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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.

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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cybersecurity for Electric Vehicle Fast-Charging Infrastructure

The integration of electric vehicles (EVs) into electric grid operations can potentially leave the grid vulnerable to cyberattacks from both legacy and new equipment and protocols, including extreme fast-charging infrastructure. This paper introduces a co-simulation platform to perform cyber vulnerability analysis of EV charging infrastructure and its dependencies on communications and control systems. Grid impact scenarios through linkages to power system simulation tools such as OpenDSS and vehicle infrastructure-specific attack paths are discussed. An adaptive platform that assists with predicting and solving evolving cybersecurity challenges is demonstrated with a cyber-energy emulation that accelerates the analysis of cyberattacks and system behavior.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Palm: Easing the Burden of Analytical Performance Modeling

Analytical (predictive) application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult because they must be both accurate and concise. To ease the burden of performance modeling, we developed Palm, a modeling tool that combines top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. To express insight, Palm defines a source code modeling annotation language. By coordinating models and source code, Palm's models are `first-class' and reproducible. Unlike prior work, Palm formally links models, functions, and measurements. As a result, Palm (a) uses functions to either abstract or express complexity (b) generates hierarchical models (representing an application's static and dynamic structure); and (c) automatically incorporates measurements to focus attention, represent constant behavior, and validate models. We discuss generating models for three different applications.

annotation languages↗
DOE OSTI2018

IGCAPT

The IGCAPT allows electric utility personnel to perform a static analysis of their communications network supporting smart grid architectures from a network utilization and performance standpoint. IGCAPT is meant to be a "first order" planning tool - the tool will accommodate estimates and best available data alongside default settings, which the user can then improve over time.

Young, JeffreyM.↗
DOE OSTI2020

Software for Transformative Remedial Action Scheme Tool (TRAST)

The transformative remedial action scheme tool (TRAST) can be applied to improve and validate the power system remedial action scheme (RAS), and further improve the performance of power system operation and control. This tool provides a full suite of advanced functionalities, which are given as follows: 1. Advanced statistical data analysis; 2. OPF-based automated power flow case generation; 3. Customized dynamic simulation in HPC/cloud platform; 4. Machine learning based RAS coefficient prediction; 5. A reliable RAS validation strategy in multiple commercial platforms.

Fan, Xiaoyuan↗
DOE OSTI2022

CityBES v2021

City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.

Hong, Tianzhen↗
DOE OSTI2022

clif

SAND2022-12903 O clif contains code to perform climate fingerprinting. It includes capabilities for principal component analysis of climate data, Fourier analysis, a collection of pre-processing scripts, and time series statistical tools. It uses a templated object-oriented programming approach to integrate all classes with the operator in Scikit Learn. 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.

Nichol, Jeffrey↗
DOE OSTI2024

Dispatch Optimization Variable Engine

The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.

McDowell, DylanJ. [Idaho National Laboratory (INL)↗
DOE OSTI2015

Fire Protection Engineering Design Brief Template: Hydrogen Refueling Station

Building a hydrogen infrastructure system is critical to supporting the development of alternate- fuel vehicles. This report provides a methodology for implementing a performance-based design of an outdoor hydrogen refueling station that does not meet specific prescriptive requirements in NFPA 2, The Hydrogen Technologies Code . Performance-based designs are a code-compliant alternative to meeting prescriptive requirements. Compliance is demonstrated by comparing a prescriptive-based fueling station design with a performance-based design approach using Quantitative Risk Assessment (QRA) methods and hydrogen risk assessment tools. This template utilizes the Sandia-developed QRA tool, Hydrogen Risk Analysis Models (HyRAM), which combines reduced-order deterministic models that characterize hydrogen release and flame behavior with probabilistic risk models to quantify risk values. Each project is unique and this template is not intended to account for site-specific characteristics. Instead, example content and a methodology are provided for a representative hydrogen refueling site which can be built upon for new hydrogen applications.

08 HYDROGEN↗
DOE OSTI2019

Final Electrochemical Safeguards Model for the MPACT 2020 Milestone.

The Material Protection, Accounting, and Control Technologies (MPACT) program is working toward a 2020 demonstration of Safeguards and Security by Design for advanced fuel cycle facilities. This milestone ties together modeling and experimental work and will initially demonstrate the concept for electrochemical processing facilities. The safeguards modeling tool used is the Separation and Safeguards Performance Model (SSPM). This report outlines the baseline model design that will be used for the 2020 milestone analysis, which was updated to represent a new baseline flowsheet developed for the MPACT program. The model was also used to generate simulation data for other labs to use as part of their safeguards analysis. Finally, this report describes how the 2020 milestone will be met. ACKNOWLEDGEMENTS This work was funded by the Materials Protection, Accounting, and Control Technologies (MPACT) working group as part of the Nuclear Technology Research and Development Program under the U.S. Department of Energy, Office of Nuclear Energy.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Regulatory Treatment of Low Frequency External Events under a Risk-Informed Performance-Based Licensing Pathway

Significant efforts are underway to develop and implement a risk-informed performance-based licensing framework for advanced reactors built on the establishment of an affirmative safety case. Such approaches offer the benefits of increased flexibility regarding key design and licensing decisions based on a detailed assessment and understanding of plant risk. These methods include the comprehensive analysis of scenarios that have historically been addressed through conservative and deterministic licensing analysis approaches, such as the evaluation of event sequences at frequencies of occurrence beyond the design basis. While the detailed analysis of low frequency events provides insights that can help justify alternative treatments to past conservatism, the findings are dependent on the quality and confidence associated with the analyses. The assessment of external hazards presents a unique challenge, as their potential frequency of occurrence, especially of large magnitude events, is inherently uncertain given the long return periods in question. The current project seeks to further explore the regulatory treatment of low frequency external events as part of a risk-informed performance-based framework. The goals are to identify the benefits and challenges of such approaches for advanced reactor vendors and to aid in the development of consistent and appropriate methodologies. As part of this effort, the current report summarizes initial project findings, with a focus on the evaluation of the seismic hazard. This includes an exploration of the implementation of a risk-informed performance-based approach through an example analysis. Based on the identified challenges associated with the probabilistic treatment of low frequency event sequences, additional performance-based methods were explored as complementary tools for demonstrating regulatory compliance. The report highlights key challenges and opportunities associated with the methods and outlines recommendations and future activities to assist with their implementation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Sparse Data Machine Learning Integration with Theory, Experiment and Uncertainty Quantification: Process-Structure-Property-Performance of Friction Deformation Processing

Computer vision and deep learning tools that advance the ability to establish processing-structure-property-performance (PSPP) relations are presented. The Bayesian binning method for image segmentation enables quantitative analysis of microstructural features in an automated way, while the analysis of shapes and relative orientation of these features reveals local deformation maps indicative of both, material flow and residual stresses due to materials processing. The deep learning method leads to the previous knowledge agnostic mapping of empirically observed microstructural zones in friction stir welding (FSW) process and synthetic microstructure generation capability that is statistically equivalent to experimentally collected data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

sympl (v. 0.4.0) and climt (v. 0.15.3) – towards a flexible framework for building model hierarchies in Python

sympl (System for Modelling Planets) andclimt (Climate Modelling and Diagnostics Toolkit) are anattempt to rethink climate modelling frameworks from the ground up. The aimis to use expressive data structures available in the scientific Pythonecosystem along with best practices in software design to allow scientists toeasily and reliably combine model components to represent the climate systemat a desired level of complexity and to enable users to fully understandwhat the model is doing. sympl is a framework which formulates the model in terms of astate that gets evolved forward in time or modified within a specifictime by well-defined components. sympl's design facilitates buildingmodels that are self-documenting, are highly interoperable, and providefine-grained control over model components and behaviour. symplcomponents contain all relevant information about the input they expect andoutput that they provide. Components are designed to be easily interchanged,even when they rely on different units or array configurations.sympl provides basic functions and objects which could be used inany type of Earth system model. climt is an Earth system modelling toolkit that contains scientificcomponents built using sympl base objects. These include both purePython components and wrapped Fortran libraries. climt providesfunctionality requiring model-specific assumptions, such as stateinitialization and grid configuration. climt's programming interfacedesigned to be easy to use and thus appealing to a wide audience. Model building, configuration and execution are performed through a Pythonscript (or Jupyter Notebook), enabling researchers to build an end-to-endPython-based pipeline along with popular Python data analysis andvisualization tools.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Heave-pitch-roll analysis and testing of air cushion landing systems

The analytical tools (analysis and computer simulation) needed to explain and predict the dynamic operation of air cushion landing systems (ACLS) is described. The following tasks were performed: the development of improved analytical models for the fan and the trunk; formulation of a heave pitch roll analysis for the complete ACLS; development of a general purpose computer simulation to evaluate landing and taxi performance of an ACLS equipped aircraft; and the verification and refinement of the analysis by comparison with test data obtained through lab testing of a prototype cushion. Demonstration of simulation capabilities through typical landing and taxi simulation of an ACLS aircraft are given. Initial results show that fan dynamics have a major effect on system performance. Comparison with lab test data (zero forward speed) indicates that the analysis can predict most of the key static and dynamic parameters (pressure, deflection, acceleration, etc.) within a margin of a 10 to 25 percent.

Boghani, A. B.↗
NASA NTRS1985

The Communications link analysis and simulation system (CLASS)

The Communications Link Analysis and Simulation System (CLASS) is a comprehensive, computerized communications and tracking system analysis tool under development by the Networks Directorate of the NASA/GSFC. The primary use of this system is to provide the capability to predict the performance of the Tracking and Data Relay Satellite system (TDRSS) User Communications and Tracking links through the TDRSS. The general capabilities and operational philosophy of the current and final versions of the CLASS are described along with some examples of analyses which have been performed utilizing the capabilities of this system.

Godfrey, R. D.↗
NASA NTRS1987

Development of a computational aero/fluids analysis system

The Computational Aero/Fluids Analysis System (AFAS) provides the analytical capability to perform state-of-the-art computational analyses in two difficult fluid dynamics disciplines associated with the Space Shuttle program. This system provides the analysis tools and techniques for rapidly and efficiently accessing, analyzing, and reformulating the large and expanding external aerodynamic data base while also providing tools for complex fluid flow analyses of the SSME engine components. Both of these fluid flow disciplines, external aerodynamics and internal gasdynamics, required this capability to ensure that MSFC can respond in a timely manner as problems are encountered and operational changes are made in the Space Shuttle.

Kelley, P. B.↗
NASA NTRS1987

Methods for evaluating integrated airframe/propulsion control system architectures

Methodology, analysis, and detailed design of integrated control system architectures suitable for high-performance aircraft of the 1990s are presented. A methodology, with supporting analytical tools, has been developed to provide system designers with the capability to specify candidate architectures and accurately predict their reliability and performance in the early stages of design development. The authors address the methodology and supporting tools.

Gerald C Cohen↗
NASA NTRS1989

Experiences with a prevalidation methodology for designing integrated/propulsion control system architectures

The work described in this paper is supported under NASA contract NAS1-18099, Analysis and Detailed Design of an Integrated Airfame/Propulsion Control System Architecture (IAPSA II). This contract address methodology, analysis and detailed design of integrated control system architectures suitable for high performance aircraft of the 1990's. We have developed methodology, with supporting analytical tools, to provide system designers with the capability to specify candidate architectures and accurately predict their reliability and performance in the early stages of design development. This paper describes experience gained using the prevalidation methodology, including supporting tools.

Propulsion control system↗
NASA NTRS1997

Aerodynamic Shape Sensitivity Analysis and Design Optimization of Complex Configurations Using Unstructured Grids

A three-dimensional unstructured grid approach to aerodynamic shape sensitivity analysis and design optimization has been developed and is extended to model geometrically complex configurations. The advantage of unstructured grids (when compared with a structured-grid approach) is their inherent ability to discretize irregularly shaped domains with greater efficiency and less effort. Hence, this approach is ideally suited for geometrically complex configurations of practical interest. In this work the nonlinear Euler equations are solved using an upwind, cell-centered, finite-volume scheme. The discrete, linearized systems which result from this scheme are solved iteratively by a preconditioned conjugate-gradient-like algorithm known as GMRES for the two-dimensional geometry and a Gauss-Seidel algorithm for the three-dimensional; similar procedures are used to solve the accompanying linear aerodynamic sensitivity equations in incremental iterative form. As shown, this particular form of the sensitivity equation makes large-scale gradient-based aerodynamic optimization possible by taking advantage of memory efficient methods to construct exact Jacobian matrix-vector products. Simple parameterization techniques are utilized for demonstrative purposes. Once the surface has been deformed, the unstructured grid is adapted by considering the mesh as a system of interconnected springs. Grid sensitivities are obtained by differentiating the surface parameterization and the grid adaptation algorithms with ADIFOR (which is an advanced automatic-differentiation software tool). To demonstrate the ability of this procedure to analyze and design complex configurations of practical interest, the sensitivity analysis and shape optimization has been performed for a two-dimensional high-lift multielement airfoil and for a three-dimensional Boeing 747-200 aircraft.

Taylor, Arthur C., III↗