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At least 145 records · Page 8

Rocket-Plume Spectroscopy Simulation for Hydrocarbon-Fueled Rocket Engines

The UV-Vis spectroscopic system for plume diagnostics monitors rocket engine health by using several analytical tools developed at Stennis Space Center (SSC), including the rocket plume spectroscopy simulation code (RPSSC), to identify and quantify the alloys from the metallic elements observed in engine plumes. Because the hydrocarbon-fueled rocket engine is likely to contain C2, CO, CH, CN, and NO in addition to OH and H2O, the relevant electronic bands of these molecules in the spectral range of 300 to 850 nm in the RPSSC have been included. SSC incorporated several enhancements and modifications to the original line-by-line spectral simulation computer program implemented for plume spectral data analysis and quantification in 1994. These changes made the program applicable to the Space Shuttle Main Engine (SSME) and the Diagnostic Testbed Facility Thruster (DTFT) exhaust plume spectral data. Modifications included updating the molecular and spectral parameters for OH, adding spectral parameter input files optimized for the 10 elements of interest in the spectral range from 320 to 430 nm and linking the output to graphing and analysis packages. Additionally, the ability to handle the non-uniform wavelength interval at which the spectral computations are made was added. This allowed a precise superposition of wavelengths at which the spectral measurements have been made with the wavelengths at which the spectral computations are done by using the line-by-line (LBL) code. To account for hydrocarbon combustion products in the plume, which might interfere with detection and quantification of metallic elements in the spectral region of 300 to 850 nm, the spectroscopic code has been enhanced to include the carbon-based combustion species of C2, CO, and CH. In addition, CN and NO have spectral bands in 300 to 850 nm and, while these molecules are not direct products of hydrocarbon-oxygen combustion systems, they can show up if nitrogen or a nitrogen compound is present as an impurity in the propellants and/or these can form in the boundary layer as a result of interaction of the hot plume with the atmosphere during the ground testing of engines. Ten additional electronic band systems of these five molecules have been included into the code. A comprehensive literature search was conducted to obtain the most accurate values for the molecular and the spectral parameters, including Franck-Cordon factors and electronic transition moments for all ten band systems. For each elemental transition in the RPSSC, six spectral parameters - Doppler broadened line width at half-height, pressure-broadened line width at half-height, electronic multiplicity of the upper state, electronic term energy of the upper state, Einstein transition probability coefficient, and the atomic line center - are required. Input files have been created for ten elements of Ni, Fe, Cr, Co, Cu, Ca, Mn, Al, Ag, and Pd, which retain only relatively moderate to strong transitions in 300 to 430 nm spectral range for each element. The number of transitions in the input files is 68 for Ni; 148 for Fe; 6 for Cr; 87 for Co; 1 for Ca; 3 for Mn; 2 each for Cu, Al, and Ag; and 11 for Pd.

Tejwani, Gopal D.↗

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

Dempsey, Paula J.↗

Investigation of Tapered Roller Bearing Damage Detection Using Oil Debris Analysis

A diagnostic tool was developed for detecting fatigue damage to tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests performed by The Timken Company in their Tapered Roller Bearing Health Monitoring Test Rig. Failure progression tests were performed under simulated engine load conditions. Tests were performed on one healthy bearing and three predamaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of debris generated during failure of the bearing. The bearing was removed periodically for inspection throughout the failure progression tests. Results indicate the accumulated oil debris mass is a good predictor of damage on tapered roller bearings. The use of a fuzzy logic model to enable an easily interpreted diagnostic metric was proposed and demonstrated.

Dempsey, Paula J.↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Diagnosis↗

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗

Automated knowledge generation

The general objectives of the NASA/UCF Automated Knowledge Generation Project were the development of an intelligent software system that could access CAD design data bases, interpret them, and generate a diagnostic knowledge base in the form of a system model. The initial area of concentration is in the diagnosis of the process control system using the Knowledge-based Autonomous Test Engineer (KATE) diagnostic system. A secondary objective was the study of general problems of automated knowledge generation. A prototype was developed, based on object-oriented language (Flavors).

Myler, Harley R.↗

Experimental investigation of a 0.15 scale model of a conformal variable-ramp inlet for the F-16 airplane

A 0.15 scale model of a proposed conformal variable-ramp inlet for the Multirole Fighter was tested from Mach 0.8 to 2.2 at a wide range of angles of attack and sideslip. Inlet ramp angle was varied to optimize ramp angle as a function of engine airflow, Mach number, angle of attack, and angle of sideslip. Several inlet configuration options were investigated to study their effects on inlet operation and to establish the final flight configuration. These variations were cowl sidewall cutback, cowl lip bluntness, boundary layer bleed, and first-ramp leading edge shape. Diagnostic and engine face instrumentation were used to evaluate inlet operation at various inlet stations and at the inlet/engine interface. Pressure recovery and stability of the inlet were satisfactory for the proposed application. On the basis of an engine stability audit of the worst-case instantaneous distortion patterns, no inlet/engine compatibility problems are expected for normal operations.

Hawkins, J. E.↗

EOS MLS Level 1B Data Processing Software

This software is an improvement on Version 2, which was described in EOS MLS Level 1B Data Processing, Version 2.2, NASA Tech Briefs, Vol. 33, No. 5 (May 2009), p. 34. It accepts the EOS MLS Level 0 science/engineering data, and the EOS Aura spacecraft ephemeris/attitude data, and produces calibrated instrument radiances and associated engineering and diagnostic data. This version makes the code more robust, improves calibration, provides more diagnostics outputs, defines the Galactic core more finely, and fixes the equator crossing. The Level 1 processing software manages several different tasks. It qualifies each data quantity using instrument configuration and checksum data, as well as data transmission quality flags. Statistical tests are applied for data quality and reasonableness. The instrument engineering data (e.g., voltages, currents, temperatures, and encoder angles) is calibrated by the software, and the filter channel space reference measurements are interpolated onto the times of each limb measurement with the interpolates being differenced from the measurements. Filter channel calibration target measurements are interpolated onto the times of each limb measurement, and are used to compute radiometric gain. The total signal power is determined and analyzed by each digital autocorrelator spectrometer (DACS) during each data integration. The software converts each DACS data integration from an autocorrelation measurement in the time domain into a spectral measurement in the frequency domain, and estimates separately the spectrally, smoothly varying and spectrally averaged components of the limb port signal arising from antenna emission and scattering effects. Limb radiances are also calibrated.

Perun, Vincent S.↗

Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission

Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft’s health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system’s health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD’s ability to run successfully in a spacecraft’s resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.

Nikora, Allen↗

Comparison of Results Obtained from Flight Tests and Simulated Tests of a Digital Electronic Engine Control System in an F-15 Airplane

Substantial benefits of a full authority digital electronic engine control on an air breathing engine were demonstrated repeatedly in simulation studies, ground engine tests, and engine altitude test facilities. A digital engine electronic control system showed improvements in efficiency, performance, and operation. An additional benefit of full authority digital controls is the capability of detecting and correcting failures and providing engine health diagnostics.

Myers, Lawrence P.↗

Instrumentation technology overview

The Instrumentation Technology program advances the state of the art of instrumentation associated with the SSME to improve service life and performance by providing increased measurement capability. Two broad categories of instrumentation technology are sought. The first category includes sensors and systems destined to be used in and on the operational engine either during operation or between operations. These measurements supply information necessary for engine control and/or diagnostics throughout the life of the engine. The second category includes measurement systems and techniques whose application will be to engine component test stands and possibly to the test bed engine. The measurements provide the detailed information necessary to verify computer models of the performance of the various engine subsystems.

Nieberding, W. C.↗

Progress report - Advanced cryogenic OTV engine technology

New technologies for space-based, reusable, throttleable, cryogenic orbit transfer propulsion are being evaluated. A variable-thrust (200 to 3000 lbF), 2000 psi chamber pressure, LO2/LH2 engine has been selected to demonstrate the 20-hour, 500-restart life goal, and a specific impulse in excess of 480 lbF-sec/lbM. The results of recent vehicle-engine integration analyses and the progress in design, fabrication, and testing are provided. Emphasis is placed on the following technology areas being investigated in support of the advanced engine design: LOX hydrostatic bearings; burn-resistant materials for high-pressure GOX turbines and valves; high surface-low flux annular combustion chambers for the dual propellant expander cycle; improved cooling approaches for high-pressure combustion chambers, new concepts in integrated controls; and engine health diagnostics.

Schoenman, L.↗

Real-time diagnostics of the reusable rocket engine using on-line system identification

A model-based failure diagnosis system has been proposed for real-time diagnosis of SSME failures. Actuation, sensor, and system degradation failure modes are all considered by the proposed system. In the case of SSME actuation failures, it was shown that real-time identification can effectively be used for failure diagnosis purposes. It is a direct approach since it reduces the detection, isolation, and the estimation of the extent of the failures to the comparison of parameter values before and after the failure. As with any model-based failure detection system, the proposed approach requires a fault model that embodies the essential characteristics of the failure process. The proposed diagnosis approach has the added advantage that it can be used as part of an intelligent control system for failure accommodation purposes.

Guo, T.-H.↗

Supersonics--Airport Noise

At this, the first year-end meeting of the Fundamental Aeronautics Program, an overview of the Airport Noise discipline of the Supersonics Project leads the presentation of technical plans and achievements in this area of the Project. The overview starts by defining the Technical Challenges targeted by Airport Noise efforts, and the Approaches planned to meet these challenges. These are fleshed out in Elements, namely Prediction, Diagnostics, and Engineering, and broken down into Tasks. The Tasks level is where individual researchers' work is defined and from whence the technical presentations to follow this presentation come. This overview also presents the Milestones accomplished to date and to be completed in the next year. Finally, the NASA Research Announcement cooperative agreement activities are covered and tied to the Tasks and Milestones.

Bridges, James↗

EOS MLS Level 1B Data Processing, Version 2.2

A computer program performs level- 1B processing (the term 1B is explained below) of data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS), which is an instrument aboard the Aura spacecraft. This software accepts, as input, the raw EOS MLS scientific and engineering data and the Aura spacecraft ephemeris and attitude data. Its output consists of calibrated instrument radiances and associated engineering and diagnostic data. [This software is one of several computer programs, denoted product generation executives (PGEs), for processing EOS MLS data. Starting from level 0 (representing the aforementioned raw data, the PGEs and their data products are denoted by alphanumeric labels (e.g., 1B and 2) that signify the successive stages of processing.] At the time of this reporting, this software is at version 2.2 and incorporates improvements over a prior version that make the code more robust, improve calibration, provide more diagnostic outputs, improve the interface with the Level 2 PGE, and effect a 15-percent reduction in file sizes by use of data compression.

Perun, Vincent↗

Feasibility Investigation on the Development of a Structural Damage Diagnostic and Monitoring System for Rocket Engines

The research activity for this project is mainly to investigate the necessity and feasibility to develop a structural health monitoring system for rocket engines, and to carry out a research plan for further development of the system. More than one hundred technical papers have been searched and reviewed during the period. We concluded after this investigation that adding a new module in NASA's existing automated diagnostic system to monitor the healthy condition of rocket engine structures is a crucial task, and it's possible to develop such a system based upon the vibrational-based nondestructive damage assessment techniques. A number of such techniques have been introduced. Their advantages and disadvantages are also discussed. A global research plan has been figured out. As the first step of the overall research plan, a proposal for the next fiscal year has been submitted.

Shen, Ji Y.↗