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  • air breathing engines  (1)
  • design optimization  (1)
  • Wiley-Blackwell  (2)
  • 1
    Electronic Resource
    Electronic Resource
    Chichester : Wiley-Blackwell
    Communications in Numerical Methods in Engineering 13 (1997), S. 635-641 
    ISSN: 1069-8299
    Keywords: design optimization ; air-breathing engine ; wave rotor ; multiflow turbofan engine ; Engineering ; Numerical Methods and Modeling
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Mathematics , Technology
    Notes: The design optimization of air-breathing propulsion engine concepts has been accomplished by soft-coupling the NASA Engine Performance Program (NEPP) analyser with the NASA Lewis multidisciplinary optimization tool COMETBOARDS. Engine problems, with their associated design variables and constraints, were cast as non-linear optimization problems with thrust as the merit function. Because of the large number of mission points in the flight envelope, the diversity of constraint types, and the overall distortion of the design space, the most reliable optimization algorithm available in COMETBOARDS, when used by itself, could not produce satisfactory, feasible, optimum solutions. However, COMETBOARDS' unique features-which include a cascade strategy, variable and constraint formulations, and scaling devised especially for difficult multidisciplinary applications-successfully optimized the performance of subsonic and supersonic engine concepts. Even when started from different design points, the combined COMETBOARDS and NEPP results converged to the same global optimum solution. This reliable and robust design tool eliminates manual intervention in the design of air-breathing propulsion engines and eases the cycle analysis procedures. It is also much easier to use than other codes, which is an added benefit. This paper describes COMETBOARDS and its cascade strategy and illustrates the capabilities of the combined design tool through the optimization of a high-bypass-turbofan wave-rotor-topped subsonic engine and a mixed-flow-turbofan supersonic engine. ©1997 John Wiley & Sons, Ltd.
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Chichester [u.a.] : Wiley-Blackwell
    International Journal for Numerical Methods in Engineering 40 (1997), S. 2257-2266 
    ISSN: 0029-5981
    Keywords: multiple optimizers ; cascade ; design ; aircraft ; air breathing engines ; Engineering ; Numerical Methods and Modeling
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Mathematics , Technology
    Notes: A research project to evaluate comparatively ten different non-linear optimization algorithms was completed recently. A conclusion was that no single optimizer could successfully solve all the 40 structural design problems in the test-bed, even though most optimizers successfully solved at least one-third of the problems. We realized that improvements to search directions and step lengths, available in the ten optimizers compared, were not likely to alleviate the convergence difficulties. For the solution of those difficult problems we have devised an alternate approach called, the cascade optimization strategy. The strategy utilizes several optimizers, one followed by another in a specified sequence, to solve a problem. A pseudo-random dumping scheme perturbs the design variables between the optimizers. The cascade strategy has been tested out successfully in the design of supersonic and subsonic aircraft configurations and air breathing engines for high-speed civil transport applications. These problems could not be successfully solved by an individual optimizer. The cascade optimization strategy, however, generated feasible optimum solutions for both aircraft and engine problems. This paper presents the cascade strategy, solution of aircraft and engine problems along with discussions and conclusions. © 1997 John Wiley & Sons, Ltd.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
    Location Call Number Limitation Availability
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