Results for “prompt engineering” — Page 2

NASA NTRSDate not supplied

Solar Cycle 25 Model Prediction Comparisons: an Engineering Perspective

The solar cycle 25 progression is ramping up, prompting satellite operators to provide estimates of propellent usage over the next several years. Drag due to atmospheric heating from solar activity is the main driver to satellite lifetime decay, especially for those in low-Earth orbit destinations. In this poster, several model predictions of the sunspot number are compared and discussed with comments on applicability to engineering programs.

Space Weather↗

NASA NTRS2005

Search for Polarization from the Prompt Gamma-Ray Emission of GRB 041219 with SPI on INTEGRAL

Measuring the polarization of the prompt gamma-ray emission from GRBs can significantly improve our understanding of both the GRB emission mechanisms, as well as the underlying engine driving the explosion. We searched for polarization in the prompt gamma-ray emission of GRB 041219 with the SPI instrument on INTEGRAL. Using multiple-detector coincidence events in the 100-500 keV energy band, our analysis yields a polarization fraction from this GRB of 66 f 21%. While statistically this measurement suggests a non-zero polarization, we cannot strongly rule out the possibility that the measured modulation is dominated by instrumental systematics. Therefore, SPI observations of GRB 041219 do not significantly constrain GRB models. However, this measurement demonstrates the capability of SPI to measure polarization, and the techniques developed for this analysis.

Kalemci, E.↗

NASA NTRS1984

Fuel property effects on USAF gas turbine engine combustors and afterburners

Since the early 1970s, the cost and availability of aircraft fuel have changed drastically. These problems prompted a program to evaluate the effects of broadened specification fuels on current and future aircraft engine combustors employed by the USAF. Phase 1 of this program was to test a set of fuels having a broad range of chemical and physical properties in a select group of gas turbine engine combustors currently in use by the USAF. The fuels ranged from JP4 to Diesel Fuel number two (DF2) with hydrogen content ranging from 14.5 percent down to 12 percent by weight, density ranging from 752 kg/sq m to 837 kg/sq m, and viscosity ranging from 0.830 sq mm/s to 3.245 sq mm/s. In addition, there was a broad range of aromatic content and physical properties attained by using Gulf Mineral Seal Oil, Xylene Bottoms, and 2040 Solvent as blending agents in JP4, JP5, JP8, and DF2. The objective of Phase 2 was to develop simple correlations and models of fuel effects on combustor performance and durability. The major variables of concern were fuel chemical and physical properties, combustor design factors, and combustor operating conditions.

Reeves, C. M.↗

NASA NTRS1982

Benchmark notch test for life prediction

Aircraft gas turbine engine components are subjected to severe stress, temperature, and environmental conditions. Economic and reliabilty demands have prompted inordinate effort in development of analytic methods to predict stresses and strains in aircraft engines. There remains, however, the need to check or verify these analytical methodologies against actual experimental data measurements. The laser interferometric strain displacement gage was recognized as having the potential to accomplish this task and was employed in this program. The actual strains incurred at the root of a discontinuity in cyclically loaded test samples subjected to inelastic deformation at high temperature where creep deformation readily occur were measured. The steady-state, cyclic stress-strain response at the root of the discontinuity in the tested samples was analyzed for comparison with the measured results. A comprehensive set of local notch root strain measurements for a variety of load patterns in an Inconel 718 notch specimen at 649 C (1200 F) was obtained and documented using the laser interferometric strain displacement gage.

Domas, P. A.↗

NASA NTRSDate not supplied

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

NASA NTRSDate not supplied

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

NASA NTRSDate not supplied

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

NASA NTRS2024

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

NASA NTRSDate not supplied

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

NASA NTRS1997

An Investigation of Nonlinear Controller for Propulsion Controlled Aircraft

Aircraft control systems are usually very reliable because of redundancy and multiple control surfaces. However, there are rare occasions when potentially disastrous flight control system failures do occur. At such times, the use of appropriate modulation of engine thrust to stabilize the aircraft may be the only chance of survival for the people aboard. In several cases where complete loss of control systems has occurred in multi-engine aircraft, pilots used the propulsion system to regain limited control of the aircraft with various degrees of success. In order to evaluate the feasibility of using only engine thrust modulation for emergency backup flight control, the NASA Dryden Flight Research Center has been conducting a series of analytical studies and flight tests on several different types of aircraft in a propulsion controlled aircraft (PCA) program. Simulation studies have included B-720, B-727, MD-11, C-402, C-17, F-18, and F-15, and flight tests have included B-747, B-777, MD-11, T-39, Lear 24, F-18, F-15, T-38, and PA-30. One objective was to determine the degree of control available with manual manipulation (open-loop) of the engine throttles. Flight tests and simulations soon showed that a closed loop controller could improve the chances of making a safe runway landing. The major work to date has concentrated on three aircraft (F-15, F-18, and the MD-11). Successful landings using PCA controllers were performed on the F-15 and MD-11 without the use of control surfaces. During the course of the research, some unique challenges have been identified. Compared to the conventional flight control surfaces, the engines are slow and have limited control effectiveness. Hence the ability of the system to promptly respond to aerodynamic changes is limited. Consequently, many nonlinear effects, which are easily accommodated by a conventional flight control system, become significant issues in the design of an effective controller when the engines are used as the only control effectors. A number of nonlinear behaviors observed during PCA flight tests, which are not meant to be exhaustive, are reviewed in the next section.

Lu, Ping↗

NASA NTRS2001

Laser Absorption Measurements of Equivalence Ratios Studied Along With Their Coupling to Pressure Fluctuations in Lean Premixed Prevaporized (LPP) Combustion

Concerns about damaging the Earth's ozone layer as a result of high levels of nitrogen oxides (known collectively as NOx) from high-altitude, high-speed aircraft have prompted the study of lean premixed prevaporized (LPP) combustion in aircraft engines. LPP combustion reduces NOx emissions principally by reducing the peak flame temperatures inside an engine. Recent advances in LPP technologies have realized exceptional reductions in pollutant emissions (single-digit ppm NOx for example). However, LPP combustion also presents major challenges: combustion instability and dynamic coupling effects between fluctuations in heat-release rate, dynamic pressure, and fuel pressure. These challenges are formidable and can literally shake an engine apart if uncontrolled. To better understand this phenomenon so that it can be controlled, we obtained real-time laser absorption measurements of the fuel vapor concentration (and equivalence ratio) simultaneously with the dynamic pressure, flame luminosity, and time-averaged gaseous emissions measurements in a research-type jet-A-fueled LPP combustor. The measurements were obtained in NASA Glenn Research Center's CE-5B optically accessible flame tube facility. The CE-5B facility provides inlet air temperatures and pressures similar to the actual operating conditions of real aircraft engines. The laser absorption measurements were performed using an infrared 3.39 micron HeNe laser in conjunction with a visible HeNe laser for liquid droplet scattering compensation.

Nguyen, Quang-Viet↗

NASA NTRS1983

Economic aspects of advanced coal-fired gas turbine locomotives

Increases in the price of such conventional fuels as Diesel No. 2, as well as advancements in turbine technology, have prompted the present economic assessment of coal-fired gas turbine locomotive engines. A regenerative open cycle internal combustion gas turbine engine may be used, given the development of ceramic hot section components. Otherwise, an external combustion gas turbine engine appears attractive, since although its thermal efficiency is lower than that of a Diesel engine, its fuel is far less expensive. Attention is given to such a powerplant which will use a fluidized bed coal combustor. A life cycle cost analysis yields figures that are approximately half those typical of present locomotive engines.

Liddle, S. G.↗

NASA NTRS1989

Toward improved durability in advanced aircraft engine hot sections

Advanced aircraft turbine engine durability needs were addressed in the NASA sponsored Hot Section Technology (HOST) Project. The seven-year project, which was concluded in late 1987, involved representatives from six engineering disciplines who were spread across three work sectors. To address more fully the technology needs resulting from durability challenges, the NASA Lewis Research Center encouraged researchers from the disciplines of instrumentation, combustion, turbine heat transfer, structural analysis, fatigue and fracture, and surface protection to work together, and prompted both basic and applications-oriented research within each of the six disciplines. This involved scientists and engineers from three work sectors: academia, where significant basic research usually is performed; industry, where research as well as applications work is addressed; and NASA, which supports both basic and applications research and has the resources to link the other two sectors. Research results from the HOST project have been reported in approximately 250 technical reports. The ASME 33rd International Gas Turbine and Aeroengine Congress and Exposition, conducted in June 1988, provided a timely and most appropriate forum in which to summarize such research results. The one-day session entitled “Toward Improved Durability in Advanced Aircraft Engine Hot Sections” and this volume of the session’s papers is the result.

Turbine engine↗

NASA NTRS1981

Disturbance estimation for a STOL transport during landing

Transport aircraft can experience dangerously high sink rates if wind shear or thrust loss are encountered during landing approach. This is of special concern for STOL aircraft that use engine thrust for lift augmentation. Such conditions must be detected quickly and available power increased promptly to avoid serious flight path deviations. This study demonstrates the feasibility of designing constant-gain estimators, which use on-board instrumentation, to detect such conditions with sufficient speed and accuracy to provide adequate warning. Estimator design techniques are discussed and simulation results presented.

Bossi, J. A.↗

NASA NTRS2013

Creep and Environmental Durability of EBC/CMCs Under Imposed Thermal Gradient Conditions

Interest in SiC fiber-reinforced SiC ceramic matrix composite (CMC) environmental barrier coating (EBC) systems for use in high temperature structural applications has prompted the need for characterization of material strength and creep performance under complex aerospace turbine engine environments. Stress-rupture tests have been performed on SiC/SiC composites systems, with varying fiber types and coating schemes to demonstrate material behavior under isothermal conditions. Further testing was conducted under exposure to thermal stress gradients to determine the effect on creep resistance and material durability. In order to understand the associated damage mechanisms, emphasis is placed on experimental techniques as well as implementation of non-destructive evaluation; including electrical resistivity monitoring. The influence of environmental and loading conditions on life-limiting material properties is shown.

Appleby, Matthew↗

NASA NTRS1993

An expert system shell for inferring vegetation characteristics: Interface for the addition of techniques (Task H)

All the NASA VEGetation Workbench (VEG) goals except the Learning System provide the scientist with several different techniques. When VEG is run, rules assist the scientist in selecting the best of the available techniques to apply to the sample of cover type data being studied. The techniques are stored in the VEG knowledge base. The design and implementation of an interface that allows the scientist to add new techniques to VEG without assistance from the developer were completed. A new interface that enables the scientist to add techniques to VEG without assistance from the developer was designed and implemented. This interface does not require the scientist to have a thorough knowledge of Knowledge Engineering Environment (KEE) by Intellicorp or a detailed knowledge of the structure of VEG. The interface prompts the scientist to enter the required information about the new technique. It prompts the scientist to enter the required Common Lisp functions for executing the technique and the left hand side of the rule that causes the technique to be selected. A template for each function and rule and detailed instructions about the arguments of the functions, the values they should return, and the format of the rule are displayed. Checks are made to ensure that the required data were entered, the functions compiled correctly, and the rule parsed correctly before the new technique is stored. The additional techniques are stored separately from the VEG knowledge base. When the VEG knowledge base is loaded, the additional techniques are not normally loaded. The interface allows the scientist the option of adding all the previously defined new techniques before running VEG. When the techniques are added, the required units to store the additional techniques are created automatically in the correct places in the VEG knowledge base. The methods file containing the functions required by the additional techniques is loaded. New rule units are created to store the new rules. The interface that allow the scientist to select which techniques to use is updated automatically to include the new techniques. Task H was completed. The interface that allows the scientist to add techniques to VEG was implemented and comprehensively tested. The Common Lisp code for the Add Techniques system is listed in Appendix A.

Harrison, P. Ann↗

NASA NTRSDate not supplied

A Comparison of Model Predictive Control Architectures for Application to Electrified Aircraft Propulsion Systems

As electrified aircraft propulsion (EAP) systems continue to mature, more sophisticated hardware and software are being developed to balance operations among electric machines and gas-turbine engines. In hybrid-electric propulsion systems, the increased complexity resulting from integrating turbine-engine shafts with electric machines necessitates control methodologies to account for various physical domains. Ideal controllers for hybrid-electric engines manage systems, subsystems, and their interactions in a coordinated fashion, able to account for safety and performance goals while being computationally efficient. In a previous work, linear model predictive control (MPC) schemes were implemented in centralized and distributed frameworks on a nonlinear turbofan engine model as a proof of concept. However, these schemes were not evaluated for computational complexity, prompting further study. The research presented here develops hierarchical MPC schemes to reduce the computational burden of the previous MPC schemes. A two-tier framework is implemented, where a slower sampling MPC controls electric machines and determines fan-speed tracking goals for a faster sampling controller, which is either a MPC or a proportional-integral (PI) controller. The proposed designs are compared to the centralized MPC investigated previously, and performance is measured via fan speed tracking error, energy storage state-of-charge, and computation time. Results reveal that the hierarchical MPC scheme employing a lower-level PI controller improves computation time while maintaining comparable tracking and state-of-charge regulation to the centralized scheme.

model predictive control↗

NASA NTRSDate not supplied

A Comparison of Model Predictive Control Architectures for Application to Electrified Aircraft Propulsion Systems

As electrified aircraft propulsion (EAP) systems continue to mature, more sophisticated hardware and software are being developed to balance operations among electric machines and gas-turbine engines. In hybrid-electric propulsion systems, the increased complexity resulting from integrating turbine-engine shafts with electric machines necessitates control methodologies to account for various physical domains. Ideal controllers for hybrid-electric engines manage systems, subsystems, and their interactions in a coordinated fashion, able to account for safety and performance goals while being computationally efficient. In a previous work, linear model predictive control (MPC) schemes were implemented in centralized and distributed frameworks on a nonlinear turbofan engine model as a proof of concept. However, these schemes were not evaluated for computational complexity, prompting further study. The research presented here develops hierarchical MPC schemes to reduce the computational burden of the previous MPC schemes. A two-tier framework is implemented, where a slower sampling MPC controls electric machines and determines fan-speed tracking goals for a faster sampling controller, which is either a MPC or a proportional-integral (PI) controller. The proposed designs are compared to the centralized MPC investigated previously, and performance is measured via fan speed tracking error, energy storage state-of-charge, and computation time. Results reveal that the hierarchical MPC scheme employing a lower-level PI controller improves computation time while maintaining comparable tracking and state-of-charge regulation to the centralized scheme.

model predictive control↗