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Aerodynamic Optimization of Turbine Based Combined Cycle Nozzle
Abstract
This paper aims at optimizing a Turbine Based Combined Cycle (TBCC) nozzle for upgrading its aerodynamic performance in multiple flight conditions. An in-house RANS solver called NSAWET is employed for aerodynamic evaluation. The optimizer is a differential evolution algorithm combined with a response surface. Firstly, a two-dimensional model of the initial TBCC nozzle system is investigated. The flow field of the nozzle contains complicated shockwave interactions that cause thrust loss. Then multi-point aerodynamic optimization of a two-dimensional ramjet nozzle is carried out, which objectives are to maximize the thrust coefficients at Mach numbers 2.5, 3.0 and 4.0. The objective functions are increased substantially at the first two Mach numbers after optimization, while slightly decreased at the last Mach number. The turbine flow path is built up based on the optimized profile and the performances in typical flight conditions are validated. Results demonstrate that both the ramjet and turbine nozzles are improved in most flight conditions.
A drag prediction method based on thrust drag bookkeeping (TDB) is introduced for civil jet propulsion/airframe integration performance analysis. The method is derived from the control volume theory of a powered-on nacelle. Key problem of the TDB is identified to be accurate prediction of velocity coefficient of the powered-on nacelle. Accuracy of CFD solver is validated by test cases of the first AIAA Propulsion Aerodynamics Workshop. Then the TDB method is applied to thrust and drag decomposing of a realistic aircraft. A linear relation between the computations assumed free stream Mach number and the velocity coefficient result is revealed. The thrust losses caused by nozzle internal drag and pylon scrubbing are obtained by the isolated nacelle and mapped on to the in-flight whole configuration analysis. Effects of the powered-on condition are investigated by comparing through-flow configuration with powered-on configuration. The variance on aerodynamic coefficients and pressure distribution is numerically studied.
An optimization design method of supercritical natural laminar flow airfoil based on Genetic Algorithm and Computational Fluid Dynamics is tested in this paper. Class Shape Transformation method is adopted as geometry parameterization method. Constraints on pressure distribution are applied to gain appropriate flow field in addition to the performance. A fixed transition computation method is used in the optimization process to save computation time while giving the reasonable friction drag estimation and predicting the influence of the laminar boundary layer on airfoil performances. Specified favorable pressure gradient constraints are used to guarantee the expected laminar length. Objective of optimization is set to weaken the shock wave and minimize the pressure drag. Such a simplified NLF optimization process is verified by natural transition computation. The optimal setting of the favorable pressure gradient constraint, which is important for the trade-off between drag reduction and laminar stability, is then studied via numerical investigation. Results show that the airfoil optimized by constraining a favorable pressure gradient larger than 0.2 is good for both cruise efficiency and robustness. A natural laminar wing is then designed based on the optimized airfoil. Numerical verifications show that the wing has good natural laminar performance and low speed behavior.
A new heuristic approach for minimizing possiblynonlinear and non-differentiable continuous spacefunctions is presented. By means of an extensivetestbed it is demonstrated that the new methodconverges faster and with more certainty than manyother acclaimed global optimization methods. The newmethod requires few control variables, is robust, easyto use, and lends itself very well to parallelcomputation.
