SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Dynamic pressure measurements and power spectra obtained from hot test firing of the Space Shuttle Main Engine are reported for test stand A3.
The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts spectral information from the engine plume and reports the amounts of metals which are present in the plume. The development of this software is at a sufficiently advanced stage where it can be used in actual engine tests to provide valuable data on engine operation and health. This activity will continue and, in addition, the OPAD system is planned to be used in flight aboard space vehicles. The two implementations, test-stand and in-flight, may have some differing requirements. For example, the data stored during a test-stand experiment are much more extensive than in the in-flight case. In both cases though, the majority of the requirements are similar. New data from the spectrograph is generated at a rate of once every 0.5 sec or faster. All processing must be completed within this period of time to maintain real-time performance. Every 0.5 sec, the OPAD system must report the amounts of specific metals within the engine plume, given the spectral data. At present, the software in the OPAD system performs this function by solving the inverse problem. It uses powerful physics-based computational models (the SPECTRA code), which receive amounts of metals as inputs to produce the spectral data that would have been observed, had the same metal amounts been present in the engine plume. During the experiment, for every spectrum that is observed, an initial approximation is performed using neural networks to establish an initial metal composition which approximates as accurately as possible the real one. Then, using optimization techniques, the SPECTRA code is repetitively used to produce a fit to the data, by adjusting the metal input amounts until the produced spectrum matches the observed one to within a given level of tolerance. This iterative solution to the original problem of determining the metal composition in the plume requires a relatively long period of time to execute the software in a modern single-processor workstation, and therefore real-time operation is currently not possible. A different number of iterations may be required to perform spectral data fitting per spectral sample. Yet, the OPAD system must be designed to maintain real-time performance in all cases. Although faster single-processor workstations are available for execution of the fitting and SPECTRA software, this option is unattractive due to the excessive cost associated with very fast workstations and also due to the fact that such hardware is not easily expandable to accommodate future versions of the software which may require more processing power. Initial research has already demonstrated that the OPAD software can take advantage of a parallel computer architecture to achieve the necessary speedup. Current work has improved the software by converting it into a form which is easily parallelizable. Timing experiments have been performed to establish the computational complexity and execution speed of major components of the software. This work provides the foundation of future work which will create a fully parallel version of the software executing in a shared-memory multiprocessor system.
Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.
The accumulation of JPL data on Single Event Phenomena (SEP), from 1979 to August 1986, is presented in full report format. It is expected that every two years a supplement report will be issued for the follow-on period. This data for 135 devices expands on the abbreviated test data presented as part of Refs. (1) and (3) by including figures of Single Event Upset (SEU) cross sections as a function of beam Linear Energy Transfer (LET) when available. It also includes some of the data complied in the JPL computer in RADATA and the SPACERAD data bank. This volume encompasses bipolar and MOS (CMOS and MHNOS) device data as two broad categories for both upsets (bit-flips) and latchup. It also includes comments on less well known phenomena, such as transient upsets and permanent damage modes.
The model generation and structural analysis performed for the High Pressure Oxidizer Turbopump (HPOTP) preburner pump volute housing located on the main pump end of the HPOTP in the space shuttle main engine are summarized. An ANSYS finite element model of the volute housing was built and executed. A static structural analysis was performed on the Engineering Analysis and Data System (EADS) Cray-XMP supercomputer
A carbureted four cylinder air cooled 0-320 DIAD Lycoming aircraft engine was tested to establish the effects of air temperature and humidity at various fuel-air ratios on the exhaust emissions on a per-mode basis. The test conditions included carburetor lean-out at air temperatures of 50, 59, 80, and 100 F at relative humidities of 0, 30, 60, and 80 percent. Temperature-humidity effects at the higher values of air temperature and relative humidity tested indicated that the HC and CO emissions increased significantly, while the NOx emissions decreased. Even at a fixed fuel-air ratio, the HC emissions increase and the NOx emissions decrease at the higher values of air temperature and humidity. Volume II contains the data taken at each of the individual test points.
An assessment of engine and component health is routinely made after each test or flight firing of a space shuttle main engine (SSME). Currently, this health assessment is done by teams of engineers who manually review sensor data, performance data, and engine and component operating histories. Based on review of information from these various sources, an evaluation is made as to the health of each component of the SSME and the preparedness of the engine for another test or flight. The objective of this project is to further develop a computer program which automates the analysis of test data from the SSME high-pressure oxidizer turbopump (HPOTP) in order to detect and diagnose anomalies. This program fits into a larger system, the SSME Post-Test Diagnostic System (PTDS), which will eventually be extended to assess the health and status of most SSME components on the basis of test data analysis. The HPOTP module is an expert system, which uses 'rules-of-thumb' obtained from interviews with experts from NASA Marshall Space Flight Center (MSFC) to detect and diagnose anomalies. Analyses of the raw test data are first performed using pattern recognition techniques which result in features such as spikes, shifts, peaks, and drifts being detected and written to a database. The HPOTP module then looks for combination of these features which are indicative of known anomalies, using the rules gathered from the turbomachinery experts. Results of this analysis are then displayed via a graphical user interface which provides ranked lists of anomalies and observations by engine component, along with supporting data plots for each.
The program consists of parametric analysis and design to provide a consistent engine system data base for defining advantages and disadvantages, system performance and operating limits, engine parametric data, and technology requirements for candidate high pressure LO2/Hydrocarbon engine systems. The parametric chamber and nozzle cooling analysis was completed for the four potential coolants: RP-1, LCH4, LO2, and LH2. A summary of the cooling capability of each propellant is presented.
Data from the P78-2 spacecraft are being used in verifying and validating analytical tools being developed for the design of spacecraft, such as NASCAP, for updating Military Standard 1541, for investigation of materials contamination, and for a study of the physics of charging. The analysis of this data has already resulted in changes in laboratory testing procedures, in a better understanding of some properties of materials exposed to the space environment, and in some insight into the EMI caused by discharges on spacecraft in a plasma environment. Some examples of early results from the engineering experiments are presented.
The ability to articulate, collect, and automate the application of the expertise needed for the analysis of space shuttle main engine (SSME) test data would be of great benefit to NASA liquid rocket engine experts. This paper describes a project whose goal is to build a rule-based expert system which incorporates such expertise. Experiential expertise, collected directly from the experts currently involved in SSME data analysis, is used to build a rule base to identify engine anomalies similar to those analyzed previously. Additionally, an alternate method of expertise capture is being explored. This method would generate rules inductively based on calculations made using a theoretical model of the SSME's operation. The latter rules would be capable of diagnosing anomalies which may not have appeared before, but whose effects can be predicted by the theoretical model.
Engineering details are presented of a small free-drifting buoy configuration designed for use in the study of continental shelf water circulation patterns in the Chesapeake Bight of the Western North Atlantic Ocean. The buoy incoporated French instrumentation and was interrogated by the French EOLE satellite to provide position and four channels of temperature data. The buoy design included a variable depth drogue and a power supply sufficient for six weeks of continuous operations. Proof tests of the configuration indicated an adequate design and subsequent field experiments verified the proper functioning of the system.
An assessment of engine and component health is routinely made after each test firing or flight firing of a Space Shuttle Main Engine (SSME). Currently, this health assessment is done by teams of engineers who manually review sensor data, performance data, and engine and component operating histories. Based on review of information from these various sources, an evaluation is made as to the health of each component of the SSME and the preparedness of the engine for another test or flight. The objective of this project - the SSME Post Test Diagnostic System (PTDS) - is to develop a computer program which automates the analysis of test data from the SSME in order to detect and diagnose anomalies. This report primarily covers work on the Systems Section of the PTDS, which automates the analyses performed by the systems/performance group at the Propulsion Branch of NASA Marshall Space Flight Center (MSFC). This group is responsible for assessing the overall health and performance of the engine, and detecting and diagnosing anomalies which involve multiple components (other groups are responsible for analyzing the behavior of specific components). The PTDS utilizes several advanced software technologies to perform its analyses. Raw test data is analyzed using signal processing routines which detect features in the data, such as spikes, shifts, peaks, and drifts. Component analyses are performed by expert systems, which use 'rules-of-thumb' obtained from interviews with the MSFC data analysts to detect and diagnose anomalies. The systems analysis is performed using case-based reasoning. Results of all analyses are stored in a relational database and displayed via an X-window-based graphical user interface which provides ranked lists of anomalies and observations by engine component, along with supporting data plots for each.
The performance of the 11-stage axial-flow compressor, modified to improve the compressor-outlet velocity, in a revised X24C-4B turbojet engine is presented and compared with the performance of the compressor in the original engine. Performance data were obtained from an investigation of the revised engine in the MACA Cleveland altitude wind tunnel. Compressor performance data were obtained for engine operation with four exhaust nozzles of different outlet area at simulated altitudes from 15,OOO to 45,000 feet, simulated flight Mach numbers from 0.24 to 1.07, and engine speeds from 4000 to 12,500 rpm. The data cover a range of corrected engine speeds from 4100 to 13,500 rpm, which correspond to compressor Mach numbers from 0.30 to 1.00.
A consistent engine system data base was generated for defining advantages and disadvantages, system performance and operating limits, engine parametric data, and technology requirements for candidate high pressure LO2/HC engine systems. Optimum LO2/HC engine power cycles were synthetized and representative conceptual engine design generated for a specified advanced surface to orbit transportation system.
Computer simulations of the direct-injection stratified-charge (DISC) Wankel engine have been used to calculate heat release rates and performance and efficiency characteristics of the 1007R engine. Engine pressure data have been used in a heat release analysis to study the effects of heat transfer, leakage, and crevice flows. Predicted engine performance data are compared with experimental test data over a range of engine speeds and loads. An examination of methods to improve the performance of the Wankel engine with faster combustion, reduced leakage, higher compression ratio, and turbocharging is presented.
Transformative science often occurs at the boundaries of different disciplines. Making interdisciplinary science data, software and documentation discoverable and accessible is essential to enabling transformative science. However, connecting this diverse and heterogeneous information is often a challenge due to several factors including the dispersed and sometimes isolated nature of data and the semantic differences between topical areas. NASA’s Science Discovery Engine (SDE) has developed several approaches to tackling these challenges. The SDE is a unified, insightful search experience that enables discovery of NASA’s open science data across five topical areas: astrophysics, biological and physical sciences, Earth science, heliophysics and planetary science. In this presentation, we will discuss our efforts to develop a systematic scientific curation workflow to integrate diverse content into a single search environment. We will also share lessons learned from our work to create a metadata crosswalk across the five disciplines.
Parametric data on split-combustor linear engine propulsion systems are presented for use in mixed-mode single-stage-to-orbit (SSTO) vehicle studies. Preliminary design data for two selected engine systems are included. The split combustor was investigated for mixed-mode operations with oxygen/hydrogen propellants used in the inner combustor in Mode 2, and in conjunction with either oxygen/RP-1, oxygen/RJ-5, O2/CH4, or O2/H2 propellants in the outer combustor for Mode 1. Both gas generator and staged combustion power cycles were analyzed for providing power to the turbopumps of the inner and outer combustors. Numerous cooling circuits and cooling fluids (propellants) were analyzed and hydrogen was selected as the preferred coolant for both combustors and the linear aerospike nozzle. The maximum operating chamber pressure was determined to be limited by the availability of hydrogen coolant pressure drop in the coolant circuit.
A major objective of the grant was to complete the fabrication, test, and evaluation of the atmosphere structure experiment on the Galileo Probe, and to receive, analyze, and interpret data received from the spacecraft. The grantee was competitively selected to be Principal Investigator of Jupiter's atmosphere structure on the Galileo Probe. His primary motivation was to learn as much as possible about Jupiter's atmosphere by means of a successful atmosphere structure experiment, and to support the needs and schedule of the Galileo Project. After a number of launch delays, the Flight instrument was shipped to Kennedy Space Center 2 years after the start of this collaboration, on April 14, 1989, at which time it was determined from System level tests of the ASI on the Probe that the instrument was in good working order and ready for flight. The spacecraft was launched on October 18, 1989. Data analysis of test and calibration data taken over a period of years of instrument testing was continued in preparation for the encounter. The initial instrument checkout in space was performed on October 26, 1989. The data set received by telemetry was thoroughly analyzed, and a report of the findings was transmitted to the Probe Operations Office on Feb. 28, 1990. Key findings reported were that the accelerometer biases had shifted by less than 1 mg through launch and since calibration at Bell Aerospace in 1983; accelerometer scale factors, evaluated by means of calibration currents, fell on lines of variation with temperature established in laboratory calibrations; pressure sensor offsets, correlated as a function of temperature, fell generally within the limits of several years of ground test data; atmospheric and engineering temperature sensor data were internally consistent within a few tenths of a degree; and the instrument electronics performed all expected functions without any observable fault. Altogether, this checkout was highly encouraging of the prospects of instrument performance, although performed greater than 5 years prior to Jupiter encounter. Capability of decoding the science data from the Experiment Data Record to be provided at encounter was developed and exercised using the tape recording of the first Cruise Checkout data. A team effort was organized to program the selection and combination of data words defining pressure, temperature, acceleration, turbulence, and engineering quantities; to apply decalibration algorithms to convert readings from digital numbers to physical quantities; and to organize the data into a suitable printout. A paper on the Galileo Atmosphere Structure Instrument was written and submitted for publication in a special issue of Space Science Reviews. At the Journal editor's request, the grantee reviewed other Probe instrument papers submitted for this special issue. Calibration data were carefully taken for all experiment sensors and accumulated over a period of 10 years. The data were analyzed, fitted with algorithms, and summarized in a calibration report for use in analyzing and interpreting data returned from Jupiter's atmosphere. The sensors included were the primary science pressure, temperature, and acceleration sensors, and the supporting engineering temperature sensors. This report was distributed to experiment coinvestigators and the Probe Project Office.