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Results for “Modeling and Performance 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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

The 2006 Kennedy Space Center Range Reference Atmosphere Model Validation Study and Sensitivity Analysis to the Performance of the National Aeronautics and Space Administration's Space Shuttle Vehicle

The Kennedy Space Center (KSC) Range Reference Atmosphere (RRA) is a statistical model that summarizes wind and thermodynamic atmospheric variability from surface to 70 km. The National Aeronautics and Space Administration's (NASA) Space Shuttle program, which launches from KSC, utilizes the KSC RRA data to evaluate environmental constraints on various aspects of the vehicle during ascent. An update to the KSC RRA was recently completed. As part of the update, the Natural Environments Branch at NASA's Marshall Space Flight Center (MSFC) conducted a validation study and a comparison analysis to the existing KSC RRA database version 1983. Assessments to the Space Shuttle vehicle ascent profile characteristics were performed by JSC/Ascent Flight Design Division to determine impacts of the updated model to the vehicle performance. Details on the model updates and the vehicle sensitivity analyses with the update model are presented.

Burns, Lee↗
NASA NTRS1994

Evaluation of SSME test data reduction methods

Accurate prediction of hardware and flow characteristics within the Space Shuttle Main Engine (SSME) during transient and main-stage operation requires a significant integration of ground test data, flight experience, and computational models. The process of integrating SSME test measurements with physical model predictions is commonly referred to as data reduction. Uncertainties within both test measurements and simplified models of the SSME flow environment compound the data integration problem. The first objective of this effort was to establish an acceptability criterion for data reduction solutions. The second objective of this effort was to investigate the data reduction potential of the ROCETS (Rocket Engine Transient Simulation) simulation platform. A simplified ROCETS model of the SSME was obtained from the MSFC Performance Analysis Branch . This model was examined and tested for physical consistency. Two modules were constructed and added to the ROCETS library to independently check the mass and energy balances of selected engine subsystems including the low pressure fuel turbopump, the high pressure fuel turbopump, the low pressure oxidizer turbopump, the high pressure oxidizer turbopump, the fuel preburner, the oxidizer preburner, the main combustion chamber coolant circuit, and the nozzle coolant circuit. A sensitivity study was then conducted to determine the individual influences of forty-two hardware characteristics on fourteen high pressure region prediction variables as returned by the SSME ROCETS model.

Santi, L. Michael↗
DOE OSTI2018

DiTTo (Distribution Transformation Tool) [SWR-18-16]

The Distribution Transformation Tool (DiTTo) provides a framework for converting between and modifying several different types of distribution model formats . These include commercial formats such as CYME, Synergi, DEW, ePHASORSIM as well as open source formats such as OpenDSS and GridLAB-D. DiTTo consists of an API which represents electrical equipment, configurations, settings and timeseries data. This API acts as an intermediary between different distribution model formats. Several modules for reading and writing the models connect to this API to facilitate easy conversion between formats. Once feeder models are converted into the intermediate API, analysis can be done on the feeder using a network module. The modification module allows changes to be made to the model in the intermediate API. This allows a clear workflow that supports reading a model from one format, performing analysis, making modifications and writing the model to a different format.

Elgindy, Tarek↗
DOE OSTI2022

Data and scripts associated with the manuscript "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning"

This package contains the data and scripts used in "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning" (Jiang et al., 2022). The data.zip file contains the flux tower and automated chamber observations used for developing the deep learning model for modeling soil respiration. The scripts.zip file contains the Jupyter notebooks and python scripts for preprocessing the data, training the deep learning models, and postprocessing the results. The src.zip contains the source code for training the deep learning model, performing mutual information analysis, and plotting functions. The trained_models.zip contains multiple folders used for hosting the trained deep-learning models and the associated soil respiration predictions. The whole process is performed using python. We include the REAMD.md to document the python package requirements.Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of accurately representing these complex interactions than traditional Q10-based models. Mutual information analysis revealed that future soil temperature shares more information with soil respiration than past soil temperature, consistent with their clockwise diel hysteresis. We explicitly encoded diel hysteresis, soil drying, and soil rewetting effects on soil respiration dynamics in a newly designed Long Short Term Memory (LSTM) model. The model takes both past and future environmental drivers as inputs to predict soil respiration. The new LSTM model substantially outperformed three Q10-based models and the Community Land Model when reproducing the observed soil respiration dynamics in a semi-arid ecosystem. The new LSTM model clearly demonstrated its superiority for temporally extrapolating soil respiration dynamics, such that the resulting correlation with observational data is up to 0.7 while the correlations of both Q10-based models and the Community Land Model (CLM) are less than 0.4. Our results underscore the high potential for knowledge-guided deep learning to replace Q10-based soil respiration modules in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Abstract Tool condition monitoring (TCM) has become a research area of interest due to its potential to significantly reduce manufacturing costs while increasing process visibility and efficiency. Machine learning (ML) is one analysis technique which has demonstrated advantages for TCM applications. However, the commonly studied individual ML models lack generalizability to new machining and environmental conditions, as well as robustness to the unbalanced datasets which are common in TCM. Ensemble ML models have demonstrated superior performance in other fields, but have only begun to be evaluated for TCM. As a result, it is not well understood how their TCM performance compares to that of individual models, or how homogeneous and heterogeneous ensemble models’ performances compare to one another. To fill in these research gaps, milling experiments were conducted using various cutting conditions, and the model groups were compared across several performance metrics. Statistical t-tests were also used to evaluate the significance of model performance differences. Through the analysis of four individual ML models and five ensemble models, all based on the processes’ sound, spindle power, and axial load signals, it was found that on average, the ensemble models performed better than the individual models, and that the homogeneous ensembles outperformed the heterogeneous ensembles.

Engineering↗
DOE OSTI2022

Simulation and Postmortem Analysis of Angeles Forest Disturbance Event

Multiple unexpected solar photovoltaic (PV) plant responses in the California region following contingencies in recent years warrant postmortem analysis leveraging digital fault recorder (DFR) data for a better understanding of such events and preventing similar events in the future. Most utilities in US, in general, possess transient stability (TS) phasor-domain models of the power grid. Since traditional phasor-based transient stability planning models cannot perform such analysis, this paper presents an approach to extract a region of such models and convert it to Electromagnetic transient (EMT) models. The approach is based on the determination of the minimum impedance-weighted spanning tree between the fault location and affected PV plants in a Western Electricity Coordinating Council (WECC) planning model followed by conversion of this region into an EMT model. The accuracy of the proposed approach is validated against DFR records obtained from the 2018 Angeles Forest disturbance event.

Samanta, Sayan↗
NASA NTRS1996

Performance Analysis and Optimization on the UCLA Parallel Atmospheric General Circulation Model Code

An analysis is presented of several factors influencing the performance of a parallel implementation of the UCLA atmospheric general circulation model (AGCM) on massively parallel computer systems. Several modificaitons to the original parallel AGCM code aimed at improving its numerical efficiency, interprocessor communication cost, load-balance and issues affecting single-node code performance are discussed.

atmospheric study optimization strategies parallel↗
NASA NTRS2023

Analysis of Cryogenic Propellant Liquefaction Rates in Cooled Constant-Wall-TemperatureTanks

NASA has been focused on developing technology that would allow the production of cryogenic propellants on the Lunar and Martian surfaces. Utilizing Lunar/Martian resources, the produced gaseous propellants must first be liquefied and stored prior to use on the Moon or Mars ascent vehicle. Liquefaction of cryogenic propellant is a necessary technical development to enable NASA’s future spaceflight goals. This paper presents an overview of the effect of spacecraft propellant system parameters on cryogenic propellant liquefaction rates. The propellant system was assumed to be a receiver of a gas from an In-Situ Resource Utilization (ISRU) harvester and condensed the gas by cooling the tank walls. First, the general thermodynamic principles pertinent to condensation are summarized, followed by an overview of the model which performed the analysis, including a summary of the Fortran implementation. Comparisons between the model results and test data are discussed, as well as sensitivity of the condensation rate to various parameters.

cryogenics↗
NASA NTRSDate not supplied

Analysis of Cryogenic Propellant Liquefaction Rates in Cooled Constant-Wall-Temperature Tanks

NASA has been focused on developing technology that would allow the production of cryogenic propellants on the Lunar and Martian surfaces. Utilizing Lunar/Martian resources, the produced gaseous propellants must first be liquefied and stored prior to use on the Moon or Mars ascent vehicle. Liquefaction of cryogenic propellant is a necessary technical development to enable NASA’s future spaceflight goals. This paper presents an overview of the effect of spacecraft propellant system parameters on cryogenic propellant liquefaction rates. The propellant system was assumed to be a receiver of a gas from an In-Situ Resource Utilization (ISRU) harvester and condensed the gas by cooling the tank walls. First, the general thermodynamic principles pertinent to condensation are summarized, followed by an overview of the model which performed the analysis, including a summary of the Fortran implementation. Comparisons between the model results and test data are discussed, as well as sensitivity of the condensation rate to various parameters.

Anson Koch↗
NASA NTRSDate not supplied

Analysis of Cryogenic Propellant Liquefaction Rates in Cooled Constant-Wall-Temperature Tanks

NASA has been focused on developing technology that would allow the production of cryogenic propellants on the Lunar and Martian surfaces. Utilizing Lunar/Martian resources, the produced gaseous propellants must first be liquefied and stored prior to use on the Moon or Mars ascent vehicle. Liquefaction of cryogenic propellant is a necessary technical development to enable NASA’s future spaceflight goals. This paper presents an overview of the effect of spacecraft propellant system parameters on cryogenic propellant liquefaction rates. The propellant system was assumed to be a receiver of a gas from an In-Situ Resource Utilization (ISRU) harvester and condensed the gas by cooling the tank walls. First, the general thermodynamic principles pertinent to condensation are summarized, followed by an overview of the model which performed the analysis, including a summary of the Fortran implementation. Comparisons between the model results and test data are discussed, as well as sensitivity of the condensation rate to various parameters.

cryogenics↗
NASA NTRS1983

Communications network design and costing model users manual

The information and procedures needed to exercise the communications network design and costing model for performing network analysis are presented. Specific procedures are included for executing the model on the NASA Lewis Research Center IBM 3033 computer. The concepts, functions, and data bases relating to the model are described. Model parameters and their format specifications for running the model are detailed.

Logan, K. P.↗
DOE OSTI2024

Fabrication, Modeling, and Testing of a Prototype Thermal Energy Storage Containment

Increasing penetration of variable renewable energy resources requires the deployment of energy storage at a range of durations. Long-duration energy storage (LDES) technologies will fulfill the need to firm variable renewable energy resource output year round; lithium-ion batteries are uneconomical at these durations. Thermal energy storage (TES) is one promising technology for LDES applications because of its siting flexibility and ease of scaling. Particle-based TES systems use low-cost solid particles that have higher temperature limits than the molten salts used in traditional concentrated solar power systems. A key component in particle-based TES systems is the containment silo for the high-temperature (>1100 degrees C) particles. This study combined experimental testing and computational modeling methods to design and characterize the performance of a particle containment silo for LDES applications. A laboratory-scale silo prototype was built and validated the congruent transient finite element analysis (FEA) model. The performance of a commercial-scale silo was then characterized using the validated model. The commercial-scale model predicted a storage efficiency above 95% after 5 days of storage with a design storage temperature of 1200 degrees C. Insulation material and concrete temperature limits were considered as well. The validation of the methodology means the FEA model can simulate a range of scenarios for future applications. This work supports the development of a promising LDES technology with implications for grid-scale electrical energy storage, but also for thermal energy storage for industrial process heating applications.

clean energy↗