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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Overview of NASA Multi-dimensional Stirling Convertor Code Development and Validation Effort

A NASA grant has been awarded to Cleveland State University (CSU) to develop a multi-dimensional (multi-D) Stirling computer code with the goals of improving loss predictions and identifying component areas for improvements. The University of Minnesota (UMN) and Gedeon Associates are teamed with CSU. Development of test rigs at UMN and CSU and validation of the code against test data are part of the effort. The one-dimensional (1-D) Stirling codes used for design and performance prediction do not rigorously model regions of the working space where abrupt changes in flow area occur (such as manifolds and other transitions between components). Certain hardware experiences have demonstrated large performance gains by varying manifolds and heat exchanger designs to improve flow distributions in the heat exchangers. 1-D codes were not able to predict these performance gains. An accurate multi-D code should improve understanding of the effects of area changes along the main flow axis, sensitivity of performance to slight changes in internal geometry, and, in general, the understanding of various internal thermodynamic losses. The commercial CFD-ACE code has been chosen for development of the multi-D code. This 2-D/3-D code has highly developed pre- and post-processors, and moving boundary capability. Preliminary attempts at validation of CFD-ACE models of MIT gas spring and "two space" test rigs were encouraging. Also, CSU's simulations of the UMN oscillating-flow fig compare well with flow visualization results from UMN. A complementary Department of Energy (DOE) Regenerator Research effort is aiding in development of regenerator matrix models that will be used in the multi-D Stirling code. This paper reports on the progress and challenges of this

Tew, Roy C.↗
DOE OSTI2023

Multimodal representation learning for predicting molecule–disease relations

Motivation: Predicting molecule–disease indications and side effects is important for drug development and pharmacovigilance. Comprehensively mining molecule–molecule, molecule–disease and disease–disease semantic dependencies can potentially improve prediction performance. Methods: We introduce a Multi-Modal REpresentation Mapping Approach to Predicting molecular-disease relations (M2REMAP) by incorporating clinical semantics learned from electronic health records (EHR) of 12.6 million patients. Specifically, M2REMAP first learns a multimodal molecule representation that synthesizes chemical property and clinical semantic information by mapping molecule chemicals via a deep neural network onto the clinical semantic embedding space shared by drugs, diseases and other common clinical concepts. To infer molecule–disease relations, M2REMAP combines multimodal molecule representation and disease semantic embedding to jointly infer indications and side effects. Results: We extensively evaluate M2REMAP on molecule indications, side effects and interactions. Results show that incorporating EHR embeddings improves performance significantly, for example, attaining an improvement over the baseline models by 23.6% in PRC-AUC on indications and 23.9% on side effects. Further, M2REMAP overcomes the limitation of existing methods and effectively predicts drugs for novel diseases and emerging pathogens. Availability and implementation: The code is available at https://github.com/celehs/M2REMAP, and prediction results are provided at https://shiny.parse-health.org/drugs-diseases-dev/.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1974

Prediction of pump cavitation performance

A method for predicting pump cavitation performance with various liquids, liquid temperatures, and rotative speeds is presented. Use of the method requires that two sets of test data be available for the pump of interest. Good agreement between predicted and experimental results of cavitation performance was obtained for several pumps operated in liquids which exhibit a wide range of properties. Two cavitation parameters which qualitatively evaluate pump cavitation performance are also presented.

Moore, R. D.↗
DOE OSTI2025

DECOVALEX-2023: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX initiative is an international research collaboration (www.decovalex.org), initiated in 1992, for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of the complex perturbations and coupled processes in geologic repositories and how these impact long-term performance predictions. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2023, started in early 2020 and ended in late 2023. More than fifty research teams associated with 17 international DECOVALEX partner organizations participated in the comparative evaluation of eight modeling tasks covering a wide range of spatial and temporal scales, geological formations, and coupled processes. This Virtual Special Issue on DECOVALEX-2023 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes. While primarily focused on radioactive waste, much of the work included here has wider application to many geoengineering topics.

Coupled processes↗
DOE OSTI2020

Characterization and verification of a two-body wave energy converter with a novel power take-off

The lack of high efficient, predictable and reliable power take-off (PTO) systems limits developments of ocean wave energy technology. In this paper, a two-body self-reacting wave energy converter (WEC) with a novel PTO is designed, modelled and implemented for efficiency enhancement. A novel mechanical motion rectifier (MMR) using a ball screw mechanism and an enclosed gear set is integrated to improve the energy harvesting efficiency and reliability by rectifying the oscillatory wave motion into unidirectional rotation of the generator. Detailed design and dynamic modelling for the proposed WEC are presented. A prototype of the PTO is tested in a dry lab to characterize and refine the dynamic modelling. The characterized PTO model is combined with the WEC model to create an overall system model. A water tank test is conducted to verify the overall system dynamics, which proves the accuracy of the model and shows the advantages of the proposed WEC on efficiency and predictability. Following the method of how the WEC system is characterized, performance prediction of the proposed WEC with MMR PTO can be achieved with high accuracy.

16 TIDAL AND WAVE POWER↗
NASA NTRS1990

Calculation of hypersonic forebody/inlet flow fields

The National Aero-Space Plane (NASP) is unique in its integration of the airframe and propulsion system. The performance of the NASP propulsion system (scramjet) is dependent upon the quality of the flow into the scramjet inlet. Hence, the calculation of the inlet flow field must be coupled to the forebody flow field for accurate performance predictions. The Compressible Navier-Stokes code has been extended to perform both external and internal hypersonic flow fields. Computations are presented that validate these changes and demonstrate the capability to perform coupled forebody/inlet computations for hypersonic flows.

Bennett, Bradford C.↗
NASA NTRS1997

IPAC-Inlet Performance Analysis Code

A series of analyses have been developed which permit the calculation of the performance of common inlet designs. The methods presented are useful for determining the inlet weight flows, total pressure recovery, and aerodynamic drag coefficients for given inlet geometric designs. Limited geometric input data is required to use this inlet performance prediction methodology. The analyses presented here may also be used to perform inlet preliminary design studies. The calculated inlet performance parameters may be used in subsequent engine cycle analyses or installed engine performance calculations for existing uninstalled engine data.

Barnhart, Paul J.↗
NASA NTRS2016

Global Positioning System Navigation Above 76,000 km for NASA's Magnetospheric Multiscale Mission

NASA's Magnetospheric Multiscale (MMS) mission, launched in March of 2015, consists of a controlled formation of four spin-stabilized spacecraft in similar highly elliptic orbits reaching apogee at radial distances of 12 and 25 Earth radii (RE) in the first and second phases of the mission. Navigation for MMS is achieved independently on-board each spacecraft by processing Global Positioning System (GPS) observables using NASA Goddard Space Flight Center (GSFC)'s Navigator GPS receiver and the Goddard Enhanced Onboard Navigation System (GEONS) extended Kalman filter software. To our knowledge, MMS constitutes, by far, the highest-altitude operational use of GPS to date and represents a high point of over a decade of high-altitude GPS navigation research and development at GSFC. In this paper we will briefly describe past and ongoing high-altitude GPS research efforts at NASA GSFC and elsewhere, provide details on the design of the MMS GPS navigation system, and present on-orbit performance data from the first phase. We extrapolate these results to predict performance in the second phase orbit, and conclude with a discussion of the implications of the MMS results for future high-altitude GPS navigation, which we believe to be broad and far-reaching.

GPS↗
NASA NTRS2017

Global Positioning System Navigation Above 76,000 km for NASA's Magnetospheric Multiscale Mission

NASA's Magnetospheric Multiscale (MMS) mission, launched in March of 2015, consists of a controlled formation of four spin-stabilized spacecraft in similar highly elliptic orbits reaching apogee at radial distances of 12 and 25 Earth radii (RE) in the first and second phases of the mission. Navigation for MMSis achieved independently on-board each spacecraft by processing Global Positioning System (GPS) observables using NASA Goddard Space Flight Center (GSFC)'s Navigator GPS receiver and the Goddard Enhanced Onboard Navigation System (GEONS) extended Kalman filter software. To our knowledge, MMS constitutes, by far, the highest-altitude operational use of GPS to date and represents a high point of over a decade of high-altitude GPS navigation research and development at GSFC. In this paper we will briefly describe past and ongoing high-altitude GPS research efforts at NASA GSFC and elsewhere, provide details on the design of the MMS GPS navigation system, and present on-orbit performance data from the first phase. We extrapolate these results to predict performance in the second phase orbit, and conclude with a discussion of the implications of the MMS results for future high-altitude GPS navigation, which we believe to be broad and far-reaching.

navigation↗
DOE OSTI2023

Predicting future well performance for environmental remediation design using deep learning

Here in this study, we developed a deep learning (DL) framework with a multi-channel three-dimensional convolutional neural network (MC3D-CNN) to predict well performance and thereby assist future environmental remediation design. Such prediction of extraction well performance at designated locations is critical for configuring pump-and-treat (P&T) well network design and operation, setting reasonable target closure dates for overall remedying, and estimating remedy costs. The framework is developed with operational and monitoring data routinely collected during P&T remedy operations, including well extraction and injection rates as well as in situ contaminant concentrations. Traditionally, the collected data were rarely used for purposes other than assessing past well performance and the accuracy of the conceptual site model. However, recent advances in data-driven computational approaches enable better use of the large datasets to inform future well performance, enhance site characterization, and improve remediation planning. In this study, we established a DL framework to integrate transient three-dimensional contaminant plumes and multiple aquifer properties (e.g., hydraulic conductivity and hydrostratigraphic maps) to identify characteristic patterns controlling and representing extraction well mass recovery, aiming at providing future mass recovery estimates for existing wells and candidate wells at any proposed locations. We evaluated our framework by using a realistic synthetic dataset generated from a well-calibrated flow and transport model used in the 200 West Area of the U.S. Department of Energy’s Hanford Site in southeastern Washington state. The multi-channel feature in our framework allows integration of various types and temporal densities of training datasets for DL model development. Overall, we found that the trained DL model achieved an accuracy of over 90% in ranking extraction well performance in validation datasets, and over 80% in predicting high-performance-ranking well locations. This data-informed approach provides a flexible tool to support adaptive site management, streamline decision-making, and potentially reduce remediation time and costs. Our DL framework can be used as a filtering tool to improve the current P&T network optimization design by reducing the number of candidate well locations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Analytic Guided-Search Model of Human Performance Accuracy in Target- Localization Search Tasks

Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.

Eckstein, Miguel P.↗
NASA NTRS1998

Flight Stability and Control and Performance Results from the Linear Aerospike SR-71 Experiment (LASRE)

The Linear Aerospike SR-71 Experiment (LASRE) is presently being conducted to test a 20-percent-scale version of the Linear Aerospike rocket engine. This rocket engine has been chosen to power the X-33 Single Stage to Orbit Technology Demonstrator Vehicle. The rocket engine was integrated into a lifting body configuration and mounted to the upper surface of an SR-71 aircraft. This paper presents stability and control results and performance results from the envelope expansion flight tests of the LASRE configuration up to Mach 1.8 and compares the results with wind tunnel predictions. Longitudinal stability and elevator control effectiveness were well-predicted from wind tunnel tests. Zero-lift pitching moment was mispredicted transonically. Directional stability, dihedral stability, and rudder effectiveness were overpredicted. The SR-71 handling qualities were never significantly impacted as a result of the missed predictions. Performance results confirmed the large amount of wind-tunnel-predicted transonic drag for the LASRE configuration. This drag increase made the performance of the vehicle so poor that acceleration through transonic Mach numbers could not be achieved on a hot day without depleting the available fuel.

Moes, Timothy R.↗
DOE OSTI2020

Cybersecurity impact of the growth of data in sports

As the sporting industry continues to increase dependence on new and often massive data sets, they also risk exposing themselves, as well as the leagues, teams, venues, players, and fans, to risks posed by not protecting the confidentiality and integrity of this data. The industry, especially true for professional sports, demands an ever increasing supply of new forms of data to achieve their goals of enticing new fans; enhancing experience; expanding the fan experience from venues and television to the internet and mobile devices; measuring and evaluating the performance and safety of players; and increasing revenue. New methods have emerged to collect data about a variety of aspects of sports ranging from players to fans to teams to venues. Data collected during sporting events is combined with historical data to also help teams analyze and predict performance. To synthesize these predictive analytical and historical memories, sports teams and organizations mix a variety of computer technologies. System integration tends to focus on ensuring the availability of the data and reliability of the technologies but might introduce risks to the confidentiality (privacy) and integrity of the data. Recognizing the potential risks requires review and evaluation. Much of the data is collected for publicly providing information to the fans, so threats to confidentiality pose fewer risks. The greatest risk is violating the privacy of players, such a private performance test, or using technology to gain a competitive advantage.

Jenkins, Stephanie↗
DOE OSTI2022

Photovoltaic System Health-State Architecture for Data-Driven Failure Detection

The timely detection of photovoltaic (PV) system failures is important for maintaining optimal performance and lifetime reliability. A main challenge remains the lack of a unified health-state architecture for the uninterrupted monitoring and predictive performance of PV systems. To this end, existing failure detection models are strongly dependent on the availability and quality of site-specific historic data. The scope of this work is to address these fundamental challenges by presenting a health-state architecture for advanced PV system monitoring. The proposed architecture comprises of a machine learning model for PV performance modeling and accurate failure diagnosis. The predictive model is optimally trained on low amounts of on-site data using minimal features and coupled to functional routines for data quality verification, whereas the classifier is trained under an enhanced supervised learning regime. The results demonstrated high accuracies for the implemented predictive model, exhibiting normalized root mean square errors lower than 3.40% even when trained with low data shares. The classification results provided evidence that fault conditions can be detected with a sensitivity of 83.91% for synthetic power-loss events (power reduction of 5%) and of 97.99% for field-emulated failures in the test-bench PV system. Finally, this work provides insights on how to construct an accurate PV system with predictive and classification models for the timely detection of faults and uninterrupted monitoring of PV systems, regardless of historic data availability and quality. Such guidelines and insights on the development of accurate health-state architectures for PV plants can have positive implications in operation and maintenance and monitoring strategies, thus improving the system’s performance.

photovoltaics↗
NASA NTRS1981

Verification of the Space Shuttle entry GN&C system

The certification procedures for the initial Shuttle flight are discussed. Particular attention is paid to the entry guidance, navigation, and control (GNC) verification, comprising tests, analysis, demonstration, inspection, and simulation. Flow diagrams for the verification and operational flight sequences are provided, along with a block diagram of the GNC circuitry interfaces. The development of the test matrix software for the GNC is outlined, noting the constant interplay between software verification and spacecraft reconfiguration to meet simulated performance requirements. Comparison of GNC performance predictions with actual entry flight data showed a good match in all performance areas except for sideslip excursions, bank overshoots, an area of transonic buffet, and an increased lift/drag ratio in the preflare to landing flight phase.

Van Hoften, J. D. A.↗
NASA NTRS1992

Electrochemical Impedance Of Inorganic-Zinc-Coated Steel

Report describes preliminary experiments to evaluate both direct-current and alternating-current electrochemical impedance measurements as candidate techniques for use in accelerated corrosion testing of mild-steel panels coated with inorganic zinc-rich primers and exposed to seaside air. Basic idea behind experiments to compare electrochemical impedance measurements with anticorrosion performances of coating materials to determine whether measurements can be used to predict performances. Part of continuing program to identify anticorrosion coating materials protecting steel panels adequately for as long as 5 years and beyond.

Macdowell, Louis G.↗
NASA NTRS1952

Performance and Operational Characteristics of a Python Turbine-propeller Engine at Simulated Altitude Conditions / Carl L. Meyer and Lavern A. Johnson

The performance and operational characteristics of a Python turbine propeller engine have been investigated over a range of engine operating conditions at simulated altitudes from 5000 to 40,000 feet in the NACA Lewis altitude wind tunnel . For the performance phase of the investigation, a single cowl-inlet ram pressure ratio was maintained and independent control of engine speed and fuel flow was used to obtain a range of power at each engine speed. Engine performance data obtained at a given altitude could not be used to predict performance accurately at other altitudes by use of the standard air pressure and temperature generalizing factors. Specific fuel consumption based on shaft horsepower decreased as the shaft horsepower increased at a given engine speed. At a given altitude condition and turbine -inlet total temperature, there was an optimum engine speed at which maximum shaft horsepower was obtained. At a given engine speed and turbine-inlet total temperature, a greater portion of the total available energy was converted to propulsive power as the altitude increased. Windmilling starts were made at altitudes up to 40,000 feet; the minimum true airspeed required for successful windmilling starts increased as the altitude was raised. In general, the engine control prevented large overshoots or undershoots of engine speed during starts, accelerations, and decelerations.

Engines - Armstrong-Siddely Python Turbo-Propeller↗
NASA NTRS2000

Analysis of the DFP/AFCS Systems for Compensating Gravity Distortions on the 70-Meter Antenna

This paper presents the theoretical computations showing the expected performances for both systems. The basic analysis tool is a Physical Optics reflector analysis code that was ported to a parallel computer for faster execution times. There are several steps involved in computing the RF performance of the various systems. 1 . A model of the RF distortions of the main reflector is required. This model is based upon measured holography maps of the 70-meter antenna obtained at 3 elevation angles. The holography maps are then processed (using an appropriate gravity mechanical model of the dish) to provide surface distortion maps at all elevation angles. 2. From the surface distortion maps, ray optics is used to determine the theoretical shape of the DFP that will exactly phase compensate the distortions. 3. From the theoretical shape and a NASTRAN mechanical model of the plate, the actuator positions that generate a surface that provides the best RMS fit to the theoretical model are selected. Using the actuator positions and the NASTRAN model provides an accurate description of the actual mirror shape. 4. Starting from the mechanical drawings of the feed, a computed RF feed pattern is generated. This pattern is expanded into a set of spherical wave modes so that a complete near field analysis of the reflector system can be obtained. 5. For the array feed, the excitation coefficients that provide the maximum gain are computed using a phase conjugate technique. The basic experimental geometry consisted of a dual shaped 70-meter antenna system; a refocusing ellipse, a DFP and an array feed system. To provide physical insight to the systems performance, focal plane field plots are presented at several elevations. Curves of predicted performance are shown for the DFP system, monopulse tracking system, AFCS and combined DFP/AFCS system. The calculated results show that the combined DFP/AFCS system is capable of recovering the majority of the gain lost due to gravity distortion.

Imbriale, William A.↗