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At least 883 records · Page 49

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DOE OSTI2018

Software Requirements of SNAP for Editing MELCOR 2.2 Models

Applications of the severe accident analysis code MELCOR, developed for the U.S. Nuclear Regulatory Commission (NRC) by Sandia National Laboratories (SNL), have been supported by the graphical user-interface and post-processing suite Symbolic Nuclear Analysis Package (SNAP), developed for the NRC by Applied Programming Technology (APT). With the release of MELCOR 2.2, new user functionality and models have been introduced and an update to the SNAP MELCOR plugin user interface is necessary to access these new features. This document relates all new features introduced into MELCOR to the development team at APT as well as the NRC.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Test based reliability assessment method for a safety critical software in reactor protection system - 284

Digitalization of the instrumentation and control systems in nuclear power plant entails some new features which do not exist in analog systems. When the new features are applied in safety critical systems, the risk stemming from them should be quantified properly to assure the reliability of the entire power plant. Among the new features, software is considered as the most important factor because it can cause common cause failure to many redundant systems. Therefore, in this work, a test based reliability assessment method for a safety-critical software is developed. An output of a software is determined by not only inputs but also the internal state of the software at the time. In the case of safety critical software developed for usage in nuclear power plant, it is possible to directly investigate probable internal states thanks to detailed design specification and programing features, and the probable inputs also can be identified based on the physical linearity of each process parameter and hardware characteristics related to data acquisition. In this work, a development method for practical exhaustive test case consisting of investigation of internal state and probable input sets to a specific internal state are suggested. In addition to this, software logic simulator for execution of software logic test and the reliability quantification method based on the test result are developed. The feasibility of the suggested method is demonstrated via a case study. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Domain Specific Language Support for Exascale

Domain-Specific Languages (DSLs) offer an attractive path to Exascale software since they provide expressive power through appropriate abstractions and enable domain-specific optimizations. But the advantages of a DSL compete with the difficulties of implementing a DSL, even for a narrowly defined domain. The DTEC project addresses how a variety of DSLs can be easily implemented to leverage existing compiler analysis and transformation capabilities within the ROSE open source compiler as part of a research program focusing on Exascale challenges. The OSU contributions to the DTEC project are in the area of code generation from high-level DSL descriptions, as well as verification of the automatically-generated code.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Multi–LDAP Dynamic User Management Tool Utilizing Oracle Application Express and PL/SQL

A Center for Infrastructure Security Analysis (CISA) client system required support of multiple Lightweight Directory Access Protocol (LDAP) directories for multiple, varied user communities. The LDAP directories were all based upon different technologies, i.e., Microsoft Active Directory (AD), Microsoft Active Directory Lightweight Directory Services (ADLDS), and Oracle Internet Directory (OID), depending on system setup, security requirements, and legacy software. Research revealed that PL/SQL provided the capability to execute dynamic PL/SQL and SQL blocks. The dynamic capabilities were utilized along with several configuration tables to provide an object-oriented, polymorphic-like behavior. This architecture was chosen so that a top-level application programming interface (API) could be defined for all calls, no matter what type of LDAP was being manipulated, as each LDAP type has slightly different attributes and requirements. The dynamic nature of the user management system allowed for easy setup and utilization of any new LDAP directories, minimizing the time and effort expended on system changes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Deploying and Tracking Software with NCCS Software Provisioning

The National Center for Computational Sciences (NCCS) at Oak Ridge National Laboratory has a long history of deploying ground-breaking leadership-class supercomputers for the U.S. Department of Energy. The latest in this line of supercomputers is Frontier, the first supercomputer to break the exascale barrier (1018 floating-point operations per second) on the TOP500 list. Frontier serves a wide array of scientific domains, from traditional simulation-based workloads to newer AI and Machine Learning workloads. To best serve the NCCS user community, NCCS uses Spack to deploy a comprehensive software stack of scientific software packages, providing straightforward access to these packages through Lmod Environment Modules. Maintaining a large software stack while also including multiple new compiler releases each year is a very time-consuming task. Additionally, it is not straightforward to provide a software stack alongside existing vendor-provided software such as the HPE/Cray Programming Environment (CPE), and existing CPE, Spack, and Lmod integration does not allow for multiple versions of GPU libraries such as AMD’s ROCm to be used. To address these challenges and shortcomings, NCCS has developed the NCCS Software Provisioning tool (NSP)1, a tool for deploying and monitoring software stacks on HPC systems. NSP allows NCCS to quickly and effectively provision software stacks from the ground up using template-driven recipes and configuration files. NSP is successfully deployed on Frontier and several other NCCS clusters, enabling the NCCS software team to quickly deploy software stacks for newly-released compilers, expand current software offerings, better support GPU-based software, and monitor Lmod module usage to identify unused software packages that can be removed from the software stack. In this work, we discuss the shortcomings of the previous CPE, Spack, and Lmod usage at NCCS, provide further details on the implementation and structure of NSP, then discuss the benefits that NSP provides.

Rentschler, Asa [ORNL] (ORCID:0009000597694743)↗

DOE OSTI2020

RAMSeS: Rapid Analysis of Mission Software Systems

Over the past few decades, software has become ubiquitous as it has been integrated into nearly every aspect of society, including household appliances, consumer electronics, industrial control systems, public utilities, government operations, and military systems. Consequently, many critical national security questions can no longer be answered convincingly without understanding software, including its purpose, its capabilities, its flaws, its communication, or how it processes and stores data. As software continues to become larger, more complex, and more widespread, our ability to answer important mission questions and reason about software in a timely way is falling behind. Today, to achieve such understanding of third-party software, we rely predominantly on the ability of reverse engineering experts to manually answer each particular mission question for every software system of interest. This approach often requires heroic human effort that nevertheless fails to meet current mission needs and will never scale to meet future needs. The result is an emerging crisis: a massive and expanding gap between the national security need to answer mission questions about software and our ability to do so. Sandia National Laboratories has established the Rapid Analysis of Mission Software Systems (RAMSeS) effort, a collaborative long-term effort aimed at dramatically improving our nation’s ability to answer mission questions about third-party software by growing an ecosystem of tools that augment the human reverse engineer through automation, interoperability, and reuse. Focusing on static analysis of binary programs, we are attempting to identify reusable software analysis components that advance our ability to reason about software, to automate useful aspects of the software analysis process, and to integrate new methodologies and capabilities into a working ecosystem of tools and experts. We aim to integrate existing tools where possible, adapt tools when modest modifications will enable them to interoperate, and implement missing capability when necessary. Although we do hope to automate a growing set of analysis tasks, we will approach this goal incrementally by assisting the human in an ever-widening range of tasks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Secure Sensor Platform Software Utilities v.2.0

The SSP Software package allows a user to connect to a CoCIM via a Personality Programmer and: Reset the firmware of the CoCIM using the SSP Personality Programmer. The changes that can be made include things such as: Recovering from a tamper event; Resetting the initialization date and message counter; Change configuration values of the CoCIM using the SSP Seal Configuration or the RMSA Configuration File Editor programs. Configuration values that can be set will depend on what version of the CoCIM firmware is being used, but can include: The IP address of the translator with which this CoCIM (or RMSA) communicates; The number of attempts the CoCIM (or RMSA) will attempt to contact the translator; The primary CoCIM (or RMSA) channel; The secondary CoCIM (or RMSA) channel; Locations of files containing CoCIM (or RMSA) encryption keys SSPSerialDataDumper downloads a CoCIM’s stored messages to a computer connected to the CoCIM via a serial cable; SSPLogAnalyzer decrypts and authenticates messages that have been downloaded using the Serial Data Dumper program and then displays the messages values.

Hymel, Ross↗

DOE OSTI2024

Large language model evaluation for high–performance computing software development

We apply AI-assisted large language model (LLM) capabilities of GPT-3 targeting high-performance computing (HPC) kernels for (i) code generation, and (ii) auto-parallelization of serial code in C ++, Fortran, Python and Julia. Our scope includes the following fundamental numerical kernels: AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG, and language/programming models: (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). Kernel implementations are generated using GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code given simple + + prompt variants. To quantify and compare the generated results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. For auto-parallelization, we use ChatGPT interactively giving simple prompts as in a dialogue with another human including simple “prompt engineering” follow ups. Results suggest that correct outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding language keywords, while Julia prompts perform acceptably well for its Threads and CUDA.jl programming models. Finally, we expect to provide an initial quantifiable point of reference for code generation in each programming model using a state-of-the-art LLM. Overall, understanding the convergence of LLMs, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking (FY2020 Progress Report)

3013 corrosion↗

DOE OSTI2021

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Understanding Data Structures by Extracting Memory Access Graphs

Understanding the data structures employed by a program is important for reverse engineering activities and can improve the results of automated software analysis techniques. In a compiled binary, access to data structure fields and array indices defined in the source program are replaced by raw pointer arithmetic. We present a representation for capturing the essential details of how a program accesses memory regions, which we call a Memory Access Graph (MAG), and a static analysis for automatically extracting this information from a program binary. The static analysis to extract the MAGs from the program is straightforward and does not require sophisticated integer or pointer analysis. The MAGs are readily understood by reverse engineers; they are generally able to perceive the data structure definition corresponding to a MAG. We briefly discuss automatic extraction of structure definitions outlining some of the difficulties in doing so.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

October 2019 SAPHIRE 8 Software Quality Assurance Oversight Status Report

The software quality assurance oversight consists of updating and maintaining revision control of the System Analysis Program for Hands-on Integrated Reliability Evaluations (SAPHIRE) Version 8 quality assurance program documentation and of monitoring revision control of the SAPHIRE Version 8 source code. This report summarizes the oversight efforts through description of the revision control system (RCS) setup, operation and contents. Documents maintained under revision control include the Acceptance Test Plan (ATP), Configuration Management Plan, Quality Assurance Plan, Software Project Plan, Requirements Traceability Matrix (RTM), System Test Plan, Significance Determination Process (SDP) Interface Training Manual, and the SAPHIRE 8 “New Features and Capabilities Overview.” These documents are referred to and can be transmitted upon request of the Nuclear Regulatory Commission (NRC) Contracting Officer’s Representative (COR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

A parametric SPICE model for the simulation of spark gap switches

The use of SPICE-based software for the simulation of pulsed power systems—even large complex systems—has become commonplace in the pulsed power community. This is in contrast to earlier work in the field that relied on specially developed simulation codes such as Sandia’s Screamer or the Navy Research Lab’s Bertha, which natively incorporated models for common pulsed power components such as spark gap switches. Unlike these programs, SPICE programs provide a simple and familiar user interface and wide availability. However, SPICE programs do not include realistic models for key pulsed power circuit devices—including the spark gap switch. While simple switch models do exist in SPICE programs, these can only crudely approximate the behavior of a spark gap. This effort focuses on developing an SPICE circuit model for a gas-filled spark gap switch that is physically realistic while being simple enough to permit simulations to run in reasonable times on typical personal computers. Detailed information is provided for implementation in two common versions of SPICE: LTspice and Orcad PSPICE. Adaptation to other SPICE programs is possible with minimal modification. The model is intended as a design tool that uses physical parameters as inputs to connect it directly to the development of useable pulsed power systems. Data collected from the operation of a high-pressure pulsed-charged switch and a complete 12-stage Marx generator have been used to demonstrate the implementation and accuracy of the model over a wide range of parameters.

Pouncey, J. Cameron (ORCID:0000000153500816)↗

DOE OSTI2015

A Research Roadmap for Computation-Based Human Reliability Analysis

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is often secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

TU-FG-201-03: Automatic Pre-Delivery Verification Using Statistical Analysis of Consistencies in Treatment Plan Parameters by the Treatment Site and Modality

Purpose: A novel computer software system, namely APDV (Automatic Pre-Delivery Verification), has been developed for verifying patient treatment plan parameters right prior to treatment deliveries in order to automatically detect and prevent catastrophic errors. Methods: APDV is designed to continuously monitor new DICOM plan files on the TMS computer at the treatment console. When new plans to be delivered are detected, APDV checks the consistencies of plan parameters and high-level plan statistics using underlying rules and statistical properties based on given treatment site, technique and modality. These rules were quantitatively derived by retrospectively analyzing all the EBRT treatment plans of the past 8 years at authors’ institution. Therapists and physicists will be notified with a warning message displayed on the TMS computer if any critical errors are detected, and check results, confirmation, together with dismissal actions will be saved into database for further review. Results: APDV was implemented as a stand-alone program using C# to ensure required real time performance. Mean values and standard deviations were quantitatively derived for various plan parameters including MLC usage, MU/cGy radio, beam SSD, beam weighting, and the beam gantry angles (only for lateral targets) per treatment site, technique and modality. 2D-based rules of combined MU/cGy ratio and averaged SSD values were also derived using joint probabilities of confidence error ellipses. The statistics of these major treatment plan parameters quantitatively evaluate the consistency of any treatment plans which facilitates automatic APDV checking procedures. Conclusion: APDV could be useful in detecting and preventing catastrophic errors immediately before treatment deliveries. Future plan including automatic patient identify and patient setup checks after patient daily images are acquired by the machine and become available on the TMS computer. This project is supported by the Agency for Healthcare Research and Quality (AHRQ) under award 1R01HS0222888. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A Business Case for Advanced Outage Management

The Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops and validates technologies that will make the U.S. operating nuclear fleet more efficient and competitive. The program has developed a standard methodology for determining the impact of new technologies in order to assist nuclear power plant (NPP) operators in building sound business cases. This paper presents a generic business case for implementation of technology that supports Advanced Outage Management (AOM). The analysis presented demonstrates that advanced communication and networking and analytical technologies will allow NPP to conduct outages with fewer people in management roles and the remaining people can be more effective and more productive. The benefits are quantified with a rough order of magnitude that provides directional guidance to NPPs that are interested in developing a similar business case. Advanced Outage Management is enabled by a suite of technologies, which are described in further detail in the body of this report. They include: • Mobile Work Packages (MWP) • Computer Based Procedures (CBP) • Personal Digital Assistants (PDA) also referred to as smart devices • Barcode readers • High bandwidth wireless networks • Collaboration software (i.e., OneNote) • Advanced digital displays • Advanced data analytics All the hardware necessary to implement AOM as envisioned in this report is readily available today. Configuration to perform within the plant systems and regulatory boundaries would need to be developed by the NPP. 1. The resulting business case demonstrates benefits in two major categories: 2. Reduction in resources required to manage the outage, a. Increased productivity in outage work that reduces the likelihood of schedule overruns: b. reduce likelihood of bulk work resulting in outage delays c. improved management of critical path single issues, d. improved management of emergent work (improve time to collect data and prepare response) It is important to note that in order to realize these benefits at the scale described in this report requires the plant to rethink how technologies can disrupt current processes; how data might be captured, processed, analyzed and presented with little or no human intervention. In many cases, technology be fully utilized in a way that not only aides productivity, but is utilized towards “work destruction” – elimination of work that is currently performed through a human interface.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Solution of the C5G7 Benchmark using the MOCUM Transport Code with ANSYS Unstructured Mesh

The objective of this research is to use finite element analysis (FEA) software to perform the unstructured meshing for reactor geometries and port the mesh information to MOCUM code. This workflow takes the advantage of the mature meshing module of the mainstream FEA; reduces the development effort for nuclear codes; and increases the nuclear code accuracy by using high quality meshes. In this work, ANSYS is used to build the reactor model and perform the unstructured meshing. The mesh information is then imported to the MOCUM code, a method of characteristic (MOC) transport program supporting unstructured meshes, using a developed MATLAB script. This procedure is verified by modeling the C5G7 benchmark problem. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗