Sonic boom reduction will be an issue of utmost importance in future supersonic trans-port, due to strong regulations on acoustic nuisance. The paper describes a new multi-objective optimization method for supersonic ...Sonic boom reduction will be an issue of utmost importance in future supersonic trans-port, due to strong regulations on acoustic nuisance. The paper describes a new multi-objective optimization method for supersonic aircraft design. The method is developed by coupling Seebass-George-Darden （SGD） inverse design method and multi-objective genetic algorithm. Based on the method, different codes are developed. Using a computational architecture, a concep-tual supersonic aircraft design environment （CSADE） is constructed. The architecture of CSADE includes inner optimization level and out optimization level. The low boom configuration is gener-ated in inner optimization level by matching the target equivalent area distribution and actual equivalent area distribution. And low boom/low drag configuration is generated in outer optimiza-tion level by using NSGA-II multi-objective genetic algorithm to optimize the control parameters of SGD method and aircraft shape. Two objective functions, low sonic boom and low wave drag, are considered in CSADE. Physically reasonable Pareto solutions are obtained from the present optimization. Some supersonic aircraft configurations are selected from Pareto front and the optimization results indicate that the swept forward wing configuration has benefits in both sonic boom reduction and wave drag reduction. The results are validated by using computational fluid dynamics （CFD） analysis.展开更多
Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor （HRM） powered vehicle. The multidisciplinary design model of the rocket system ...Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor （HRM） powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization （DDO） and uncertainty-based design optimization （UDO） are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation （KMCS） and Kriging-based Taylor series approximation （KTSA）, are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods： DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.展开更多
The reliability-based design optimization, the reliability sensitivity analysis and robust design method are employed to present a practical and effective approach for reliability-based robust design optimization of v...The reliability-based design optimization, the reliability sensitivity analysis and robust design method are employed to present a practical and effective approach for reliability-based robust design optimization of vehicle components. A procedure for reliability-based robust design optimization of vehicle components is proposed. Application of the method is illustrated by reliability-based robust design optimization of axle and spring. Numerical results have shown that the proposed method can be trusted to perform reliability-based robust design optimization of vehicle components.展开更多
基金supported by the Doctorate Foundation of Northwestern Polytechnical University (CX-201232)
文摘Sonic boom reduction will be an issue of utmost importance in future supersonic trans-port, due to strong regulations on acoustic nuisance. The paper describes a new multi-objective optimization method for supersonic aircraft design. The method is developed by coupling Seebass-George-Darden （SGD） inverse design method and multi-objective genetic algorithm. Based on the method, different codes are developed. Using a computational architecture, a concep-tual supersonic aircraft design environment （CSADE） is constructed. The architecture of CSADE includes inner optimization level and out optimization level. The low boom configuration is gener-ated in inner optimization level by matching the target equivalent area distribution and actual equivalent area distribution. And low boom/low drag configuration is generated in outer optimiza-tion level by using NSGA-II multi-objective genetic algorithm to optimize the control parameters of SGD method and aircraft shape. Two objective functions, low sonic boom and low wave drag, are considered in CSADE. Physically reasonable Pareto solutions are obtained from the present optimization. Some supersonic aircraft configurations are selected from Pareto front and the optimization results indicate that the swept forward wing configuration has benefits in both sonic boom reduction and wave drag reduction. The results are validated by using computational fluid dynamics （CFD） analysis.
基金supported by the National Natural Science Foundation of China(No.51305014)China Postdoctoral Science Foundation(No.2013M540842)
文摘Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor （HRM） powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization （DDO） and uncertainty-based design optimization （UDO） are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation （KMCS） and Kriging-based Taylor series approximation （KTSA）, are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods： DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.
文摘The reliability-based design optimization, the reliability sensitivity analysis and robust design method are employed to present a practical and effective approach for reliability-based robust design optimization of vehicle components. A procedure for reliability-based robust design optimization of vehicle components is proposed. Application of the method is illustrated by reliability-based robust design optimization of axle and spring. Numerical results have shown that the proposed method can be trusted to perform reliability-based robust design optimization of vehicle components.
