Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters.This paper presents a hybrid uncertainty-based design o...Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters.This paper presents a hybrid uncertainty-based design optimization（UDO） method developed from probability theory and interval theory.Most of the uncertain design parameters which have sufficient information or experimental data are classified as random variables using probability theory,while the others are defined as interval variables with interval theory.Then a hybrid uncertainty analysis method based on Monte Carlo simulation and Taylor series interval analysis is developed to obtain the uncertainty propagation from the design parameters to system responses.Three design optimization strategies,including deterministic design optimization（DDO）,probabilistic UDO and hybrid UDO,are applied to the conceptual design of a hybrid rocket motor（HRM） used as the ascent propulsion system in Apollo lunar module.By comparison,the hybrid UDO is a feasible method and can be effectively applied to the general design of aerospace systems.展开更多
With the increasing demands of aircraft design,the traditional deterministic design can hardly meet the requirements of fine design optimization because uncertainties may exist throughout the whole lifecycle of the ai...With the increasing demands of aircraft design,the traditional deterministic design can hardly meet the requirements of fine design optimization because uncertainties may exist throughout the whole lifecycle of the aircraft. To enhance the robustness and reliability of the aircraft design, Uncertainty Multidisciplinary Design Optimization( UM DO) has been developing for a long time. This paper presents a comprehensive reviewof UM DO methods for aerospace vehicles,including basic UM DO theory and research progress of its application in aerospace vehicle design. Firstly,the UM DO theory is preliminarily introduced,with giving the definition and classification of uncertainty as well as its sources corresponding to the aircraft design. Then following the UM DO solving process, the application in different coupled disciplines is separately discussed during the aircraft design process,specifically clarifying the UM DO methods for aerostructural optimization. Finally,the main challenges of UM DO and the future research trends are given.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
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
In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket M...In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket Motor (HRM) powered Launch Vehicle (LV).In the method proposed,membership functions are used to represent the uncertain factors,the fuzzy statistical experiment is introduced to analyze the propagation of uncertainties,and means,standard deviations and credibility measures are used to delineate uncertain responses.A geometric programming problem is solved to verify the feasibility of the Fuzzy-based Multi-Discipline Feasible(F-MDF) method.A multi-disciplinary analysis of a three-stage HRM powered LV involving the disciplines of propulsion,structure,aerodynamics and trajectory is implemented,and the mathematical models corresponding to the F-MDF method and the MDF method are established.A two-phase optimization method is proposed for multi-disciplinary design optimization of the LV,including the orbital capacity optimization phase based on the Ziolkowski formula,and the scheme trajectory verification phase based on the 3-degree-of-freedom point trajectory simulation.The correlation coefficients and the quadratic Response Surface Method (RSM) based on Latin Hypercube Sampling (LHS) are adopted for sensitive analysis of uncertain factors,and the Multi-Island Genetic Algorithm (MIGA) is adopted as the optimization algorithm.The results show that the F-MDF method is applicable in LV conceptual design,and the design with the F-MDF method is more reliable and robust than that with the MDF method.展开更多
基金supported by the National Natural Science Foundation of China(No.51305014)
文摘Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters.This paper presents a hybrid uncertainty-based design optimization（UDO） method developed from probability theory and interval theory.Most of the uncertain design parameters which have sufficient information or experimental data are classified as random variables using probability theory,while the others are defined as interval variables with interval theory.Then a hybrid uncertainty analysis method based on Monte Carlo simulation and Taylor series interval analysis is developed to obtain the uncertainty propagation from the design parameters to system responses.Three design optimization strategies,including deterministic design optimization（DDO）,probabilistic UDO and hybrid UDO,are applied to the conceptual design of a hybrid rocket motor（HRM） used as the ascent propulsion system in Apollo lunar module.By comparison,the hybrid UDO is a feasible method and can be effectively applied to the general design of aerospace systems.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.303QKJJ2016105002 and 30300002014105011)
文摘With the increasing demands of aircraft design,the traditional deterministic design can hardly meet the requirements of fine design optimization because uncertainties may exist throughout the whole lifecycle of the aircraft. To enhance the robustness and reliability of the aircraft design, Uncertainty Multidisciplinary Design Optimization( UM DO) has been developing for a long time. This paper presents a comprehensive reviewof UM DO methods for aerospace vehicles,including basic UM DO theory and research progress of its application in aerospace vehicle design. Firstly,the UM DO theory is preliminarily introduced,with giving the definition and classification of uncertainty as well as its sources corresponding to the aircraft design. Then following the UM DO solving process, the application in different coupled disciplines is separately discussed during the aircraft design process,specifically clarifying the UM DO methods for aerostructural optimization. Finally,the main challenges of UM DO and the future research trends are given.
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.
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 National Natural Science Foundation of China (No. 51305014)
文摘In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket Motor (HRM) powered Launch Vehicle (LV).In the method proposed,membership functions are used to represent the uncertain factors,the fuzzy statistical experiment is introduced to analyze the propagation of uncertainties,and means,standard deviations and credibility measures are used to delineate uncertain responses.A geometric programming problem is solved to verify the feasibility of the Fuzzy-based Multi-Discipline Feasible(F-MDF) method.A multi-disciplinary analysis of a three-stage HRM powered LV involving the disciplines of propulsion,structure,aerodynamics and trajectory is implemented,and the mathematical models corresponding to the F-MDF method and the MDF method are established.A two-phase optimization method is proposed for multi-disciplinary design optimization of the LV,including the orbital capacity optimization phase based on the Ziolkowski formula,and the scheme trajectory verification phase based on the 3-degree-of-freedom point trajectory simulation.The correlation coefficients and the quadratic Response Surface Method (RSM) based on Latin Hypercube Sampling (LHS) are adopted for sensitive analysis of uncertain factors,and the Multi-Island Genetic Algorithm (MIGA) is adopted as the optimization algorithm.The results show that the F-MDF method is applicable in LV conceptual design,and the design with the F-MDF method is more reliable and robust than that with the MDF method.
