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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Tessera: Open source software for accelerated data science

Extracting useful, actionable information from data can be a formidable challenge for the safeguards, nonproliferation, and arms control verification communities. Data scientists are often on the “front-lines” of making sense of complex and large datasets. They require flexible tools that make it easy to rapidly reformat large datasets, interactively explore and visualize data, develop statistical algorithms, and validate their approaches—and they need to perform these activities with minimal lines of code. Existing commercial software solutions often lack extensibility and the flexibility required to address the nuances of the demanding and dynamic environments where data scientists work. To address this need, Pacific Northwest National Laboratory developed Tessera, an open source software suite designed to enable data scientists to interactively perform their craft at the terabyte scale. Tessera automatically manages the complicated tasks of distributed storage and computation, empowering data scientists to do what they do best: tackling critical research and mission objectives by deriving insight from data. We illustrate the use of Tessera with an example analysis of computer network data.

Sego, Landon H.↗
DOE OSTI2018

System Advisor Model (SAM) General Description (Version 2017.9.5)

This document describes the capabilities of the System Advisor Model (SAM) developed and distributed by the U.S. Department of Energy's National Renewable Energy Laboratory. The document is for potential users and others wanting to learn about the model's capabilities. SAM is a techno-economic computer model that calculates performance and financial metrics of renewable energy projects. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial models are for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (PPA). SAM's simulation tools facilitate parametric and sensitivity analyses, Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C plus plus, C sharp, Java, Python, MATLAB, and other languages. NREL provides both SAM and the SDK as free downloads at https://sam.nrel.gov. SAM is an open source project, so its source code is available to the public. Researchers can study the code to understand the model algorithms, and software programmers can contribute their own models and enhancements to the project. Technical support and more information about the software are available on the website.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

gPhoton: THE GALEX PHOTON DATA ARCHIVE

gPhoton is a new database product and software package that enables analysis of GALEX ultraviolet data at the photon level. The project’s stand-alone, pure-Python calibration pipeline reproduces the functionality of the original mission pipeline to reduce raw spacecraft data to lists of time-tagged, sky-projected photons, which are then hosted in a publicly available database by the Mikulski Archive at Space Telescope. This database contains approximately 130 terabytes of data describing approximately 1.1 trillion sky-projected events with a timestamp resolution of five milliseconds. A handful of Python and command-line modules serve as a front end to interact with the database and to generate calibrated light curves and images from the photon-level data at user-defined temporal and spatial scales. The gPhoton software and source code are in active development and publicly available under a permissive license. We describe the motivation, design, and implementation of the calibration pipeline, database, and tools, with emphasis on divergence from prior work, as well as challenges created by the large data volume. We summarize the astrometric and photometric performance of gPhoton relative to the original mission pipeline. For a brief example of short time-domain science capabilities enabled by gPhoton, we show new flares from the known M-dwarf flare star CR Draconis. The gPhoton software has permanent object identifiers with the ASCL (ascl:1603.004) and DOI (doi:10.17909/T9CC7G). This paper describes the software as of version v1.27.2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Microscopy image segmentation tool: Robust image data analysis

We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems that facilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Self-Admitted Technical Debt in Scientific Software: Prioritization, Sentiment, and Propagation Across Artifacts

Self-admitted technical debt (SATD) impairs scientific software (SSW), yet its prioritization, sentiment, persistence, and propagation remains underexplored. Understanding how SSW developers express, and address SATD is crucial for improving SSW maintenance, and tooling. This study investigates how SATD types and artifacts in SSW are prioritized, how sentiment relates to urgency, SATD removal and resolution rates, and the extent to which SATD propagates across artifacts. We analyzed nine SSW repositories using a SATD classification model and a semantic embedding-based prioritization heuristic. SATD was examined across multiple artifacts, with sentiment assessed via a fine-tuned transformer. Propagation was traced, priority scores compared to static analysis, and removal and resolution rates quantified. SATD in comments, commits, and pull requests receive higher priority than SATD in issues, with negative sentiment amplifying urgency. Resolution and removal rates lag behind open-source software (OSS) averages. Most SATD remains confined to the originating artifact, but longer propagation chains are rare and correlate with higher priority, highlighting persistent and high impact debt. Prioritization is influenced by artifact type and sentiment, while low removal and resolution rates signal persistent debt. Cross-artifact propagation marks high priority, unresolved SATD, providing empirical guidance for targeted monitoring, review prioritization, and tool supported maintenance in SSW.

Melin, Eric [Boise State University]↗
DOE OSTI2021

Continuous Integration, In-Code Documentation, and Automation for Nuclear Quality Assurance Conformance

The Multiphysics Object Oriented Simulation Environment (MOOSE) is an open-source, finite element framework for solving highly coupled sets of nonlinear equations. The development of the framework and applications occurs concurrently using an agile, continuous-integration software package. Included in the framework is an in-code, extensible documentation system. Using these two tools in union with the repository management tools GitHub and GitLab, a software quality plan was created and followed such that MOOSE and a MOOSE-based application (BISON) have been shown to meet the American Society of Mechanical Engineers’ Nuclear Quality Assurance-1 standard. The approach relies heavily on automation for both testing and documentation. The resulting effort demonstrates that a rigorous software quality plan may be implemented that incurs a minimal impact on day-to-day development of the software, satisfying the stringent guidelines necessary to operate the software in a safety function within a nuclear facility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Fenestration system energy performance research, implementation, and international harmonization

The research conducted by the NFRC and its contractors adds significantly to the understanding of several areas of investigation. NFRC enables manufacturers to rate fenestration energy performance to comply with building energy codes, participate in ENERGY STAR, and compete fairly. NFRC continuously seeks to improve its ratings and also seeks to simplify the rating process. Several research projects investigated rating improvement potential such as • Complex Product VT Rating Research • Window 6 and Therm 6 Validation Research Project • Complex Product VT Rating Research Conclusions from these research projects led to important changes and increased confidence in the existing NFRC rating process. Conclusions from the Window 6/Therm 6 project will enable window manufacturers to rate an expanded array of products and improve existing ratings. Some research lead to an improved new rating method called the Component Modeling Approach. A primary goal of the CMA was a simplification of the commercial energy rating process to increase participation and make the commercial industry more competitive and code compliant. The project below contributed towards CMA development: • Component Modeling Approach Condensation Resistance Research NFRC continues to implement the Component Modeling Approach program. The program includes the CMA software tool, CMAST, and several procedural documents to govern the certification process. This significant accomplishment was a response the commercial fenestration industry’s need for a simplification of the present NFRC energy rating method (named site built). To date, most commercial fenestration is self-rated by a variety of techniques. The CMA enables commercial fenestration manufacturers to rate according to the NFRC 100/200 as most commercial energy codes require. International Harmonization NFRC achieved significant international harmonization success by continuing its licensing agreements with the Australian Fenestration Rating Council and the Association of Architectural Aluminum Manufacturers of South Africa (AAAMSA) to produce NFRC certified product ratings in their respective nations. NFRC worked in several other nations to introduce the NFRC ratings system: • India • China • Japan • Canada • Thailand • South Africa • Brazil • Korea NFRC attended or hosted several meetings in each of these nations establishing academic, commercial, industrial, and governmental contacts. NFRC presented the NFRC process and then necessary infrastructure steps necessary to achieve harmonization with the NFRC labeling system. NFRC looks forward to continued work toward harmonization in these nations and potentially others.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

COTS Data Analytics Software User Manual: Version 1.0

Large volumes of data are being collected by Sandia National Laboratories as part of an active commercial-off-the-shelf (COTS) part testing and surveillance program. This user manual documents Python-based COTS Data Analytics software that has been developed for standardizing, displaying, visualizing, and analyzing the resulting COTS part testing and surveillance data. It is the objective of these software tools to streamline the analysis of COTS testing and surveillance data and improve the efficiency with which test engineers and data analytics experts can pinpoint possible performance and reliability problems in COTS parts.

42 ENGINEERING↗
DOE OSTI2022

A Strategy for NACS investment in Machine Learning

The Nuclear and Chemical Sciences (NACS) Division furnishes the expertise in the scientific areas of chemical, nuclear and isotopic sciences that are foundational in the Laboratory’s national security missions. This expertise is maintained and advanced through identification, development and application of state-of-the-art theoretical, computational and experimental methods and tools. Recent developments in artificial intelligence and machine learning (AI/ML) techniques enabled by advances in computing capabilities and widespread availability of powerful software implementations have made use of these techniques ubiquitous across both science and industry. While the scope of AI/ML applications is incredibly large and evolves very rapidly, the topics most relevant to NACS missions fall into the general category of detecting, categorizing or identifying features in large, complex datasets using either supervised or unsupervised learning. This covers both basic scientific data analysis and the development of efficient surrogate models of real-life technological systems, experimental detectors, or theoretical models. To remain at the forefront of its core scientific disciplines, NACS must both cultivate ML expertise as well as continuously explore applying this expertise to new problems or utilizing new methods. This document identifies the key areas where this support is critical and provides a strategy for investing in them.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

Process Modeling and Validation for Metal Big Area Additive Manufacturing

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology based on the metal arc welding. A continuously fed metal wire is melted by an electric arc that forms between the wire and the substrate, and deposited in the form of a bead of molten metal along the predetermined path. Objects are manufactured one layer at a time starting from the base plate. The final properties of the manufactured object are dependent on its geometry and the metal deposition path, in addition to depending on the basic welding process parameters. Computational modeling can be used to accelerate the development of the mBAAM technology as well as a design and optimization tool for the actual manufacturing process. We have developed a finite element method simulation framework for mBAAM using the new features of software ABAQUS. The computational simulation of material deposition with heat transfer is performed first, followed by the structural analysis based on the temperature history for predicting the final deformation and stress state. In this formulation, we assume that two physics phenomena are coupled in only one direction, i.e. the temperatures are driving the deformation and internal stresses, but their feedback on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

Simunovic, Srdjan↗
DOE OSTI2018

Digital Engineering Ecosystem for Innovative Nuclear Technologies

The construction, aerospace, and automotive industries have achieved considerable cost and schedule savings by utilizing virtual design. This program will develop a connected ecosystem of tools to support the design of innovative nuclear technologies. This ecosystem will develop a formal representation of information (data ontology) and systems software to facilitate digital engineering.

42 ENGINEERING↗
DOE OSTI2024

Advancements in Multiphysics Microdepletion Analysis of an eVinci TM -like Microreactor Leveraging OpenMC-CRAB Workflow

Nuclear microreactors (MRs) are a class of nuclear reactor technology, characterized by reduced dimensions, modular design, and reduced power output in contrast to conventional Light Water Reactors (LWRs). MRs are proposed for supplying electricity and eventual process heat to remote locations, such as military installations and disaster-affected areas. Current research work sponsored by the US Department of Energy Microreactor Program (MRP) is devoted to the development of novel modeling and simulation tools to better support MR vendors and regulatory bodies. Notably, the NRC is projected to utilize the CRAB multiphysics software driver for executing both design and beyond-design-basis accident analyses. Furthermore, the NRC has been utilizing the MELCOR code to calculate mechanistic source terms during accidents. Since MELCOR relies on isotopic inventory and reactor temperature/power profiles under accident conditions, which theoretically can be derived from CRAB, the goal is to establish a comprehensive CRAB-MELCOR computational framework. Past work was focused on testing and demonstrating CRAB's capability to generate results that can be used to inform mechanistic source term calculations in MELCOR. In particular, a computational workflow leveraging OpenMC-generated microscopic cross sections and CRAB was first applied to perform multiphysics microscopic depletion calculation followed by an accident scenario for a stylized microreactor problem. In fiscal year 2024, the research work has been focused on applying the OpenMC-CRAB workflow, which was first tested in fiscal year 2023, to a realistic 3D heat-pipe cooled MR problem representative of the eVinci TM design. The latter computational problem was developed with inputs from WEC to conserve selected neutronic and thermal characteristics of the eVinci TM design without releasing proprietary data. The results of this simulation, encompassing isotopic inventory, power density distribution, and kinetic parameters, will inform both MELCOR and the WEC-developed FATE code for mechanistic source terms calculations. The results from the two codes will then be compared for code verification purposes. This report contains the design characteristics of the realist heat pipe cooled microreactor developed as a use-case for the verification exercise, and the current results for the multiphysics microscopic depletion performed with the OpenMC-CRAB workflow. The results include eigenvalue as a function of time, power distribution at EOL, in addition to nuclides inventory's time evolution and spatial distribution. Finally, we report improvements to the workflow efficiency achieved through a collaboration with the NEAMS programs. Through this collaborative effort, we were able to strongly decrease the computational time for the multiphysics microdepletion calculation (i.e., from 17.4 hours to 5.7 hours on 280 processors) in addition to simplifying the interface to generate isotopics spatial distribution utilizable by FATE and MELCOR. Future work, including the improvement of the current microscopic cross-sections' library and the simulation of an accident scenario at EOL, is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Success Path Method: Introduction to the Success Path Method Software Tool©

As part of its commitment to advancing safety and reliability assessment methodologies, Argonne National Laboratory pioneered the use of an evaluation method called the Success Path Method (SPM) to improve risk management for offshore oil and gas operations. The development of the SPM at Argonne has been driven by the need to improve existing risk assessment methodologies by focusing on the steps necessary for success rather than failure modes alone. This is particularly important for industrial environments like offshore facilities that perform multiple functions under a continuously evolving set of operational conditions – such as water depth and temperature, currents, and weather conditions. In these dynamic environments, the traditional Probabilistic Risk Assessment (PRA) approach is far too complex as it focuses on what can go wrong – which comprises an infinite failure space that must be fully explored and understood. By shifting the focus to a finite space of success paths, the SPM enables operators and decision makers to prioritize a manageable number of steps that must go right to ensure success. Building on its five decades of experience in safety assessments for the nuclear industry, Argonne made major adaptations to existing risk assessment methods utilizing features similar to fault trees that are traditionally used in PRA to map all pathways in which the system can malfunction. In contrast, SPM identifies the components and processes that must function correctly to achieve specific outcomes – such as preventing the uncontrolled release of hydrocarbons during drilling operations. The SPM framework integrates equipment, procedures, software, processes, and human actions to ensure that physical barriers meet critical safety functions in dynamic operational conditions. This approach helps identify failure modes and improve operational risk management by narrowing the focus to key success elements, which in turn reduces uncertainty and helps users understand, manage, and respond to failures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Reactivity Feedback Modeling in SAM

System Analysis Module (SAM) is being developed at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report presents the development of Point-Kinetics modeling and reactivity feedback mechanisms in SAM. It also presents a new capability for predicting the thermal expansion in various structural components by coupling SAM with an external thermomechanics module (Tensor Mechanics) from the MOOSE framework. The analysis of the transient behavior of a nuclear reactor requires the coupled simulation of reactor kinetics and thermal-hydraulics of the reactor core, especially for those unprotected transients where the reactor scram system may not function properly. The point kinetics model has been widely used for reactor safety analysis due to its simplicity to capture the transient behavior of the reactor. Various reactivity feedback models have been developed and integrated with the Point-Kinetics module, including fuel axial expansion, core radial expansion, fuel Doppler, and coolant density reactivity. The reactivity feedback models in SAM are similar to the respective models used in SAS4A/SASSYS-1. This report first presents the brief theory of the Point-Kinetics module and reactivity feedback models. A number of verification tests have been performed where the code simulations are compared to the analytical model results. The reactivity feedback due to the thermal deformation, such as the fuel axial expansion and core radial expansion, is important for SFR transient analysis. Simplified thermal expansion models for the fuel pin and reactor constrain system (e.g. grid plate) are developed and verified in SAM. Additionally, a coupling interface is developed to couple SAM with external thermomechanical analysis modules for more accurate predictions of the thermal expansion of different components during the transients. The current coupling interface has been tested with the Tensor Mechanics module from MOOSE. These point kinetics and reactivity feedback modeling capabilities have also been demonstrated by simulating the early stage of the unprotected loss-of-flow (ULOF) accident in the Advanced Burner Test Reactor (ABTR). Both the stand-alone SAM and coupled SAM and Tensor Mechanics simulations are performed. It is confirmed that the major physics phenomena in the heat transport system of the ABTR reactor are captured by SAM, and the point kinetics model, reactivity feedback models, and the coupling schemes are working well as expected.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Multi-Physics Simulations of Heat Pipe Micro Reactor

System Analysis Module (SAM) is under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report presents the development of new capabilities for modeling the heat pipe type reactor systems. The need for power at remote locations away from a reliable electrical grid is an important niche for nuclear energy. Heat pipe-cooled fast-spectrum nuclear reactors are well suited for these applications. The key feature of the heat pipe reactors is the use of heat pipes for heat removal from the reactor core. The heat pipe makes use of the phase change of the working fluid and transports a large amount of heat from the evaporator to the condensation end with very small temperature drops. In contrast to the traditional nuclear reactor system that makes use of pumped loop for extracting the thermal power, the heat pipe reactors make use of hundreds of heat pipes for removing the thermal power (including the decay heat) passively. This could potentially significantly improve the reliability and safety of the reactor systems. The essential part in the analysis of a heat pipe type reactor is the modeling of heat transport inside the heat pipe. The capability of SAM was extended to enable the modeling of the conventional heat pipe. The full suite of non-LWR codes for confirmatory analysis at NRC is known as the Comprehensive Reactor Analysis Bundle (CRAB). It makes use of existing NRC codes, and integrates them with several codes developed through the DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this report, the heat pipe micro reactor is simulated using three submodules under CRAB. The MAMMOTH module is used to simulate the reactor kinetics behavior of the micro reactor; the SAM module is used to simulate the heat conduction in the reactor core and heat removal through the heat pipe heat exchangers and Reactor Cavity Cooling System (RCCS); and the MOOSE Tensor Mechanics module is used to simulate the thermal expansion of the reactor cores. The different sub-models are coupled together using MOOSE’s MultiApp system and executed using the BlueCrab application. The new capability has been demonstrated by a steady-state operation analysis, a failure of a single central heat pipe transient analysis, and a loss of heat sink transient analysis. The fully coupled model is shown to work well.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Reactivity Feedback Modeling in SAM

System Analysis Module (SAM) is being developed at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report presents the development of Point-Kinetics modeling and reactivity feedback mechanisms in SAM. It also presents a new capability for predicting the thermal expansion in various structural components by coupling SAM with an external thermomechanics module (Tensor Mechanics) from the MOOSE framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗