Engineering topics

Garg, Sanjay

Publications and source records attributed to Garg, Sanjay.

At least 37 records · Page 2

NASA NTRS2010

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Simon, Donald L.↗

NASA NTRS2010

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Simon, Donald L.↗

NASA NTRS2009

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Simon, Donald L.↗

NASA NTRS2008

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

NASA NTRS2008

Implementation Challenges for Multivariable Control: What You Did Not Learn in School

Multivariable control allows controller designs that can provide decoupled command tracking and robust performance in the presence of modeling uncertainties. Although the last two decades have seen extensive development of multivariable control theory and example applications to complex systems in software/hardware simulations, there are no production flying systems aircraft or spacecraft, that use multivariable control. This is because of the tremendous challenges associated with implementation of such multivariable control designs. Unfortunately, the curriculum in schools does not provide sufficient time to be able to provide an exposure to the students in such implementation challenges. The objective of this paper is to share the lessons learned by a practitioner of multivariable control in the process of applying some of the modern control theory to the Integrated Flight Propulsion Control (IFPC) design for an advanced Short Take-Off Vertical Landing (STOVL) aircraft simulation.

Garg, Sanjay↗

NASA NTRS2007

Propulsion Health Management System Development for Affordable and Reliable Operation of Space Exploration Systems

The constraints of future Exploration Missions will require unique integrated system health management capabilities throughout the mission. An ambitious launch schedule, human-rating requirements, long quiescent periods, limited human access for repair or replacement, and long communication delays, all require an integrated approach to health management that can span distinct, yet interdependent vehicle subsystems, anticipate failure states, provide autonomous remediation and support the Exploration Mission from beginning to end. Propulsion is a critical part of any space exploration mission, and monitoring the health of the propulsion system is an integral part of assuring mission safety and success. Health management is a somewhat ubiquitous technology that encompasses a large spectrum of physical components and logical processes. For this reason, it is essential to develop a systematic plan for propulsion health management system development. This paper provides a high-level perspective of propulsion health management systems, and describes a logical approach for the future planning and early development that are crucial to planned space exploration programs. It also presents an overall approach, or roadmap, for propulsion health management system development and a discussion of the associated roadblocks and challenges.

Melcher, Kevin J.↗

NASA NTRS2007

Propulsion Controls and Diagnostics Research at NASA Glenn Research Center

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 National Aeronautics and Space Administration (NASA) Vision for Space Exploration in an affordable manner will need to have high reliability, safety and autonomous operation capability. The Controls and Dynamics Branch (CDB) 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. This paper describes the current activities of the CDB under the NASA Aeronautics Research and Exploration Systems Missions. The programmatic structure of the CDB activities is described along with a brief overview of each of the CDB tasks including research objectives, technical challenges, and recent accomplishments. These tasks include active control of propulsion system components, intelligent propulsion diagnostics and control for reliable fault identification and accommodation, distributed engine control, and investigations into unsteady propulsion systems.

Garg, Sanjay↗

NASA NTRS2007

A Retro-Fit Control Architecture to Maintain Engine Performance With Usage

An outer loop retrofit engine control architecture is presented which modifies fan speed command to obtain a desired thrust based on throttle position. This maintains the throttle-to-thrust relationship in the presence of engine degradation, which has the effect of changing the engine s thrust output for a given fan speed. Such an approach can minimize thrust asymmetry in multi-engine aircraft, and reduce pilot workload. The outer loop control is demonstrated under various levels of engine deterioration using a standard deterioration profile as well as an atypical profile. It is evaluated across various transients covering a wide operating range. The modified fan speed command still utilizes the standard engine control logic so all original life and operability limits remain in place. In all cases it is shown that with the outer loop thrust control in place, the deteriorated engine is able to match the thrust performance of a new engine up to the limits the controller will allow.

Litt, Jonathan S.↗

NASA NTRS2007

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. The Controls and Dynamics Branch (CDB) at NASA (National Aeronautics and Space Administration) 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. This presentation describes the current CDB activities in support of the NASA Aeronautics Research Mission, with an emphasis on activities under the Integrated Vehicle Health Management (IVHM) and Integrated Resilient Aircraft Control (IRAC) projects of the Aviation Safety Program. Under IVHM, CDB focus is on developing advanced techniques for monitoring the health of the aircraft engine gas path with a focus on reliable and early detection of sensor, actuator and engine component faults. Under IRAC, CDB focus is on developing adaptive engine control technologies which will increase the probability of survival of aircraft in the presence of damage to flight control surfaces or to one or more engines. The technology development plans are described as well as results from recent research accomplishments.

Garg, Sanjay↗

NASA NTRS2007

Status, Vision, and Challenges of an Intelligent Distributed Engine Control Architecture

A Distributed Engine Control Working Group (DECWG) consisting of the Department of Defense (DoD), the National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) and industry has been formed to examine the current and future requirements of propulsion engine systems. The scope of this study will include an assessment of the paradigm shift from centralized engine control architecture to an architecture based on distributed control utilizing open system standards. Included will be a description of the work begun in the 1990's, which continues today, followed by the identification of the remaining technical challenges which present barriers to on-engine distributed control.

Behbahani, Alireza↗

NASA NTRS2005

Propulsion Control Technology Development in the United States A Historical Perspective

This paper presents a historical perspective of the advancement of control technologies for aircraft gas turbine engines. The paper primarily covers technology advances in the United States in the last 60 years (1940 to approximately 2002). The paper emphasizes the pioneering technologies that have been tested or implemented during this period, assimilating knowledge and experience from industry experts, including personal interviews with both current and retired experts. Since the first United States-built aircraft gas turbine engine was flown in 1942, engine control technology has evolved from a simple hydro-mechanical fuel metering valve to a full-authority digital electronic control system (FADEC) that is common to all modern aircraft propulsion systems. At the same time, control systems have provided engine diagnostic functions. Engine diagnostic capabilities have also evolved from pilot observation of engine gauges to the automated on-board diagnostic system that uses mathematical models to assess engine health and assist in post-flight troubleshooting and maintenance. Using system complexity and capability as a measure, we can break the historical development of control systems down to four phases: (1) the start-up phase (1942 to 1949), (2) the growth phase (1950 to 1969), (3) the electronic phase (1970 to 1989), and (4) the integration phase (1990 to 2002). In each phase, the state-of-the-art control technology is described and the engines that have become historical landmarks, from the control and diagnostic standpoint, are identified. Finally, a historical perspective of engine controls in the last 60 years is presented in terms of control system complexity, number of sensors, number of lines of software (or embedded code), and other factors.

Jaw, Link C.a↗

NASA NTRS2005

A Survey of Intelligent Control and Health Management Technologies for Aircraft Propulsion Systems

Intelligent Control and Health Management technology for aircraft propulsion systems is much more developed in the laboratory than in practice. With a renewed emphasis on reducing engine life cycle costs, improving fuel efficiency, increasing durability and life, etc., driven by various government programs, there is a strong push to move these technologies out of the laboratory and onto the engine. This paper describes the existing state of engine control and on-board health management, and surveys some specific technologies under development that will enable an aircraft propulsion system to operate in an intelligent way--defined as self-diagnostic, self-prognostic, self-optimizing, and mission adaptable. These technologies offer the potential for creating extremely safe, highly reliable systems. The technologies will help to enable a level of performance that far exceeds that of today s propulsion systems in terms of reduction of harmful emissions, maximization of fuel efficiency, and minimization of noise, while improving system affordability and safety. Technologies that are discussed include various aspects of propulsion control, diagnostics, prognostics, and their integration. The paper focuses on the improvements that can be achieved through innovative software and algorithms. It concentrates on those areas that do not require significant advances in sensors and actuators to make them achievable, while acknowledging the additional benefit that can be realized when those technologies become available. The paper also discusses issues associated with the introduction of some of the technologies.

Litt, Jonathan S.↗

NASA NTRS2004

Propulsion Control and Health Management (PCHM) Technology for Flight Test on the C-17 T-1 Aircraft

The C-I 7 T-l Globemaster III is an Air Force flight research vehicle located at Edwards Air Force Base. NASA Dryden and the C-17 System Program Office have entered into a Memorandum of Agreement to permit NASA the use of the C-I 7 T-I to conduct flight research on a mutually coordinated schedule. The C-17 Propulsion Control and Health Management (PCHM) Working Group was formed in order to foster discussion and coordinate planning amongst the various government agencies conducting PCHM research with a potential need for flight testing, and to communicate to the PCHM community the capabilities of the C-17 T-l aircraft to support such flight testing. This paper documents the output of this Working Group, including a summary of the candidate PCHM technologies identified and their associated benefits relative to NASA goals and objectives.

Simon, Donald L.↗

NASA NTRS2004

Controls and Health Management Technologies 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. The Controls and Dynamics Technology Branch at NASA (National Aeronautics and Space Administration) 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 an Intelligent Engine. The key enabling technologies for an Intelligent Engine are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance 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 Technology Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Garg, Sanjay↗

NASA NTRS2002

Propulsion Controls and Health Management Research at NASA Glenn Research Center

Garg, Sanjay↗

NASA NTRS2001

Aeroelastic Deformation Measurements of Flap, Gap, and Overhang on a Semispan Model

Single-camera, single-view videogrammetry has been used for the first time to determine static aeroelastic deformation of a slotted flap configuration on a semispan model at the National Transonic Facility (NTF). Deformation was determined by comparing wind-off to wind-on spatial data from targets placed on the main element, shroud, and flap of the model. Digitized video images from a camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. The videogrammetric technique used for the measurements presented here has been established at NASA facilities as the technique of choice when high-volume static aeroelastic data with minimum impact on data taking is required. However, the primary measurement at the NTF with this technique in the past has been the measurement of the static aeroelastic wing twist of the main wing element on full span models rather than for the measurement of component deformation. Considerations for using the videogrammetric technique for semispan component deformation measurements as well as representative results are presented.

Burner, A. W.↗

NASA NTRS2000

Aeroelastic Deformation Measurements of Flap, Gap, and Overhang on a Semispan Model

Single-camera, single-view videogrammetry has been used to determine static aeroelastic deformation of a slotted flap configuration on a semispan model at the National Transonic Facility (NTF). Deformation was determined by comparing wind-off to wind-on spatial data from targets placed on the main element, shroud, and flap of the model. Digitized video images from a camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. The videogrammetric technique has been established at NASA facilities as the technique of choice when high-volume static aeroelastic data with minimum impact on data taking is required. The primary measurement at the NTF with this technique in the past has been the measurement of static aeroelastic wing twist on full span models. The first results using the videogrammetric technique for the measurement of component deformation during semispan testing at the NTF are presented.

Burner, A. W.↗

NASA NTRS1999

Unified Model Deformation and Flow Transition Measurements

The number of optical techniques that may potentially be used during a given wind tunnel test is continually growing. These include parameter sensitive paints that are sensitive to temperature or pressure, several different types of off-body and on-body flow visualization techniques, optical angle-of-attack (AoA), optical measurement of model deformation, optical techniques for determining density or velocity, and spectroscopic techniques for determining various flow field parameters. Often in the past the various optical techniques were developed independently of each other, with little or no consideration for other techniques that might also be used during a given test. Recently two optical techniques have been increasingly requested for production measurements in NASA wind tunnels. These are the video photogrammetric (or videogrammetric) technique for measuring model deformation known as the video model deformation (VMD) technique, and the parameter sensitive paints for making global pressure and temperature measurements. Considerations for, and initial attempts at, simultaneous measurements with the pressure sensitive paint (PSP) and the videogrammetric techniques have been implemented. Temperature sensitive paint (TSP) has been found to be useful for boundary-layer transition detection since turbulent boundary layers convect heat at higher rates than laminar boundary layers of comparable thickness. Transition is marked by a characteristic surface temperature change wherever there is a difference between model and flow temperatures. Recently, additional capabilities have been implemented in the target-tracking videogrammetric measurement system. These capabilities have permitted practical simultaneous measurements using parameter sensitive paint and video model deformation measurements that led to the first successful unified test with TSP for transition detection in a large production wind tunnel.

Burner, Alpheus W.↗