Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight

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 analysis 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.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 analysis 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.     

Performance evaluation of complex systems using evidential reasoning approach with uncertain parameters

The composition of the modern aerospace system becomes more and more complex. The performance degradation of any device in the system may cause it difficult for the whole system to keep normal working states. Therefore, it is essential to evaluate the performance of complex aerospace systems. In this paper, the performance evaluation of complex aerospace systems is regarded as a Multi-Attribute Decision Analysis (MADA) problem. Based on the structure and working principle of the system, a new Evidential Reasoning (ER) based approach with uncertain parameters is proposed to construct a nonlinear optimization model to evaluate the system performance. In the model, the interval form is used to express the uncertainty, such as error in testing data and inaccuracy in expert knowledge. In order to analyze the subsystems that have a great impact on the performance of the system, the sensitivity analysis of the evaluation result is carried out, and the corresponding maintenance strategy is proposed. For a type of Inertial Measurement Unit (IMU) used in a rocket, the proposed method is employed to evaluate its performance. Then, the parameter sensitivity of the evaluation result is analyzed, and the main factors affecting the performance of IMU are obtained. Finally, the comparative study shows the effectiveness of the proposed method.     

基于自适应模糊系统的空天飞行器非线性预测控制

 针对一类多输入多输出非线性不确定系统,提出了基于自适应模糊系统的非线性预测控制方法。控制器由基于模糊系统的非线性预测控制器和鲁棒自适应控制器两个部分组成。根据系统的跟踪误差在线调整模糊系统的权值,使得模糊系统一致逼近被控对象中的非线性函数,通过泰勒展开设计出基于模糊系统的非线性预测控制律,避免了预测控制在线优化带来的繁重的计算负担。鲁棒自适应控制器则用于减少不确定和模糊逼近误差对系统的影响。所设计的控制器保证了闭环系统的最终一致有界稳定。基于Lyapunov稳定原理,给出了理论证明和分析。最后利用提出的控制方案设计了空天飞行器高超声速飞行姿态的控制系统,仿真结果表明了控制方案的有效性。     

Index allocation for a reusable LOX/CH4 rocket engine

Reusable rocket engines are the core components of reusable launch vehicles, and have thus become a major focus of aerospace engineering research in recent years. In practice, subsystem design is based on the overall index allocation of an engine; therefore, a multidisciplinary optimization approach is necessary. In this study, design of a reusable methane/liquid oxygen (LOX/CH4) rocket engine with a gas generator cycle was investigated using multidisciplinary optimization. Two parameters were chosen as design variables: pressure and fuel mix ratio of the main combustion chamber. Optimization objectives were specific impulse, structural mass, and life cycle cost of the reusable rocket engine, and constraints were assigned to each discipline according to rocket design requirements. Then, an optimization model was developed, and optimal design parameters were acquired for the LOX/CH4 rocket engine. The proposed method is effective for designing the index allocation of reusable rocket engines and takes into account the multidisciplinary nature of complex systems.     

ABCLS method for high-reliability aerospace mechanism with truncated random uncertainties

The random variables are always truncated in aerospace engineering and the truncated distribution is more feasible and effective for the random variables due to the limited samples available.For high-reliability aerospace mechanism with truncated random variables, a method based on artificial bee colony(ABC) algorithm and line sampling(LS) is proposed.The artificial bee colony-based line sampling(ABCLS) method presents a multi-constrained optimization model to solve the potential non-convergence problem when calculating design point(is also as most probable point, MPP) of performance function with truncated variables; by implementing ABC algorithm to search for MPP in the standard normal space, the optimization efficiency and global searching ability are increased with this method dramatically.When calculating the reliability of aerospace mechanism with too small failure probability, the Monte Carlo simulation method needs too large sample size.The ABCLS method could overcome this drawback.For reliability problems with implicit functions, this paper combines the ABCLS with Kriging response surface method,therefore could alleviate computational burden of calculating the reliability of complex aerospace mechanism.A numerical example and an engineering example are carried out to verify this method and prove the applicability.     

基于重要性测度降维的液压管路稳健优化设计

提出一种基于重要性测度的降维预处理优化方法,对不确定环境下飞机局部液压管路系统的稳健性优化问题展开研究。引入区间模型描述随机变量分布参数（即设计变量）的不确定性,引入基于方差的重要性测度衡量设计变量对优化目标的贡献程度,从而筛选出对优化目标影响较大的设计变量,简化优化模型。该方法可以有效降低优化问题的维数,进而减少优化的计算成本。通过数值算例验证了所提方法的合理性和可行性,并采用该方法对飞机局部液压管路系统进行了稳健性优化设计。     

Aerodynamic optimization of re-entry capsules

Methods for aerodynamic design and optimization based on linear theory are not well suited for modelling non-linear phenomenons. Their results only represent approximations of real optima. In the present study a new method based on non-linear theory, i.e. the solution of the Euler/Navier–Stokes equations, has been applied to improve these approximations. The structure of the system as well as the incorporated modules are described. Aerodynamic optimizations of a biconic re-entry capsule with respect to the lift-to-drag ratio, the effective volume and the stability are presented and discussed. The method proves to be a robust and relative efficient tool for aerodynamic design of modern aerospace vehicles. An increase in the performance of computer systems will result in an increase in the efficiency as well. It is shown that the method keeps and sometimes expands the established knowledge base of experienced engineers but reduces the design cycle times significantly.     

Multi-scale design and optimization for solid-lattice hybrid structures and their application to aerospace vehicle components

By integrating topology optimization and lattice-based optimization, a novel multi-scale design method is proposed to create solid-lattice hybrid structures and thus to improve the mechanical performance as well as reduce the structural weight. To achieve this purpose, a two-step procedure is developed to design and optimize the innovative structures. Initially, the classical topology optimization is utilized to find the optimal material layout and primary load carrying paths. Afterwards, the solid-lattice hybrid structures are reconstructed using the finite element mesh based modeling method. And lattice-based optimization is performed to obtain the optimal cross-section area of the lattice structures. Finally, two typical aerospace structures are optimized to demonstrate the effectiveness of the proposed optimization framework. The numerical results are quite encouraging since the solid-lattice hybrid structures obtained by the presented approach show remarkably improved performance when compared with traditional designs.     

基于六西格玛设计及改进遗传算法的直升机优化设计

本文研究了六西格玛设计方法和改进的遗传算法,并应用该设计方法对直升机总体参数进行了优化设计。采用优化设计后获得的直升机设计方案,由于受许多不确定性因素的影响,最后付诸实现时并不能保证得到像预先优化设计方案那样的结果。在改进的遗传算法实现最优化设计的同时进行六西格玛设计,可提高优化设计结果的可靠性和鲁棒性。本文以CH-47D纵列式直升机为优化算例,优化效果良好,结果可靠,表明本文方法切实可行。     

航空发动机套齿动态装配间隙非概率优化设计

为解决航空发动机套齿动态装配间隙的响应问题,在考虑动态变形和参数不确定性的情况下,将1种非概率区间分析方法与Kriging响应面模型及响应面优化方法相结合,对套齿初始装配间隙进行了可靠性优化设计。以某刚性套齿联轴器作为数值算例,在确定性设计的基础上,考虑机械载荷、热载荷、材料参数的分散性,运用区间分析方法得到了动态装配间隙的响应范围,利用非概率可靠性指标对初始装配间隙进行了优化设计。与确定性设计相比,优化设计提高了结构的可靠性;与概率设计相比,优化设计降低了对不确定参数的信息要求。验证了非概率方法解决装配对象不确定性结构响应问题的可行性与适用性。     

Effect of Variable Selection on Multidisciplinary Design Optimization： a Flight Vehicle Example

Different multidisciplinary design optimization (MDO) problems are formulated and compared. Two MDO formulations are applied to a sounding rocket in order to optimize the performance of the rocket. In the MDO of the referred vehicle, three disciplines have been considered,which are trajectory, propulsion and aerodynamics. A special design structure matrix is developed to assist data exchange between disciplines. This design process uses response surface method (RSM) for multidisciplinary optimization of the rocket. The RSM is applied to the design in two categories: the propulsion model and the system level. In the propulsion model, RSM deter-mines an approximate mathematical model of the engine output parameters as a function of design variables. In the system level, RSM fits a surface of objective function versus design variables. In the first MDO problem formulation, two design variables are selected to form propulsion discipline. In the second one, three new design variables from geometry are added and finally, an optimization method is applied to the response surface in the system level in order to find the best result. Application of the first developed multidisciplinary design optimization procedure increased accessible altitude (performance index) of the referred sounding rocket by twenty five percents and the second one twenty nine.     

Multi-disciplinary design optimization with fuzzy uncertainties and its application in hybrid rocket motor powered launch vehicle

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.     

部件级多组件结构系统的整体式拓扑布局优化

基于多组件结构系统整体式拓扑布局优化设计方法,研究了同时含有部件布局、组件布局、主结构框架构型和部件结构构型4类设计变量的复杂系统协同优化设计问题,是整体式拓扑布局优化设计面向复杂飞行器结构系统设计的拓展。采用多点约束(MPC)模拟组件、部件及支撑结构之间的刚性连接,采用有限包络圆方法(FCM)解决组件之间、组件与设计域边界之间的几何干涉问题。通过整体式拓扑布局的刚度优化设计,部件和组件均可以获得优化的布局位置,同时主结构框架构型和部件结构构型获得优化的结构样式,充分体现了整体式拓扑布局优化设计方法应用于复杂结构系统设计的能力。     

航天电磁继电器可靠性容差分析技术的研究

航天电磁继电器是在航天电子系统中完成信号传递、执行控制、系统配电等功能的主要电子元器件之一，其可靠性直接影响整个航天电子系统的可靠性。航天继电器可靠性设计技术是其产品可靠性工程的关键技术。本文分析了当前各领域可靠性研究现状及航天电磁继电器产品的可靠性现状与问题，提出并建立了基于正交试验表的电磁吸力可靠性容差分析数学模型、基于概率统计方法的机械反力可靠性容差分析数学模型及基于“应力-强度干涉法”的吸反力配合特性可靠性容差分析数学模型。以某型号航天电磁继电器为例，进行了可靠性容差分析与研究，给出了对航天电磁继电器可靠性设计具有指导作用的重要结论。     

螺旋桨的数值优化设计

本文提供一种螺旋桨气动设计的数值优化方法。作为优化基础的气动性能计算部分,采用了 Goldstein理论为基础的片条理论,计算结果与实验数据比较表明,性能计算方法是可用的。数值优化采用的是混合罚函数法。利用本数值优化方法对两个已有的螺旋桨重新进行了优化设计。结果表明,在最高效率点附近,效率随桨叶几何参数的变化比较缓慢;同时取弦长和扭角作为设计变量可以设计出比单独取扭角为设计变量时弦长更短的螺旋桨,从而可减小桨叶重量和提高螺旋桨的巡航效率。      

Direct dynamic-simulation approach to trajectory optimization

This paper proposes a new direct method for an efficient trajectory optimization using the point that the dynamics of a deterministic system are uniquely determined by initial states and controls imposed over the time horizon of interest. To effectively implement this concept, the Hermite spline is adopted to interpolate the continuous controls and the system dynamics are integrated with corresponding control parameters in prior. As a result, the optimal control problem can be transcribed into a nonlinear programming problem which has no dynamic equality constraints and no intermediate states in its design variables. In addition, the paper proposes an efficient recursive Jacobian estimation technique and introduces a Jacobian transformation matrix to straightforwardly handle the general state constraints. Important properties of the present method are thoroughly investigated through its applications to the trajectory optimization for a soft lunar landing from a parking orbit, including the detailed analyses for the de-orbiting phase. The computed results are compared with those using the pseudo-spectral method to demonstrate an extreme outperformance of the proposed method in the aerospace applications over the traditional direct method.     

General optimal design of solar-powered unmanned aerial vehicle for priority considering propulsion system

This paper describes the general optimization design method of Solar-Powered Unmanned Aerial Vehicle which priority considering propulsion system planning. Based on the traditional solar powered aircraft design method, the propulsion system top-level target parameters which affect the path planning are integrated into the general optimization design. According to the typical mission requirements of Solar-Powered Unmanned Aerial Vehicle, considering the design variables such as wing area, aspect ratio, design mission date and so on, the general optimization is carried out with the minimum aircraft weight as the optimization objective. The influence of wing area and aspect ratio on the optimal design results is analyzed and compared with the traditional design method. The results show that the general design method of Solar-Powered Unmanned Aerial Vehicle for priority considering propulsion system can greatly reduce the electricity demand of energy storage battery, greatly reduce the aircraft weight of Solar-Powered Unmanned Aerial Vehicle.     

某直升机主减速器行星轮系功质比的区间多目标优化

针对某型直升机主减速器行星轮系功质比的优化问题,建立含有密度和啮合摩擦因数等不确定性参数的区间多目标优化函数及相应的约束函数,利用改进的区间多目标分层优化方法,得到多目标优化函数的最优结果区间和参数变量,对优化前后主减速器行星轮系的传动性能进行深入比较。根据优化结果设计直升机主减速器行星轮系的传动效率试验方案,试验结果表明:区间多目标优化后主减速器行星轮系质量减少6.2%,传动效率提高2.14%,且效率曲线变化随着载荷的波动更加趋于稳定,说明区间多目标优化方法应用于某型直升机主减速器行星轮系功质比优化方面的有效性。      

Review of hybrid electric powered aircraft,its conceptual design and energy management methodologies

The paper overviews the state-of-art of aircraft powered by hybrid electric propulsion systems. The research status of the design and energy management of hybrid aircraft and hybrid propulsion systems are further reviewed. The first contribution of the review is to demonstrate that, in the context of relatively underdeveloped electrical storage technologies, the study of mid-scale hybrid aircraft can contribute the most to both theoretical and practical knowledge. Meanwhile, the profits and potential drawbacks of applying hybrid propulsion to mid-scale hybrid airplanes have not been thoroughly illustrated. Secondly, as summed in the overview of design methodologies, the multi-objective optimization transcends the single-objective one. The potential of the hybrid propulsion system can be thoroughly evaluated in only one optimization run, if several objectives optimized simultaneously. Yet there are few researches covering the conceptual design of hybrid aircraft using multi-objective optimization. The review of the most popular energy management strategies discloses the third research gap—current methodologies favoured in hybrid ground vehicles do not consider the aircraft safety. Additionally, both non-causal and causal energy management are needed for performing a complicated flight mission with several sub-tasks.     

基于混合遗传算法的压气机叶型自动优化设计

1引言遗传算法(Genetic A lgorithms,简称GA)是模拟生物在自然环境中的遗传选择和自然淘汰的进化过程而形成的一种全局优化概率搜索算法。遗传算法实施群体搜索,概率转移,不需要目标函数的导数信息,其全局搜索能力强,简单通用,适于并行处理,因而广泛应用于各种复杂系统的优化问