When modeling a stealth aircraft with low RCS（Radar Cross Section）, conventional parameter estimation methods may cause a deviation from the actual distribution, owing to the fact that the characteristic parameters ...When modeling a stealth aircraft with low RCS（Radar Cross Section）, conventional parameter estimation methods may cause a deviation from the actual distribution, owing to the fact that the characteristic parameters are estimated via directly calculating the statistics of RCS. The Bayesian–Markov Chain Monte Carlo（Bayesian-MCMC） method is introduced herein to estimate the parameters so as to improve the fitting accuracies of fluctuation models. The parameter estimations of the lognormal and the Legendre polynomial models are reformulated in the Bayesian framework. The MCMC algorithm is then adopted to calculate the parameter estimates. Numerical results show that the distribution curves obtained by the proposed method exhibit improved consistence with the actual ones, compared with those fitted by the conventional method. The fitting accuracy could be improved by no less than 25% for both fluctuation models, which implies that the Bayesian-MCMC method might be a good candidate among the optimal parameter estimation methods for stealth aircraft RCS models.展开更多
Based on computational fluid dynamics （CFD）/computational eleetromagnetics method （CEM） coupling method and surrogate model optimization techniques, an integration design method about aerodynamic/stealth character...Based on computational fluid dynamics （CFD）/computational eleetromagnetics method （CEM） coupling method and surrogate model optimization techniques, an integration design method about aerodynamic/stealth characteristics of airfoil is established. The O-type body-fitted and orthogonal grid around airfoil is first generated by using the Poisson equations, in which the points per wave and the normal range satisfy the aerodynamic and electromagnetic calculation accuracy requirement. Then the aerodynamic performance of airfoil is calculated by sol- ving the Navier-Stokes （N-S） equations with Baldwin-Lomax （B-L） turbulence model. The stealth characteristics of airfoil are simulated by using finite volume time domain （FVTD） method based on the Maxwell＇s equations, Steger-Warming flux splitting and the third-order MUSCL scheme. In addition, based upon the surrogate model optimization technique with full factorial design （FFD） and radial basis function （RBF）, an integration design about aerodynamic/stealth characteristics of rotor airfoil is conducted by employing the CFD/CEM coupling meth- od. The aerodynamic/stealth characteristics of NACA series airfoils with different maximum thickness and camber combinations are discussed. Finally, by choosing suitable lift-to-drag ratio and radar cross section （RCS） ampli- tudes of rotor airfoil in four important scattering regions as the objective function and constraint, the compromised airfoil with high lift-to-drag ratio and low scattering characteristics is designed via systemic and comprehensive ana- lyses.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61101173)the National Basic Research Program of China(Grant No.613206)+1 种基金the National High Technology Research and Development Program of China(Grant No.2012AA01A308)the State Scholarship Fund by the China Scholarship Council(CSC),and the Oversea Academic Training Funds,and University of Electronic Science and Technology of China(UESTC)
文摘When modeling a stealth aircraft with low RCS（Radar Cross Section）, conventional parameter estimation methods may cause a deviation from the actual distribution, owing to the fact that the characteristic parameters are estimated via directly calculating the statistics of RCS. The Bayesian–Markov Chain Monte Carlo（Bayesian-MCMC） method is introduced herein to estimate the parameters so as to improve the fitting accuracies of fluctuation models. The parameter estimations of the lognormal and the Legendre polynomial models are reformulated in the Bayesian framework. The MCMC algorithm is then adopted to calculate the parameter estimates. Numerical results show that the distribution curves obtained by the proposed method exhibit improved consistence with the actual ones, compared with those fitted by the conventional method. The fitting accuracy could be improved by no less than 25% for both fluctuation models, which implies that the Bayesian-MCMC method might be a good candidate among the optimal parameter estimation methods for stealth aircraft RCS models.
文摘Based on computational fluid dynamics （CFD）/computational eleetromagnetics method （CEM） coupling method and surrogate model optimization techniques, an integration design method about aerodynamic/stealth characteristics of airfoil is established. The O-type body-fitted and orthogonal grid around airfoil is first generated by using the Poisson equations, in which the points per wave and the normal range satisfy the aerodynamic and electromagnetic calculation accuracy requirement. Then the aerodynamic performance of airfoil is calculated by sol- ving the Navier-Stokes （N-S） equations with Baldwin-Lomax （B-L） turbulence model. The stealth characteristics of airfoil are simulated by using finite volume time domain （FVTD） method based on the Maxwell＇s equations, Steger-Warming flux splitting and the third-order MUSCL scheme. In addition, based upon the surrogate model optimization technique with full factorial design （FFD） and radial basis function （RBF）, an integration design about aerodynamic/stealth characteristics of rotor airfoil is conducted by employing the CFD/CEM coupling meth- od. The aerodynamic/stealth characteristics of NACA series airfoils with different maximum thickness and camber combinations are discussed. Finally, by choosing suitable lift-to-drag ratio and radar cross section （RCS） ampli- tudes of rotor airfoil in four important scattering regions as the objective function and constraint, the compromised airfoil with high lift-to-drag ratio and low scattering characteristics is designed via systemic and comprehensive ana- lyses.
