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The design practices for the gas turbine are traced throughout history with particular emphasis on the calculational or analytical methods. Three principal components of the gas turbine engine will be considered: namely, the compressor, the combustor and the turbine.
The design practices for the gas turbine are traced throughout history with particular emphasis on the calculational or analytical methods. Three principal components of the gas turbine engine will be considered: namely, the compressor, the combustor and the turbine.
The conceptual design for an improved gas turbine (IGT) powertrain and vehicle was investigated. Cycle parameters, rotor systems, and component technology were reviewed and a dual rotor gas turbine concept was selected and optimized for best vehicle fuel economy. The engine had a two stage centrifugal compressor with a design pressure ratio of 5.28, two axial turbine stages with advanced high temperature alloy integral wheels, variable power turbine nozzle for turbine temperature and output torque control, catalytic combustor, and annular ceramic recuperator. The engine was rated at 54.81 kW, using water injection on hot days to maintain vehicle acceleration. The estimated vehicle fuel economy was 11.9 km/l in the combined driving cycle, 43 percent over the 1976 compact automobile. The estimated IGT production vehicle selling price was 10 percent over the comparable piston engine vehicle, but the improved fuel economy and reduced maintenance and repair resulted in a 9 percent reduction in life cycle cost.
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.
The reduction of oxides of nitrogen (NO(x)) emissions from aircraft gas turbine engines is a vital part of the NASA High Speed Research Program. Emissions reductions are critical to the feasibility of future High Speed Civil Transports which operate at supersonic speeds in the stratosphere. It is believed that large fleets of such aircraft using conventional gas turbine engines would emit levels of NO(x) that would be harmful to the stratospheric ozone layer. Previous studies have shown that NO(x) emissions can be reduced from stationary powerplant exhausts by the addition of additives such as ammonia to the exhaust gases. Since the exhaust residence times, pressures and temperatures may be different for aircraft gas turbines, a study has been made of additive effectiveness for high speed, high altitude flight.
Heat transfer coefficient and static pressure distributions are experimentally investigated on a gas turbine blade tip in a five-bladed stationary linear cascade. The blade is a 2-dimensional model of a first stage gas turbine rotor blade with a blade tip profile of a GE-E(sup 3) aircraft gas turbine engine rotor blade. The flow condition in the test cascade corresponds to an overall pressure ratio of 1.32 and exit Reynolds number based on axial chord of 1.1 x 10(exp 6). The middle 3-blade has a variable tip gap clearance. All measurements are made at three different tip gap clearances of about 1%, 1.5%, and 2.5% of the blade span. Heat transfer measurements are also made at two different turbulence intensity levels of 6.1 % and 9.7% at the cascade inlet. Static pressure measurements are made in the mid-span and the near-tip regions as well as on the shroud surface, opposite the blade tip surface. Detailed heat transfer coefficient distributions on the plane tip surface are measured using a transient liquid crystal technique. Results show various regions of high and low heat transfer coefficient on the tip surface. Tip clearance has a significant influence on local tip beat transfer coefficient distribution. Heat transfer coefficient also increases about 15-20% along the leakage flow path at higher turbulence intensity level of 9.7% over 6.1 %.
The AGT101 ceramic gas turbine engine feasibility study has made use of the slip casting of silicon or silicon nitride powders to produce either reaction-bonded or sintered components such as turbine rotors, turbine shrouds, and inner and outer diffusers. Attention is given to the effects of processing parameters on the microstructure and properties of the finished components; the parameters encompass powder particle size distribution, casting slip viscosity, pH, and solid content fraction. The green slip cast components were consolidated by nitriding, sintering, or sinter/HIPping.
Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.
Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.
Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.
Results were arrived at by utilizing and expanding on information presented in the literature. The results were analyzed and compared with those for simple gas turbine and combined cycles for both utility power generation and industrial cogeneration applications. The efficiency and specific power of simple gas turbine cycles can be increased as much as 30 and 50 percent, respectively, by the injection of steam into the combustor. Steam-injected gas turbines appear to be economically competitive with both simple gas turbine and combined cycles for small, clean-fuel-fired utility power generation and industrial cogeneration applications. For large powerplants with integrated coal gasifiers, the economic advantages appear to be marginal.
A fuel control system is reported for automotive-type gas turbines and particulary advanced gas turbines utilizing variable geometry components to improve mileage and reduce pollution emission. The fuel control system compensates for fuel density variations, inlet temperature variations, turbine vane actuation, acceleration, and turbine braking. These parameters are utilized to control various orifices, spool valves and pistons.
Heat tranfer problems in aircraft gas turbines required for improved prediction of turbine blade or vane gas-side heat transfer are examined. Estimates of the heat transfer from the gas to vanes or rotating blades are uncertain due to the complexity of the heat transfer processes, since the gas flow is three dimensional with complex secondary viscous flow patterns that interact with the endwalls and blade surfaces. In addition, upstream disturbances, stagnation flow, curvature effects, and flow acceleration complicate the thermal transport mechanisms in the boundary layers. The thermal state and flow characteristics of the hot gases that enter the turbine blade row, analytical methods for calculating the gas-side heat transfer to turbine blades, and flow phenomena such as stagnation, curvature effects, acceleration, secondary flows, and transition that influences local heat transfer rates are discussed.
Cooling Flow Reduction: a) Focus on improving turbine hot gas path part cooling efficiency. b) Applicable to current metallic turbine components and synergistic with advanced materials. c) Address challenges of IGCC/hydrogen fuel environment (for example, possible cooling hole plugging). Leakage Flow Reduction: a) Focus on decreasing turbine parasitic leakages, i.e. between static-to-static, static-to-rotating turbine parts. b) Develop improved seal designs in a variety of important areas. Purge Flow Reduction: a) Focus on decreasing required flows to keep rotor disk cavities within temperature limits. b) Develop improved sealing at the cavity rims and modified flow geometries to minimize hot gas ingestion and aerodynamic impact.
An analysis was developed for calculating the radial temperature distribution in a gas turbine with only the temperatures of the gas and the cooling air and the surface heat-transfer coefficient known. This analysis was applied to determine the temperatures of a complete wheel of a conventional single-stage impulse exhaust-gas turbine. The temperatures were first calculated for the case of the turbine operating at design conditions of speed, gas flow, etc. and with only the customary cooling arising from exposure of the outer blade flange and one face of the rotor to the air. Calculations were next made for the case of fins applied to the outer blade flange and the rotor. Finally the effects of using part of the nozzles (from 0 to 40 percent) for supplying cooling air and the effects of varying the metal thermal conductivity from 12 to 260 Btu per hour per foot per degree Farenheit on the wheel temperatures were determined. The gas temperatures at the nozzle box used in the calculations ranged from 1600F to 2000F. The results showed that if more than a few hundred degrees of cooling of turbine blades are required other means than indirect cooling with fins on the rotor and outer blade flange would be necessary. The amount of cooling indicated for the type of finning used could produce some improvement in efficiency and a large increase in durability of the wheel. The results also showed that if a large difference is to exist between the effective temperature of the exhaust gas and that of the blade material, as must be the case with present turbine materials and the high exhaust-gas temperatures desired (2000F and above), two alternatives are suggested: (a) If metal with a thermal conductivity comparable with copper is used, then the blade temperature can be reduced by strong cooling at both the blade tip and root. The center of the blade will be less than 2000F hotter than the ends; (b) With low conductivity materials some method of direct cooling other than partial admission of cooling air is essential. From this study, it can be deduced that indirect cooling of turbine blades will not make possible large increases in gas temperature.
The present conference on durability improvement methods for advanced aircraft gas turbine hot-section components discusses NASA's 'HOST' project, advanced high-temperature instrumentation for hot-section research, the development and application of combustor aerothermal models, and the evaluation of a data base and numerical model for turbine heat transfer. Also discussed are structural analysis methods for gas turbine hot section components, fatigue life-prediction modeling for turbine hot section materials, and the service life modeling of thermal barrier coatings for aircraft gas turbine engines.
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In a continuing program of research and development, a system has been demonstrated that makes high-speed measurements of thermal infrared radiance from gas-turbine engine exhaust streams. When a gas-turbine engine is operated under conditions that minimize the emission of pollutants, there is a risk of crossing the boundary from stable to unstable combustion. Combustion instability can lead to engine damage and even catastrophic failure. Sensor systems of the type under development could provide valuable data during the development testing of gas-turbine engines or of engine components. A system of the type under development makes high-speed measurements of thermal infrared radiance from the engine exhaust stream. The sensors of this system can be mounted outside the engine, which eliminates the need for engine case penetrations typical with other engine dynamics monitors. This is an important advantage in that turbine-engine manufacturers consider such penetrations to be very undesirable. A prototype infrared sensor system has been built and demonstrated on a turbine engine. This system includes rugged and inexpensive near-infrared sensors and filters that select wavelengths of infrared radiation for high sensitivity. In experiments, low-frequency signatures were consistently observed in the detector outputs. Under some conditions, the signatures also included frequency components having one or two radiance cycles per engine revolution. Although it has yet to be verified, it is thought that the low-frequency signatures may be associated with bulk-mode combustion instabilities or flow instabilities in the compressor section of the engine, while the engine- revolution-related signatures may be indicative of mechanical problems in the engine. The system also demonstrated the ability to detect transient high-radiance events. These events indicate hot spots in the exhaust stream and were found to increase in frequency during engine acceleration.