Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “software: data analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Risk Analysis of Various Design Architectures for High Safety-significant Safety-related Digital Instrumentation and Control Systems of Nuclear Power Plants during Accident Scenarios

This report documents the plus-up activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades/designs. An integrated risk assessment technology for the DI&C systems was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the safety margin obtained from plant modernization, especially for the high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing advanced risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems to support system design decisions and diversity and redundancy applications, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals and deal with the expensive licensing justifications from regulatory insights, the LWRS-developed framework instructs nuclear vendors and utilities on how to effectively lower the costs associated with digital compliance and speed industry advances by: (1) defining an integrated risk-informed analysis process for DI&C upgrade, including hazard analysis, reliability analysis, and consequence analysis, (2) applying systematic and risk-informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development, licensing, and deployment of advanced DI&C technologies on nuclear power plant (NPPs). Adding diversity within system or components is the main means to eliminate and mitigate CCFs, but diversity also increases plant complexity and errors and may not address all sources of systematic failures. How to optimize the diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in HSSSR DI&C systems of NPPs and supporting relevant design optimization, the framework provides: ? An integrated best-estimate, risk-informed capability to address new technical digital issues quantitatively, accurately, and efficiently in plan modernization progress, such as software CCFs in HSSSR DI&C systems of NPPs ? A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to efficiently predict and prevent risk in the early design stage of DI&C systems ? Technical bases and risk-informed insights to assist U.S. Nuclear Regulatory Commission (NRC) and industry to address and fulfill the risk-informed alternatives for evaluation of CCFs in HSSSR DI&C systems of NPPs ? An integrated risk-informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The plus-up research and development efforts of this project in FY 2022 are focused on methodology improvement of software CCF modeling and estimation, prevention analysis, importance analysis and risk analysis of various design architectures of HSSSR DI&C systems. This work greatly enhances the capability of the LWRS-developed framework for the risk assessment and design optimization of safety-critical DI&C systems. It should be noted that all the analyses are performed for the demonstration of the LWRS-developed framework, not for the evaluation of relevant systems. Results are obtained based on very limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Elastic Bayesian Model Calibration

Functional data are ubiquitous in scientific modeling. For instance, quantities of interest are modeled as functions of time, space, energy, density, etc. Uncertainty quantification methods for computer models with functional response have resulted in tools for emulation, sensitivity analysis, and calibration that are widely used. However, many of these tools do not perform well when the computer model’s parameters control both the amplitude variation of the functional output and its alignment (or phase variation). This paper introduces a framework for Bayesian model calibration when the model responses are misaligned functional data. The approach generates two types of data out of the misaligned functional responses: (1) aligned functions so that the amplitude variation is isolated and (2) warping functions that isolate the phase variation. These two types of data are created for the computer simulation data (both of which may be emulated) and the experimental data. The calibration approach uses both types so that it seeks to match both the amplitude and phase of the experimental data. The framework is careful to respect constraints that arise, especially when modeling phase variation, and is framed in a way that it can be done with readily available calibration software. In conclusion, we demonstrate the techniques on two simulated data examples and on two dynamic material science problems: a strength model calibration using flyer plate experiments and an equation of state model calibration using experiments performed on the Sandia National Laboratories’ Z-machine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Heating Ventilation Air-Conditioning (HVAC) System Analysis and Optimization for Revit with the OpenStudio Analytical Framework (CRADA Final Report)

This project proposes to integrate the NREL-developed OpenStudio (OS) and its accompanying Analytical Framework (OSAF) into Autodesk’s (ADSK’s) market leading suite of building information modeling (BIM) tools. As a result, BIM users will gain access to advanced (but user-friendly) building energy modeling (BEM), calibration, and design optimization capabilities. Following integration, the BIM software will automatically generate a consistent OS-based BEM model, allowing users to develop projects in an integrated manner, moving back and forth between architectural and engineering perspectives without redundancy or data loss, saving time and effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

ONIX: An open-source depletion code

Open Source software enables innovative, community-based software development. ONIX brings this concept to the field of depletion calculations. It is an open-source depletion software to be used for nuclear reactor simulations, for fissile material production analysis as well as for nuclear arms control applications. ONIX provides a module to solve the depletion equation using a Chebyshev Rational Approximation Method. For the generation of one-group cross sections, it includes a coupling interface for the open-source neutron transport code, OpenMC, as well as a module to read pre-computed values in a stand-alone mode. ONIX has special features to optimize nuclear data libraries, to update isomeric branching ratio during burnup, and to support automation of simulations for nuclear archaeology. In conclusion, ONIX has been validated against results from numerical and experimental benchmarks, and its results agree with other methods within expected error ranges.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

GridOPTICS/GridPACK

GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.

Palmer, Bruce↗
DOE OSTI2023

OpenCSP v.1.0

SAND2024-08987O OpenCSP analyzes and improves the performance of optical mirrors that reflect sunlight and concentrate it onto a receiver. The algorithms in this library analyze the flow of light from an original source—such as the sun—reflecting off one or more mirrors, and onto a receiver, optical screen, or camera. OpenCSP also analyzes optical systems using other techniques, such as shape or slope comparison. The software calculates aggregate properties of the optical system, such as its efficiency, manufacturing error, pointing control error, expected performance, and other useful parameters. OpenCSP also includes high-level tools, such as Open SOFAST, a program that obtains high-resolution measurement of CSP mirrors, full heliostats, and other CSP collectors. OpenCSP supports producing meaningful output data to help CSP designers and field operators improve the performance of their systems. OpenCSP also includes classes and functions that support these calculations, including input utilities, analysis output libraries, geometric constraint analysis for drone flight planning, and more. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Brost, Randolph↗
DOE OSTI2020

ECP ST Capability Assessment Report (CAR) for VTK-m (FY20)

The ECP/VTK-m project is providing the core capabilities to perform scientific visualization on Exascale architectures. The ECP/VTK-m project fills the critical feature gap of performing visualization and analysis on processors like graphics-based processors. The results of this project will be delivered in tools like ParaView, Vislt, and Ascent as well as in stand-alone form. Moreover, these projects are depending on this ECP effort to be able to make effective use of ECP architectures. One of the biggest recent changes in high-performance computing is the increasing use of accelerators. Accelerators contain processing cores that independently are inferior to a core in a typical CPU, but these cores are replicated and grouped such that their aggregate execution provides a very high computation rate at a much lower power. Current and future CPU processors also require much more explicit parallelism. Each successive version of the hardware packs more cores into each processor, and technologies like hyper threading and vector operations require even more parallel processing to leverage each core's full potential. VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures. The ECP/VTK-m project is building up the VTK-m codebase with the necessary visualization algorithm implementations that run across the varied hardware platforms to be leveraged at the Exascale. We will be working with other ECP projects, such as ALPINE, to integrate the new VTK-m code into production software to enable visualization on our HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Attack Surface Analysis of the Digital Twins interface with Advanced Sensor and Instrumentation Interfaces: Cyber Threat Assessment and Attack Demonstration for Digital Twins in Advanced Reactor Architectures

A digital twin is a virtual representation of a physical system or object using real-time data that can predict and analyze how the system or object performs. This relatively new technology can be applied to the field of nuclear power generation, to aid in the design and development of new nuclear power plants and reduce operation costs using predictive maintenance and other data analytical methods. While there are already companies utilizing simulation software to train operators and technicians in the nuclear industry, some are now transitioning to utilizing their existing technology, software, and methods to develop digital twin solutions for the next generation of nuclear power plants, offering their services to utilities and government organizations around the world.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

VTAnDeM: A python toolkit for simultaneously visualizing phase stability, defect energetics, and carrier concentrations of materials

Phase stability, defect formation energies, and carrier concentrations are closely interrelated features of semiconductors. Due to their joint dependence on the multidimensional chemical potential space, it is challenging to quantitatively establish patterns between these quantities in a given semiconductor, especially when the semiconductor is comprised of multiple elements. To enable synchronous visualization and analysis of these complementary material properties and their interdependence, we developed the Visualization Toolkit for Analyzing Defects in Materials (VTAnDeM). This python-based toolkit allows users to interactively explore how defect formation energies and carrier concentrations vary across the composition and chemical potential spaces of multicomponent semiconductors. Here, we illustrate the computational workflow that employs VTAnDeM as a post-processing tool for first-principles calculations and describe the data organization and theory underlying the visualization scheme. Furthermore, we believe that this software will serve as a useful tool for simultaneously visualizing the often complex and non-intuitive chemical potential – defect – carrier concentration phase space of semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sandia Optical Fringe Analysis Slope Tool (SOFAST) Improvement Effort (Final Report)

The Sandia Optical Fringe Analysis Slope Tool (SOFAST) is a tool that has been developed at Sandia to measure the surface slope of concentrating solar power optics. This tool has largely remained of research quality over the past few years. Since SOFAST is important to ongoing tests happening at Sandia as well as an interest to others outside Sandia, there is a desire to bring SOFAST up to professional software standards. The goal of this effort was to make progress in several broad areas including: code quality, sample data collection, and validation and testing. During the course of this effort, much progress was made in these areas. SOFAST is now a much more professional grade tool. There are, however, some areas of improvement that could not be addressed in the timeframe of this work and will be addressed in the continuation of this effort.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Autonomous Flow Electrochemistry for Accelerated Catalyst Discovery

Our objective is to develop an Autonomous Chemical Experimentation (ACE) platform that accelerates discovery of new catalytic transformations and other energy-relevant chemical reactions and processes. We intentionally designed ACE to be highly modular, both with respect to its rapid deployment to different chemistries and experimental workflows as well as incorporation of a wide range of different AI algorithms. In addition to the development of the core software architecture, initial efforts were made to incorporate Large Language Models to provide human-interpretable reasoning of the optimizer’s actions, and to develop a user-friendly graphical interface for experimental researchers. ACE was demonstrated using a flow electrocatalysis platform containing an inline FTIR spectrometer for real-time analysis and quantification of the reaction outcome. Human-in-the-loop experiments were performed in which a human researcher conducted an experiment using electrode potentials suggested by ACE, then fed the spectral data back to ACE for decision making. After confirming the successful function of the optimizer, efforts were next directed to automation of the hardware and performed full autonomy tests using three reactions: catalytic oxidation of formate, catalytic oxidation of cyclohexanol, and oxidation of hydroquinone. These studies confirm that ACE can close the loop between reaction execution, analysis, and optimization. They also reveal that more improved product detection methods will be essential for ACE to make well-informed decisions for reactions with low conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Network Uncertainty Quantification for Analysis of Multi-Component Systems

To impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

42 ENGINEERING↗
DOE OSTI2022

The Terrestrial Biosphere Model Farm

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Translator Plan: A Coordinated Vision for Fiscal Years 2023-2025

Translators serve a unique role in the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility, offering scientific input through various leadership and service roles. The Translators direct the creation of value-added products (VAPs) and analysis tools that make ARM measurements more accessible to the scientific community. Translators also serve as liaisons between users and the ARM infrastructure, collecting information about priorities and communicating ARM data and services. A key group focus is supporting the DOE Atmospheric System Research (ASR) program scientists and ASR’s efforts towards a process-level understanding of cloud-aerosol interactions, and in reducing uncertainty in global climate model projections. The ARM Translator Group (Table 1) consists of the five Translators, a representative of software development, and one from the Data Quality Office (DQO). Additionally, the ARM Engineering and Process Manager participates in this group and provides input and direction from ARM and its programmatic priorities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Retro-Commissioning Sensor Suitcase for Energy Efficiency (CRADA Final Report)

The Sensor Suitcase project aimed to enable cost-effective, data-driven retro-commissioning (RCx) in small commercial buildings through a self-installable toolkit consisting of portable sensors and diagnostic software. Results showed that the Sensor Suitcase could identify common operational faults leading to 5–15% energy savings opportunities, with automated reports requiring minimal user interpretation. The project adhered closely to its Statement of Work (SOW) but evolved the reporting interface and sensor logging duration based on field feedback. The development and validation of diagnostics are documented in PNNL technical reports and internal analysis summaries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

IDAES-PSE Software Tools for Optimizing Energy Systems and Market Interactions

Modern power grids coordinate electricity production and consumption via multi-scale wholesale energy markets. Historically, levelized cost metrics were the de facto standard for techno-eco-nomic analyses of energy systems and comparison of technology options. However, these metrics neglect the complexity of energy infrastructure including the time-varying value of electricity. An emerging alternative is multi-period optimization, which considers the locational marginal price of electricity as input data (parameters). In this work, we present a general interface for multi-period optimization with time-varying energy prices to facilitate rapid analysis and comparison of potential energy systems models. The PriceTakerModel class is written in the IDAES-PSE platform and allows users to generate a multi-period, price-taker model instance, as well as automatically generate common operational constraints for their model, such as start-up and shutdown. We show this interface successfully generates multi-period price-taker models, facilitates model discrimination, and aids in analyzing various technologies for deployment in unique energy markets.

Laky, Daniel↗
DOE OSTI2021

MACCS Theory Manual

This report describes the models of the MACCS computer code as presented in MACCS Version 3.10.0. The purpose of MACCS is to simulate the impact of severe accidents at nuclear power plants on the surrounding environment. MACCS has been developed by Sandia National Laboratories for the U.S. Nuclear Regulatory Commission. From a given release of radioactive material into the atmosphere, MACCS estimates the extent and magnitude of radiological contamination, offsite doses, protective actions, socioeconomic impacts and costs, and health effects. Since the weather at the time of an accident is not predictable, MACCS supports various sampling options to run a representative set of simulations to evaluate weather variability. MACCS simulates atmospheric transport with a straight-line Gaussian plume segment model. From the estimated air and ground concentrations, MACCS models dose projections through several dose exposure pathways. These exposures can be offset by protective actions during the emergency response and long-term recovery of the accident. MACCS users directly specify the evacuation and sheltering area, while other protective actions (e.g., relocation, farmland restrictions, decontamination) are based on user-specified dose or concentration limits. While protective actions help reduce dose accumulation, they also cause social and economic impacts. MACCS models the extent of displaced individuals and land contamination, and the cost of offsite property damage, economic disruptions, and various accident expenditures caused by protective actions. Finally, from the dose accumulation, MACCS estimates early and stochastic health effects according to dose-response models. The purpose of consequence analyses is to be able to understand and estimate the impact of nuclear accidents. Consequence analysis is an essential tool to inform determinations of adequate protection of the public, to understand nuclear power hazards, to measure the value of regulations, and to help us appreciate the importance of nuclear safety. As such, MACCS has a variety of regulatory uses including environmental analyses (10 CFR 51.53, 52.47), regulatory cost-benefit analyses, backfit analyses (10 CFR 50.109), consequence analysis studies such as SOARCA (NUREG-1935), Level 3 PRA studies, and risk-informing of emergency planning (10 CFR 50 App. E and 50.47). This report updates the previous MACCS theory manual (NUREG/CR-4691 Vol. 2; Chanin, Sprung, Ritchie, & Jow, 1990) and accompanies the MACCS User's Guide (SAND-2021-1588) that describes the use and input requirements of the graphical user interface of MACCS known as WinMACCS. The MACCS User's Guide is also a reference guide that describes data input file formats, describes various software components in the MACCS code suite, and provides a set of example tutorials for running WinMACCS. Also, soon to be published is a MACCS input parameter guidance report (NUREG/CR-7270) that provides technical bases for commonly used MACCS input values. This page left blank

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Numerical investigation of the AP1000 response following loss-of-coolant accident using PCTRAN and CFD to support R&D of SMRs

Small Modular Reactors (SMRs) present a promising solution for the future of sustainable energy, offering advantages such as reduced waste generation, advanced passive safety features, and potential cost efficiencies. Ongoing research focuses on the design and development of SMRs, addressing challenges through numerical simulations and experimental test data. Given that many next-generation reactors are first-of-a-kind (FOK), current operational reactors serve as valuable benchmarks for understanding various thermal-hydraulic phenomena during postulated design basis accidents (DBAs), including loss-of-coolant accidents (LOCA), main steam line breaks (MSLB), and steam generator tube ruptures (SGTR). This study employs the AP1000 model Personal Computer Transient Analyzer (PCTRAN) to simulate reactor responses to small-break LOCA scenarios, specifically analyzing break sizes of 2 and 10 inches. Additionally, ANSYS FLUENT software is utilized to assess containment responses to large-break LOCAs, focusing on the quantification of decay heat removal via natural convection. Verification of the PCTRAN results is achieved using Westinghouse data, with CFD results corroborating the findings. The outcomes demonstrate strong agreement with Westinghouse data, confirming the accuracy of the simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗