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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

Lo, C. F.↗
NASA NTRS2000

Observations on Rotating Cavitation and Cavitation Surge from the Development of the Fastrac Engine Turbopump

Observations regarding rotating cavitation and cavitation surge experienced during the development of the Fastrac engine turbopump are discussed. Detailed observations acquired from the analysis of both water flow and liquid oxygen test data are offered in this paper. Scaling and general comparison of rotating cavitation between water flow and liquid oxygen testing are discussed. Complex data features linking the localized rotating cavitation mechanism of the inducer to system surge components are described in detail. Finally a description of a lumped-parameter hydraulic system model developed to better understand observed data is given.

Zoladz, Thomas F.↗
NASA NTRS2017

Quantitative Image Analysis Techniques with High-Speed Schlieren Photography

Optical flow visualization techniques such as schlieren and shadowgraph photography are essential to understanding fluid flow when interpreting acquired wind tunnel test data. Output of the standard implementations of these visualization techniques in test facilities are often limited only to qualitative interpretation of the resulting images. Although various quantitative optical techniques have been developed, these techniques often require special equipment or are focused on obtaining very precise and accurate data about the visualized flow. These systems are not practical in small, production wind tunnel test facilities. However, high-speed photography capability has become a common upgrade to many test facilities in order to better capture images of unsteady flow phenomena such as oscillating shocks and flow separation. This paper describes novel techniques utilized by the authors to analyze captured high-speed schlieren and shadowgraph imagery from wind tunnel testing for quantification of observed unsteady flow frequency content. Such techniques have applications in parametric geometry studies and in small facilities where more specialized equipment may not be available.

Pollard, Victoria J.↗
NASA NTRS1993

Enhancements to the Engine Data Interpretation System (EDIS)

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The results of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Hofmann, Martin O.↗
NASA NTRS1993

Enhancements to the Engine Data Interpretation System (EDIS)

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The result of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Hofmann, Martin O.↗
DOE OSTI2020

Evaluating the Potential and Challenges of an Uncertainty Quantification Method for Long Short–Term Memory Models for Soil Moisture Predictions

Recently, recurrent deep networks have shown promise to harness newly available satellite–sensed data for long–term soil moisture projections. However, to be useful in forecasting, deep networks must also provide uncertainty estimates. Here we evaluated Monte Carlo dropout with an input–dependent data noise term (MCD+N), an efficient uncertainty estimation framework originally developed in computer vision, for hydrologic time series predictions. MCD+N simultaneously estimates a heteroscedastic input–dependent data noise term (a trained error model attributable to observational noise) and a network weight uncertainty term (attributable to insufficiently constrained model parameters). Although MCD+N has appealing features, many heuristic approximations were employed during its derivation, and rigorous evaluations and evidence of its asserted capability to detect dissimilarity were lacking. To address this, we provided an in–depth evaluation of the scheme's potential and limitations. We showed that for reproducing soil moisture dynamics recorded by the Soil Moisture Active Passive (SMAP) mission, MCD+N indeed gave a good estimate of predictive error, provided that we tuned a hyperparameter and used a representative training data set. The input–dependent term responded strongly to observational noise, while the model term clearly acted as a detector for physiographic dissimilarity from the training data, behaving as intended. However, when the training and test data were characteristically different, the input–dependent term could be misled, undermining its reliability. Additionally, due to the data–driven nature of the model, data noise also influences network weight uncertainty, and therefore the two uncertainty terms are correlated. Altogether, this approach has promise, but care is needed to interpret the results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Adaptation of fan motor and VFD efficiency correlations using Bayesian inference

Energy performance contracts (EPC) are types of agreements in which a service provider guarantees that customers’ buildings will achieve a specified energy performance (i.e., minimum energy savings) to reduce the risk of their investment in energy efficiency improvements. EPC requires prediction of future energy consumption of the building, at the design stage, before construction or major retrofit. To this end, building energy simulations taking into account all the major energy-using components are performed. In particular, fans can contribute significantly to the total building consumption. The overall efficiency of fans is the combination of three factors: mechanical, motor, and variable frequency drive (VFD). Manufacturers usually provide fan mechanical efficiency curves for a broad operating range. In contrast, motor and VFD efficiencies are generally given at rating conditions only. To represent part-load conditions, correlations are typically used to estimate motor and VFD efficiency variations, to evaluate the overall electricity consumption. The first aim of this study is to evaluate existing correlations for motor and VFD efficiency as a function of load and speed, by comparison with manufacturer data, for a vendor that has shared its detailed test data. While VFD efficiency correlations from the literature provide reasonable accuracy against real data, motor correlations under predict actual motor efficiency at low loads. Finally, the second aim of the paper is to improve such correlations using Bayesian inference to fit the available data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Development of a High-Efficiency Hot Gas Turbo-expander and Low-Cost Heat Exchangers for Optimized CSP Supercritical CO 2 Operation

Southwest Research Institute® (SwRI®) has developed a novel, high-efficiency, supercritical carbon dioxide (sCO 2 ), hot gas turbo-expander optimized for the highly-transient, solar-powerplant, duty-cycle profile. This MW-scale sCO 2 turbo-expander design advances the state-of-theart of sCO 2 turbo-expanders from a current Technology Readiness Level (TRL) of three (initial, small-scale, laboratory, size testing) to a full TRL6 (MW-scale prototype demonstration). A secondary objective of this project was to optimize novel compact heat exchangers for sCO 2 applications to drastically reduce their manufacturing costs. Significant learning was achieved on how to design and fabricate a more cost effective, high performance recuperator, at the MWt capacity. The sCO 2 turbo-expander and novel sCO 2 heat exchanger have been tested in a 1- MWe sCO 2 test loop, fabricated to demonstrate component performance and the performance of the optimized sCO 2 Brayton cycle over a wide range of part load conditions and during transient operations representative of a typical Concentrating Solar Power (CSP) duty cycle. The scalable sCO 2 expander design and improved heat exchanger address and close two critical technology gaps required for an optimized CSP sCO 2 power plant and provide a major stepping stone on the pathway to achieving CSP power at $\$ $0.06/kW-hr Levelized Cost of Electricity (LCOE), increasing energy conversion efficiency to greater than 50% and reducing total power block cost to below $\$ $1,200/kW installed. Construction of the facility and testing has been completed. Test targets of 1,320°F, 27,000 rpm, and 3,500 psi were reached during separate tests. Overall, the turbine saw 37.5 hours of operation with many other hours of testing and troubleshooting all of the loop components. All the test data and troubleshooting is useful and applicable for future tests and operations with not only this loop but in any sCO2 application.

14 SOLAR ENERGY↗
DOE OSTI2020

Markforged Continuous Fiber Composite Material Testing

Continuous fiber composite 3D printing promises to greatly expand the design space of polymer additive manufacturing (AM). A series of mechanical tests were performed to attempt to fully characterize the composite materials built from feedstock provided by the Markforged company. These tests included tensile, compression, Charpy impact, three point bending, coefficient of thermal expansion, and calorimetry tests. Specimens were prepared on the Mark Two 3D printer at LANL during the spring and summer of 2019. These samples were then shipped to New Mexico Institute of Mining and Technology’s Thermo-Mechanical Lab for testing during the summer and fall of 2019. Test data are reported and analyzed for each of the tests.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning applied to classifying neutron resonances

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit resonance structure whose shape is determined in part by the angular momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. In this project, we apply a machine learning technique, namely decision trees, to automate the quantum number assignments. The tree is trained from simulated data generated to mimic the errors found in real data. We explore the use of several physics-motivated features for training our trees, including the nearest neighbor spacing distribution, cumulative level distribution, and channel width distributions. Initial results using random matrix theory motivated fits which demonstrated that we can determine resonance spin groups somewhat reliably. If we use these fits as features in our trees, we can train them to spot outliers corresponding to misassigned resonances. We found that with the large number of features used in this project that the decision tree tended to over t training data resulting in poor performance with respect to the test data. By reducing the number of features, we can achieve nearly perfect assignment of quantum numbers with our training data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1971

Sun compass error model

An error model is described for the Apollo 15 sun compass, a contingency navigational device. Field test data are presented along with significant results of the test. The errors reported include a random error resulting from tilt in leveling the sun compass, a random error because of observer sighting inaccuracies, a bias error because of mean tilt in compass leveling, a bias error in the sun compass itself, and a bias error because the device is leveled to the local terrain slope.

Blucker, T. J.↗
NASA NTRS1974

Government-Industry Data Exchange Program (GIDEP)

The Government-Industry Data Exchange Program (GIDEP) was originated in 1959 by the Army, Navy, and Air Force Ballistic Missile Agencies. Known at that time as IDEP--Interservice Data Exchange Program--its intent was to eliminate duplicate testing of parts and components by disseminating pertinent test data among Department of Defense contractors and various government agencies. In 1966 both the National Aeronautics and Space Administration and the Canadian Military Electronics Standards Agency (CAMESA) recognized the value of the data provided by the program and became participants. Today, GIDEP provides the interchange of specialized technical data to all the military services, participating government contractors and numerous government agencies such as the Atomic Energy Commission, Federal Aviation Administration, Defense Supply Agency, and the Small Business Administration.

Richards, E. T.↗
NASA NTRS1975

Vortex information display system program description manual

A vortex information display system is described which provides flexible control through system-user interaction for collecting wing-tip-trailing vortex data, processing this data in real time, displaying the processed data, storing raw data on magnetic tape, and post processing raw data. The data is received from two asynchronous laser Doppler velocimeters (LDV's) and includes position, velocity, and intensity information. The raw data is written onto magnetic tape for permanent storage and is also processed in real time to locate vortices and plot their positions as a function of time. The interactive capability enables the user to make real time adjustments in processing data and provides a better definition of vortex behavior. Displaying the vortex information in real time produces a feedback capability to the LDV system operator allowing adjustments to be made in the collection of raw data. Both raw data and processing can be continually upgraded during flyby testing to improve vortex behavior studies. The post-analysis capability permits the analyst to perform in-depth studies of test data and to modify vortex behavior models to improve transport predictions.

Conway, R.↗
NASA NTRS1975

Evaluation of a data dictionary system

The usefulness was investigated of a data dictionary/directory system for achieving optimum benefits from existing and planned investments in computer data files in the Data Systems Development Branch and the Institutional Data Systems Division. Potential applications of the data catalogue system are discussed along with an evaluation of the system. Other topics discussed include data description, data structure, programming aids, programming languages, program networks, and test data.

Driggers, W. G.↗