantities of interest that are relevant in an optimization analysis and adjustable in the model. The sensitivity analysis utilized a polynomial chaos expansion methodology to compute global sensitivity metrics. This analysis showed that thermal hydraulics parameters and quantities of interest had a relatively small impact on simulation results. Finally, the ROM generation work involved exploring three different ROM methodologies: polynomial regression, a Gaussian process, and artificial neural networks. Using a cross-validation technique to characterize ROM performance, the Gaussian process and single-layer artificial neural networks showed the most promising results. Overall, this study was insightful and the lessons learned will be invaluable for the eventual development of an HTGR design optimization workflow.

97 MATHEMATICS AND COMPUTING↗