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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ProFAST (Production Financial Analysis Scenario Tool) [SWR-23-88]

The Production Financial Analysis Scenario Tool (ProFAST) provides a quick and convenient in-depth financial analysis for production facilities. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. ProFAST allows users to calculate the levelized cost of the produced commodity by providing an expected financial performance, or on the other hand, calculate the financial performance based on an input price. Model inputs generally capital expenditures, operating expenditures, and financing structure. The programmatic approach of ProFAST allows users to easily perform large sensitivity analyses and integrates easily with other python tools.

Kee, Jamie↗
DOE OSTI2019

H2FAST: Hydrogen Financial Analysis Scenario Tool [SWR 15-06]

The Hydrogen Financial Analysis Scenario Tool, H2FAST, provides a quick and convenient in-depth financial analysis for hydrogen and nonhydrogen systems and services. H2FAST is available as a downloadable Excel spreadsheet. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. H2FAST allows users to generate a side-by-side scenario analysis, where a base system can be tested by varying key operating or financing parameters. Detailed capital structure, taxation, and incentives are included. The model has built-in risk analysis allowing impact assessment of parameters bearing user-specified uncertainty ranges. Financial articulation is presented in graphical and tabular format for the user-specified analysis period. The model is self-documented, with embedded help functions and annotation of input parameters. Note: The model is also flexible for providing analysis for International Financial Reporting Standards by adjusting inputs for compliance with their rules. The H2FAST framework has been used for analysis of a variety of systems, e.g., retail hydrogen refueling stations with incentives analysis, ammonia production, methane pyrolysis, seasonal energy storage, hydrogen fleet operations, electric vehicle charging with time of use rate structures, combined heat and power systems, hydrogen production pathways, and hydrogen transmission and distribution. The example cases available for download are intended to demonstrate model functionality and should be populated with user-specific analysis values such as CapEx, OpEx, and capital structure.

Penev, Michael↗
NASA NTRS2019

Uncertainty Analysis of the CE-22 Advanced Nozzle Test Facility

This paper presents methods and results of a detailed measurement uncertainty analysis that was performed for the Advanced Nozzle Test Facility, CE-22, located at the NASA Glenn Research Center. Results for the uncertainty in thrust and flow coefficients, in addition to other variables of interest, are provided. Results are presented separately as random uncertainty (characterizing errors inherent to instrument or measurement environment, impacting repeatability), systematic uncertainty (capturing inaccuracies due to measurement process, calibration, installation effects or other sources which may introduce bias), and total combined uncertainty. The statistical methods and engineering judgments used to estimate elemental uncertainties are described. The analysis tool MANTUS (Measurement Analysis Tool for Uncertainty in Systems) was used to quantify instrumentation system uncertainty, and statistical analysis and engineering judgment were used to quantify other random and systematic uncertainty sources. The Monte Carlo method was used to propagate systematic and random elemental uncertainties to determine the uncertainties of various calculated variables of interest.

data quality↗
NASA NTRS2001

Methodology Development for Assessment of Spaceport Technology Returns and Risks

As part of Kennedy Space Center's (KSC's) challenge to open the space frontier, new spaceport technologies must be developed, matured and successfully transitioned to operational systems. R&D investment decisions can be considered from multiple perspectives. Near mid and far term technology horizons must be understood. Because a multitude of technology investment opportunities are available, we must identify choices that promise the greatest likelihood of significant lifecycle At the same time, the costs and risks of any choice must be well understood and balanced against its potential returns The problem is not one of simply rank- ordering projects in terms of their desirability. KSC wants to determine a portfolio of projects that simultaneously satisfies multiple goals, such as getting the biggest bang for the buck, supporting projects that may be too risky for private funding, staying within annual budget cycles without foregoing the requirements of a long term technology vision, and ensuring the development of a diversity of technologies that, support the variety of operational functions involved in space transportation. This work aims to assist in the development of in methods and techniques that support strategic technology investment decisions and ease the process of determining an optimal portfolio of spaceport R&D investments. Available literature on risks and returns to R&D is reviewed and most useful pieces are brought to the attention of the Spaceport Technology Development Office (STDO). KSC's current project management procedures are reviewed. It is found that the "one size fits all" nature of KSC's existing procedures and project selection criteria is not conducive to prudent decision-making. Directions for improving KSC's - procedures and criteria are outlined. With help of a contractor, STDO is currently developing a tool, named Change Management Analysis Tool (CMAT)/ Portfolio Analysis Tool (PAT), to assist KSC's R&D portfolio determination. A critical review of CMAT/PAT is undertaken. Directions for the improvement of this tool are provided. STDO and KSC intend to follow up on many, if not all, of the recommendations provided.

Joglekar, Prafulla↗
NASA NTRS2010

FSSC Science Tools: Pulsar Analysis

This slide presentation reviews the typical pulsar analysis, giving tips for screening of the data, the use of time series analysis, and utility tools. Specific information about analyzing Vela data is reviewed.

Thompson, Dave↗
NASA NTRSDate not supplied

Features for a Modern Strain-Gage Balance Data Analysis Software Tool

Required, recommended, and optional features are discussed that benefit preparation and evaluation of the load prediction equations in a strain-gage balance data analysis tool. First, milestones in the evolution of load prediction methods are reviewed so that suggested features can be put into a historical context. Afterwards, independent and dependent variable choices for the balance data analysis are discussed. Then, it is illustrated how three different metrics may be used for the identification of the root cause of an unwanted divergence of the load iterations that may be observed during an iterative load prediction. Finally, a list of features is provided to guide software development efforts.

wind tunnel test↗
DOE OSTI2022

The EGS Collab Project – Stimulations at Two Depths

The EGS Collab project, supported by the US Department of Energy, is performing intensively monitored rock stimulation and flow tests at the 10-m scale in an underground research laboratory to address challenges in implementing enhanced geothermal systems (EGS). Data and observations from the field tests are compared to simulations to understand processes and build confidence in numerical modeling of the processes. We have completed Experiment 1 (of 3), which examined hydraulic fracturing in a well-characterized underground fractured phyllite test bed at a depth of approximately 1.5 km at the Sanford Underground Research Facility (SURF) in Lead, South Dakota. Testbed characterization included fracture mapping, borehole acoustic and optical televiewers, full waveform sonic, conductivity, resistivity, temperature, campaign p- and s-wave investigations and electrical resistance tomography. Borehole geophysical techniques including passive seismic, continuous active source seismic monitoring, electrical resistance tomography, fiber-based distributed strain, distributed temperature, and distributed acoustic monitoring, were used to carefully monitor stimulation events and flow tests. More than a dozen stimulations and nearly one year of flow tests were performed. Quality data and detailed observations were collected and analyzed during stimulation and water flow tests using ambient temperature and chilled water. We achieved adaptive control of the tests using real-time monitoring and rapid dissemination of data and near-real-time simulation. More detailed numerical simulation was performed to answer key experimental design questions, forecast fracture propagation trajectories and extents, and analyze and evaluate results. Data are freely available from the Geothermal Data Repository. Experiment 2 examines the potential for hydraulic shearing in amphibolite at a depth of about 1.25 km at SURF. This site has a different set of stress and fracture conditions than Experiment 1. The Experiment 2 testbed consists of nine subhorizontal boreholes configured in two fans of two boreholes which surround the testbed and contain grouted-in electrical resistance tomography, seismic sensors, active seismic sources and distributed fiber sensors. A “five-spot” set of test wells that extends from a custom mined alcove includes an injection well and four production/monitoring wells. The testbed was characterized geophysically and hydrologically, and three stimulations have been performed using the Step-Rate Injection Method for Fracture In-Situ Properties (SIMFIP) tool to measure strains, and a new strain quantifying tool (downhole robotic strain analysis tool -DORSA) was deployed in a monitoring hole during stimulation. Real-time data were broadcast during stimulations to allow real-time response to arising issues.

EGS Collab, Enhanced Geothermal Systems, EGS, fiel↗
NASA NTRS2011

Software Users Manual (SUM): Extended Testability Analysis (ETA) Tool

This software user manual describes the implementation and use the Extended Testability Analysis (ETA) Tool. The ETA Tool is a software program that augments the analysis and reporting capabilities of a commercial-off-the-shelf (COTS) testability analysis software package called the Testability Engineering And Maintenance System (TEAMS) Designer. An initial diagnostic assessment is performed by the TEAMS Designer software using a qualitative, directed-graph model of the system being analyzed. The ETA Tool utilizes system design information captured within the diagnostic model and testability analysis output from the TEAMS Designer software to create a series of six reports for various system engineering needs. The ETA Tool allows the user to perform additional studies on the testability analysis results by determining the detection sensitivity to the loss of certain sensors or tests. The ETA Tool was developed to support design and development of the NASA Ares I Crew Launch Vehicle. The diagnostic analysis provided by the ETA Tool was proven to be valuable system engineering output that provided consistency in the verification of system engineering requirements. This software user manual provides a description of each output report generated by the ETA Tool. The manual also describes the example diagnostic model and supporting documentation - also provided with the ETA Tool software release package - that were used to generate the reports presented in the manual

Maul, William A.↗
DOE OSTI2020

Risk-Informed ATF and FLEX Analysis for an Enhanced Resilient BWR Under Design-Basis and Beyond-Design-Basis Accidents

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2020 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors’ safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. One main focus of the FY 2020 efforts documented in this report was to extend the analyses conducted in FYs 2018 and 2019 for a pressurized water reactor (PWR) to a boiling water reactor (BWR). The same analysis process, risk analysis approaches, and analysis tools as in the previous work for PWR were used for a generic BWR with near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the postulated station blackout (SBO) and medium loss-of-coolant (MLOCA) accident scenarios. In addition, a FLEX model was developed and incorporated into a generic BWR probabilistic risk assessment (PRA) model using the INL-developed software tool, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), to assess the risk impact from FLEX. The other main focus of the FY 2020 efforts was to advance analysis methods, including developing dynamic approach for FLEX human reliability analysis (HRA) using the INL-developed software tool, Event Modeling Risk Assessment using Linked Diagrams (EMRALD), as well as developing a multicriterion benefit evaluation (MCBE) method for evaluating costs and benefits of safety enhancements in nuclear power plants (NPPs). As a case study, the MCBE method was applied to evaluate the costs and benefits brought by FLEX implementation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Process design tools and techno-economic analysis for capacitive deionization

Capacitive deionization (CDI) devices use cyclical electrosorption on porous electrode surfaces to achieve water desalination. Process modeling and design of CDI systems requires accurate treatment of the coupling among input electrical forcing, input flow rates, and system responses including salt removal dynamics, water recovery, energy storage, and dissipation. Techno-economic analyses of CDI further require a method to calculate and compare between a produced commodity (e.g. desalted water) versus capital and operational costs of the system. In this work, we demonstrate a new modeling and analysis tool for CDI developed as an installable Matlab program that allows direct numerical simulation of CDI dynamics and calculation of key performance and cost parameters. The program is provided for free and is used to run open-source Simulink models. The Simulink environment sends information to the program and allows for a drag and drop design space where users can connect CDI cells to relevant periphery blocks such as grid energy, battery, solar panel, waste disposal, and maintenance/labor cost streams. The program allows for simulation of arbitrary current forcing and arbitrary flow rate forcing of one or more CDI cells. We employ validated well-mixed reactor formulations together with a non-linear circuit model formulation that can accommodate a variety of electric double layer sub-models (e.g. for charge efficiency). The program includes a graphical user interface (GUI) to specify CDI plant parameters, specify operating conditions, run individual tests or parameter batch-mode simulations, and plot relevant results. The techno-economic models convert among dimensional streams of species (e.g. feed, desalted water, and brine), energy, and cost and enable a variety of economic estimates including levelized water costs.

42 ENGINEERING↗
NASA NTRS2011

Ares I-X Flight Test Validation of Control Design Tools in the Frequency-Domain

A major motivation of the Ares I-X flight test program was to Design for Data, in order to maximize the usefulness of the data recorded in support of Ares I modeling and validation of design and analysis tools. The Design for Data effort was intended to enable good post-flight characterizations of the flight control system, the vehicle structural dynamics, and also the aerodynamic characteristics of the vehicle. To extract the necessary data from the system during flight, a set of small predetermined Programmed Test Inputs (PTIs) was injected directly into the TVC signal. These PTIs were designed to excite the necessary vehicle dynamics while exhibiting a minimal impact on loads. The method is similar to common approaches in aircraft flight test programs, but with unique launch vehicle challenges due to rapidly changing states, short duration of flight, a tight flight envelope, and an inability to repeat any test. This paper documents the validation effort of the stability analysis tools to the flight data which was performed by comparing the post-flight calculated frequency response of the vehicle to the frequency response calculated by the stability analysis tools used to design and analyze the preflight models during the control design effort. The comparison between flight day frequency response and stability tool analysis for flight of the simulated vehicle shows good agreement and provides a high level of confidence in the stability analysis tools for use in any future program. This is true for both a nominal model as well as for dispersed analysis, which shows that the flight day frequency response is enveloped by the vehicle s preflight uncertainty models.

Johnson, Matthew↗
NASA NTRS1983

Integrated verification and testing system (IVTS) for HAL/S programs

The IVTS is a large software system designed to support user-controlled verification analysis and testing activities for programs written in the HAL/S language. The system is composed of a user interface and user command language, analysis tools and an organized data base of host system files. The analysis tools are of four major types: (1) static analysis, (2) symbolic execution, (3) dynamic analysis (testing), and (4) documentation enhancement. The IVTS requires a split HAL/S compiler, divided at the natural separation point between the parser/lexical analyzer phase and the target machine code generator phase. The IVTS uses the internal program form (HALMAT) between these two phases as primary input for the analysis tools. The dynamic analysis component requires some way to 'execute' the object HAL/S program. The execution medium may be an interpretive simulation or an actual host or target machine.

Senn, E. H.↗
DOE OSTI2020

Extracting dependencies between network assets using deep learning

A network analysis tool receives network flow information and uses deep learning—machine learning that models high-level abstractions in the network flow information—to identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.

Carroll, Thomas E.↗
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 OSTI2020

Complementary workflows for identifying one-hop network behavior and multi-hop network dependencies

A network analysis tool evaluates network flow information in complementary workflows to identify one-hop behavior of network assets and also identify multi-hop dependencies between network assets. In one workflow (e.g., using association rule learning), the network analysis tool can identify significant one-hop communication patterns to and/or from network assets, taken individually. Based on the identified one-hop behavior, the network analysis tool can discover patterns of similar communication among different network assets, which can inform decisions about deploying patch sets, mitigating damage, configuring a system, or detecting anomalous behavior. In a different workflow (e.g., using deep learning or cross-correlation analysis), the network analysis tool can identify significant multi-hop communication patterns that involve network assets in combination. Based on the identified multi-hop dependencies, the network analysis tool can discover functional relationships between network assets, which can inform decisions about configuring a system, managing critical network assets, or protecting critical network assets.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Use of Transition Modeling to Enable the Computation of Losses for Variable-Speed Power Turbine

To investigate the penalties associated with using a variable speed power turbine (VSPT) in a rotorcraft capable of vertical takeoff and landing, various analysis tools are required. Such analysis tools must be able to model the flow accurately within the operating envelope of VSPT. For power turbines low Reynolds numbers and a wide range of the incidence angles, positive and negative, due to the variation in the shaft speed at relatively fixed corrected flows, characterize this envelope. The flow in the turbine passage is expected to be transitional and separated at high incidence. The turbulence model of Walters and Leylek was implemented in the NASA Glenn-HT code to enable a more accurate analysis of such flows. Two-dimensional heat transfer predictions of flat plate flow and two-dimensional and three-dimensional heat transfer predictions on a turbine blade were performed and reported herein. Heat transfer computations were performed because it is a good marker for transition. The final goal is to be able to compute the aerodynamic losses. Armed with the new transition model, total pressure losses for three-dimensional flow of an Energy Efficient Engine (E3) tip section cascade for a range of incidence angles were computed in anticipation of the experimental data. The results obtained form a loss bucket for the chosen blade.

Ameri, Ali A.↗
DOE OSTI2024

Search for pair-produced vectorlike quarks coupling to light quarks in the lepton plus jets final state using 13 TeV p p collisions with the ATLAS detector

A search is presented for the pair production of heavy vectorlike quarks (VLQs) that each decay into a W boson and a light quark. This study focuses on events where one W boson decays into leptons and the other into hadrons. The search analyzed 140 fb -1 of pp collision data with $\sqrt{s}$ = 13 TeV, recorded by the ATLAS detector from 2015 to 2018 during run 2 of the Large Hadron Collider. The final state is characterized by a high-transverse-momentum isolated electron or muon, large missing transverse momentum, multiple small-radius jets, and a single large-radius jet identified as originating from the hadronic decay of a boosted W boson. With higher center-of-mass energy and integrated luminosity than in the run 1 search, and improved analysis tools, this analysis excludes VLQs (Q) with masses below 1530 GeV at 95% confidence level for the branching ratio $\mathscr{B}$⁡(Q →W⁢q) =1, an improvement of 840 GeV on the previous ATLAS limit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1989

Integrated tools for control-system analysis

The basic functions embedded within a user friendly software package (MATRIXx) are used to provide a high level systems approach to the analysis of linear control systems. Various control system analysis configurations are assembled automatically to minimize the amount of work by the user. Interactive decision making is incorporated via menu options and at selected points, such as in the plotting section, by inputting data. There are five evaluations such as the singular value robustness test, singular value loop transfer frequency response, Bode frequency response, steady-state covariance analysis, and closed-loop eigenvalues. Another section describes time response simulations. A time response for random white noise disturbance is available. The configurations and key equations used for each type of analysis, the restrictions that apply, the type of data required, and an example problem are described. One approach for integrating the design and analysis tools is also presented.

Ostroff, Aaron J.↗