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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Structural Modeling Using "Scanning and Mapping" Technique

Supported by NASA Glenn Center, we are in the process developing a structural damage diagnostic and monitoring system for rocket engines, which consists of five modules: Structural Modeling, Measurement Data Pre-Processor, Structural System Identification, Damage Detection Criterion, and Computer Visualization. The function of the system is to detect damage as it is incurred by the engine structures. The scientific principle to identify damage is to utilize the changes in the vibrational properties between the pre-damaged and post-damaged structures. The vibrational properties of the pre-damaged structure can be obtained based on an analytic computer model of the structure. Thus, as the first stage of the whole research plan, we currently focus on the first module - Structural Modeling. Three computer software packages are selected, and will be integrated for this purpose. They are PhotoModeler-Pro, AutoCAD-R14, and MSC/NASTRAN. AutoCAD is the most popular PC-CAD system currently available in the market. For our purpose, it plays like an interface to generate structural models of any particular engine parts or assembly, which is then passed to MSC/NASTRAN for extracting structural dynamic properties. Although AutoCAD is a powerful structural modeling tool, the complexity of engine components requires a further improvement in structural modeling techniques. We are working on a so-called "scanning and mapping" technique, which is a relatively new technique. The basic idea is to producing a full and accurate 3D structural model by tracing on multiple overlapping photographs taken from different angles. There is no need to input point positions, angles, distances or axes. Photographs can be taken by any types of cameras with different lenses. With the integration of such a modeling technique, the capability of structural modeling will be enhanced. The prototypes of any complex structural components will be produced by PhotoModeler first based on existing similar components, then passed to AutoCAD for modification and correction of any discrepancies seen in the Photomodeler version of the 3Dmodel. These three software packages are fully compatible. The DXF file can be used to transfer drawings among those packages. To begin this entire process, we are using a small replica of an actual engine blade as a test object. This paper introduces the accomplishment of our recent work.

Amos, Courtney L.↗
NASA NTRS2005

NASA Glenn Research in Controls and Diagnostics for Intelligent Aerospace Propulsion Systems

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. Also the propulsion systems required to enable the NASA (National Aeronautics and Space Administration) Vision for Space Exploration in an affordable manner will need to have high reliability, safety and autonomous operation capability. The Controls and Dynamics Branch at NASA Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. The key enabling technologies for an Intelligent Propulsion System are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance operational reliability and component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This paper describes the current activities of the Controls and Dynamics Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Source record↗
NASA NTRS2020

DGEN Aeropropulsion Research Turbofan Source-Diagnostic Test: Experimental Setup and Acoustic-Data Structure

The experimental setup of, and available data from a recent core/combustor-noise source-diagnostic test utilizing a small turbofan engine are described. The 2019 test campaign continued the investigation of the core/combustor-noise component of aircraft-propulsor noise begun in an earlier baseline test, but with a more extensive acoustic-instrumentation layout. The purpose of both tests was to better understand the impact on civilian-transport airport-community noise from turbofan-combustor sources and thereby to lay the foundation for improved noise-prediction methods and noise-mitigation techniques. Simultaneous high-data-rate acoustic measurements were obtained using a circumferential sensor array at the core nozzle exit in conjunction with sideline and farfield microphone arrays. The test matrix contained engine operational points from engine idle to maximum power and was repeated for different circumferential and sideline array configurations, as well as for redundancy. The extensive data set (up to 93 channels of data and various configurations) allows the application of advanced source-separation and phased-array methods to elucidate not only the core-noise structure, but also the propagation characteristics of other propulsion noise sources. The present report provides a detailed description of the different test points, their associated instrumentation layouts, and the structure of the acquired data set. Results from various data analyses are reported separately.

Aeroacoustics↗
NASA NTRS1989

Reusable rocket engine turbopump health monitoring system, part 3

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Perry, John G.↗
NASA NTRS2007

Automated Diagnosis and Control of Complex Systems

Livingstone2 is a reusable, artificial intelligence (AI) software system designed to assist spacecraft, life support systems, chemical plants, or other complex systems by operating with minimal human supervision, even in the face of hardware failures or unexpected events. The software diagnoses the current state of the spacecraft or other system, and recommends commands or repair actions that will allow the system to continue operation. Livingstone2 is an enhancement of the Livingstone diagnosis system that was flight-tested onboard the Deep Space One spacecraft in 1999. This version tracks multiple diagnostic hypotheses, rather than just a single hypothesis as in the previous version. It is also able to revise diagnostic decisions made in the past when additional observations become available. In such cases, Livingstone might arrive at an incorrect hypothesis. Re-architecting and re-implementing the system in C++ has increased performance. Usability has been improved by creating a set of development tools that is closely integrated with the Livingstone2 engine. In addition to the core diagnosis engine, Livingstone2 includes a compiler that translates diagnostic models written in a Java-like language into Livingstone2's language, and a broad set of graphical tools for model development.

Kurien, James↗
NASA NTRS2005

Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management

Aircraft gas-turbine engine data is available from a variety of sources, including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data fusion is the integration of data or information from multiple sources for the achievement of improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/ information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This report describes a basic PHM data fusion architecture being developed in alignment with the NASA C-17 PHM Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center, NASA Dryden Flight Research Center, and Pratt & Whitney have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion, as it applies to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This report will provide a chronology and summary of the work accomplished under this research contract.

Volponi, Al↗
NASA NTRS1993

A laboratory model of a hydrogen/oxygen engine for combustion and nozzle studies

A small laboratory diagnostic thruster was developed in order to evaluate approaches for the use of temperature and pressure sensors for the investigation of low thrust rocket flowfields. Tests were performed at chamber pressures of about 255 kPa, 370 kPa, and 500 kPa with oxidizer/fuel mixture ratios between 4.0 and 8.0. Two gaseous hydrogen/gaseous oxygen injector designs were tested with 60 and 75 fuel film cooling. The results of hot-wire tests showed the thruster and instrumentation designs to be effective. Azimuthal temperature distributions were found to be a function of operating conditions and hardware configuration. Results indicated that small differences in injector design can result in dramatically different thruster performance and wall temperature behavior. However, the importance of these injector effects may be decreased by operating at a high fuel film cooling rate.

Morren, Sybil H.↗
NASA NTRS2006

Aligned and Unaligned Coherence: A New Diagnostic Tool

The study of combustion noise from turbofan engines has become important again as the noise from other sources like the fan and jet are reduced. A method has been developed to help identify combustion noise spectra using an aligned and unaligned coherence technique. When used with the well known three signal coherent power method and coherent power method it provides new information by separating tonal information from random process information. Examples are presented showing the underlying tonal structure which is buried under broadband noise and jet noise. The method is applied to data from a Pratt and Whitney PW4098 turbofan engine.

Miles, Jeffrey Hilton↗
NASA NTRS2010

J-2X Turbopump Cavitation Diagnostics

The J-2X is the upper stage engine currently being designed by Pratt & Whitney Rocketdyne (PWR) for the Ares I Crew Launch Vehicle (CLV). Propellant supply requirements for the J-2X are defined by the Ares Upper Stage to J-2X Interface Control Document (ICD). Supply conditions outside ICD defined start or run boxes can induce turbopump cavitation leading to interruption of J-2X propellant flow during hot fire operation. In severe cases, cavitation can lead to uncontained engine failure with the potential to cause a vehicle catastrophic event. Turbopump and engine system performance models supported by system design information and test data are required to predict existence, severity, and consequences of a cavitation event. A cavitation model for each of the J-2X fuel and oxidizer turbopumps was developed using data from pump water flow test facilities at Pratt & Whitney Rocketdyne (PWR) and Marshall Space Flight Center (MSFC) together with data from Powerpack 1A testing at Stennis Space Center (SSC) and from heritage systems. These component models were implemented within the PWR J-2X Real Time Model (RTM) to provide a foundation for predicting system level effects following turbopump cavitation. The RTM serves as a general failure simulation platform supporting estimation of J-2X redline system effectiveness. A study to compare cavitation induced conditions with component level structural limit thresholds throughout the engine was performed using the RTM. Results provided insight into system level turbopump cavitation effects and redline system effectiveness in preventing structural limit violations. A need to better understand structural limits and redline system failure mitigation potential in the event of fuel side cavitation was indicated. This paper examines study results, efforts to mature J-2X turbopump cavitation models and structural limits, and issues with engine redline detection of cavitation and the use of vehicle-side abort triggers to augment the engine redline system.

Santi, I. Michael↗
NASA NTRS1994

Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.

Iverson, David L.↗
NASA NTRS2002

Measuring Rocket Engine Temperatures with Hydrogen Raman Spectroscopy

Laser-based combustion diagnostics, such as single-pulse UV Raman spectroscopy and visible Raman spectroscopy, have been successfully applied to optically-accessible rocket-like test articles. If an independent pressure measurement is available, Raman major species concentration measurements can also provide a temperature measurement. However it is desirable to obtain a Raman-derived temperature measurement without the need for simultaneous pressure measurement, especially when chamber pressure may vary spatially. This report describes Raman temperature measurements obtained by exploiting the variation in shape of the H2 Raman spectrum. Hydrogen is advantageous since it is ubiquitous in H2-O2 systems and its Raman spectrum is simpler than for other diatomics. However the influence of high pressure on the H2 Raman spectrum must be investigated. At moderate pressures, well below those of rocket engines, the Raman spectra of O2 and N2 are known to become featureless due to collisional broadening.

Joseph A Wehrmeyer↗
NASA NTRS1992

Emission spectra of selected SSME elements and materials

Stennis Space Center (SSC) is pursuing the advancement of experimental techniques and theoretical developments in the field of plume spectroscopy for application to rocket development testing programs and engine health monitoring. Exhaust plume spectral data for the Space Shuttle Main Engine (SSME) are routinely acquired. The usefulness of this data depends upon qualitative and quantitative interpretation of spectral features and their correlation with the engine performance. A knowledge of the emission spectral characteristics of effluent materials in the exhaust plume is essential. A study of SSME critical components and their materials identified 30 elements and 53 materials whose engine exhaust plume spectral might be required. The most important were evaluated using SSC's Diagnostic Testbed Facility Thruster (DTFT), a 1200-lbf, liquid oxygen/gaseous hydrogen rocket engine which very nearly replicates the temperature and pressure conditions of the SSME exhaust plume in the first Mach diamond. This report presents the spectral data for the 10 most important elements and 27 most important materials which are strongly to moderately emitting in the DTFT exhaust plume. The covered spectral range is 300 to 426 nm and the spectral resolution is 0.25 nm. Spectral line identification information is provided and line interference effects are considered.

Tejwani, Gopal D.↗
NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗
NASA NTRS1992

Intelligent diagnostics systems

Intelligent systems have been applied to today's problems and could also be applied to space operations integrity. One of these systems is the XMAN tool designed for 'troubleshooting' jet engines. XMAN is the eXpert MAiNtenance tool developed to be an expert information analysis tool which stores trending and diagnostic data on Air Force engines. XMAN operates with a 'network topology' which follows a flow chart containing engine management information reports required by the governments technical order procedures. With XMAN technology, the user is able to identify engine problems by presenting the assertions of the fault isolation logic and attempting to satisfy individual assertions by referring to the databases created by an engine monitoring system. The troubleshooting process requires interaction between the technician and the computer to acquire new evidence form auxiliary maintenance tests corroboration of analytical results to accurately diagnose equipment malfunctions. This same technology will be required for systems which are functioning in space either with an onboard crew, or with an unmanned system. The technology and lessons learned developing this technology while suggesting definite applications for its use with developing space systems are addressed.

Mcquiston, Barbara M.↗
NASA NTRS1995

A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

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.

Wu, G. Gordon↗
NASA NTRS1994

An Object-Oriented Graphical User Interface for a Reusable Rocket Engine Intelligent Control System

An intelligent control system for reusable rocket engines under development at NASA Lewis Research Center requires a graphical user interface to allow observation of the closed-loop system in operation. The simulation testbed consists of a real-time engine simulation computer, a controls computer, and several auxiliary computers for diagnostics and coordination. The system is set up so that the simulation computer could be replaced by the real engine and the change would be transparent to the control system. Because of the hard real-time requirement of the control computer, putting a graphical user interface on it was not an option. Thus, a separate computer used strictly for the graphical user interface was warranted. An object-oriented LISP-based graphical user interface has been developed on a Texas Instruments Explorer 2+ to indicate the condition of the engine to the observer through plots, animation, interactive graphics, and text.

Litt, Jonathan S.↗
NASA NTRS1981

Symposium /International/ on Combustion, 18th, University of Waterloo, Waterloo, Ontario, Canada, August 17-22, 1980, Proceedings

Problems related to combustion generated pollution are explored, taking into account the mechanism of NO formation from nitrogen compounds in hydrogen flames studied by laser fluorescence, the structure and similarity of nitric oxide production in turbulent diffusion flames, the effect of steam addition on NO formation, and the formation of NO2 by laminar flames. Other topics considered are concerned with propellant combustion, fluidized bed combustion, the combustion of droplets and sprays, premixed flame studies, fire studies, and flame stabilization. Attention is also given to coal flammability, chemical kinetics, turbulent combustion, soot, coal combustion, the modeling of combustion processes, combustion diagnostics, detonations and explosions, ignition, internal combustion engines, combustion studies, and furnaces.

Source record↗
NASA NTRS1989

Development of fiber-based laser anemometer for SSME application

A recent study by Rocketdyne for NASA identified laser anemometry, using a compact optical head, as a feasible diagnostic instrument for the Space Shuttle Main Engine (SSME) Model Verification experiments. Physical Research, Inc. (PRI) is presently under contract from NASA Lewis to develop and deliver such a laser anemometer system. For this application, it is desired to place the laser at a remote distance from the engine, and use single mode polarization preserving fiber optics for the transmission of the laser light to and from the measurement head. Other requirements are given. Analytical and experimental tools are being used to develop the technologies required for the laser anemometer. These include finite element analysis of the optical head and vibration tests for various optical and mechanical components. Design of the optical head and the fiber optic connectors are driven by the temperature and vibration requirements for the measurement environment. Results of the finite element analysis and the vibration tests of the components are included. Conceptual design of the fiber optic launcher and the optical probe has also been complete. Detailed design of the probe as well as the fabrication and assembly of the components is in progress.

Modarress, Dariush↗