A multi-objective airfoil shape optimization study using mesh morphing and response surface method

Journal of Mechanical Science and Technology - Here, a distinct procedure was adopted to optimize the shape of the NACA 0012 airfoil profile for Reynolds number, Mach number, and angle of attack...     

多目标优化设计的最小偏差法

提出了处理多目标问题的最小偏差法，并将其应用于普通圆柱螺旋弹簧的优化设计，以普通圆柱螺旋弹簧的质量、高度及防共振性能为目标函数进行了优化设计。算例结果表明，此方法能够克服传统优化算法极易陷入局部最优的缺点，而且收敛速度快。因而得到了比传统算法更优的设计方案。     

基于粒子群算法的螺旋输送机多目标优化设计

以螺旋输送机的重量最小和输送效率最大作为数学模型的2个目标函数,螺旋体的结构参数为设计变量,建立了螺旋输送机的多目标优化模型,并用粒子群算法编程求解数学模型。求解优化结果表明,螺旋输送机的重量减少8.2%,输送效率提高4.5%,对螺旋输送机的优化设计具有一定的指导意义。     

基于遗传退火算法的装配线设计多目标优化方法

针对混装配线设计这一有约束的多目标优化问题,建立了数学模型。将基于Pareto的解的分级方法与Lp-范数形式的非线性机制相组合,构建了基于遗传退火算法多目标优化方法。重点阐述了个体编码、染色体检修、多目标处理机制等关键技术。设计了算法流程图,并开发了优化程序。该方法克服了加权和方法的不足,用模拟退火改善了遗传算法全局寻优性能。计算实例表明,随着迭代次数的增加,每代的非受控点逐渐收敛于Pareto最优边界,是一种混装线设计多目标优化的新方法。     

Fluid-dynamic analysis and multi-objective design optimization of piezoelectric servo valves

This paper proposes an effective methodology for the fluid-dynamic design optimization of the main spool of a piezoelectric servo valve. The aim is to improve global performances of the piezoelectric servo valve by reducing the flow force acting on the main spool and the mass of the main spool. The main disturbance forces acting the main spool were analyzed. The steady-state flow force acting on the main spool was derived and the relationship between the flow force and the design parameters of the main spool was established. The design problem of the main spool was formulated mathematically as a multi-objective optimization problem. The minimum steady-state flow force and the minimum mass of main spool were considered as optimization objectives. The elitist non-dominated sorting genetic algorithm (NSGA-II) was applied and a set of Pareto-optimal solutions was calculated. The optimized results were analyzed and the final design parameters of the main spool were selected for the simulation analysis and experimental research. The computational fluid dynamics (CFD) simulation was employed to calculate the forces acting on the main spool. Simulation results show the flow force acting on the optimized main spool is significantly reduced. The unoptimized and optimized main spools were machined and experimental study was performed. Results show that the piezoelectric servo valve equipped with the optimized main spool has better response performance and dynamic bandwidth. The dynamic bandwidth is measured to 172 Hz under the amplitude attenuation of −3 dB. Compared with the piezoelectric servo valve with unoptimized main spool, the dynamic bandwidth of the piezoelectric servo valve with optimized main spool is increased by 26%.     

机械产品生命周期的多目标优化设计方法

机械产品生命周期包括对产品的社会需求的形成,产品的设计、试验、定型,产品的制造、使用、维修以及达到其经济使用寿命之后的回收利用和再生产的整个闭环周期.通过分析机械产品生命周期的生产成本和经济损失的期望,并分析了多目标产品成本价值与可靠度的关系.机械产品生命周期的多目标优化设计方法是实现现代设计理论发展的产物,也是现代机械设计的必然方向.     

基于粒子群算法的机械零件多目标优化设计研究

机械零件多目标优化设计是工程设计中常遇到的优化设计问题.提出了一种基于粒子群算法的机械零件多目标优化设计方法与策略,对弹簧零件设计参数进行了多目标优化设计分析.结果表明该方法可用于弹簧参数的多目标优化设计,且计算参数调整简单,应用方便,可根据分目标侧重需要,得到不同分目标偏重的优化设计参数.     

Optimum design of pultrusion process via evolutionary multi-objective optimization

Pultrusion is one of the most cost-effective manufacturing techniques for producing fiber-reinforced composites with constant cross-sectional profiles. This obviously makes it more attractive for both researchers and practitioners to investigate the optimum process parameters, i.e., pulling speed, power, and dimensions of the heating platens, length and width of the heating die, design of the resin injection chamber, etc., to provide better understanding of the process, consequently to improve the efficiency of the process as well as the product quality. Using validated computer simulations is “cheap” and therefore is an attractive and efficient tool for autonomous (numerical) optimization. Optimization problems in engineering in general comprise multiple objectives often having conflict with each other. Evolutionary multi-objective optimization (EMO) algorithms provide an ideal way of solving this type of problems without any biased treatment of objectives such as weighting constants serving as pre-assumed user preferences. In this paper, first, a thermochemical simulation of the pultrusion process has been presented considering the steady-state conditions. Following that, it is integrated with a well-known EMO algorithm, i.e., nondominated sorting genetic algorithm (NSGA-II), to simultaneously maximize the pulling speed and minimize “total energy consumption” (TEC) which is defined as a measure of total heating area(s) and associated temperature(s). Finally, the results of the evolutionary computation step is used as starting guesses for a serial application of a of gradient-based classical algorithm to improve the convergence. As a result, a set of optimal solutions are obtained for different trade-offs between the conflicting objectives. The trade-off solution, thus obtained, would remain as a valuable source for a multi-criterion decision-making task for eventually choosing a single preferred solution for the pultrusion process.     

基于物理规划的多学科多目标设计优化

针对复杂产品多学科多目标设计优化存在的耦合严重、计算效率低、难以获得体现设计者偏好的最优解等问题,提出了基于物理规划和改进的协同优化策略的多学科多目标设计优化方法,阐述了该方法的基本思想并给出了设计优化流程.该方法密切结合实际工程设计经验,将多目标优化问题转换为反映设计者偏好的综合目标优化问题,采用改进的协同优化策略建立多层次的优化模型进行并行优化,得到了反映设计者偏好的最优解.以飞机起落架缓冲器为例,证明了该方法可以较好地求解多目标优化问题的折中非裂解.     

随机梯度遗传算法在翼型优化设计中的运用研究

针对标准遗传算法在优化搜索过程中,局部搜索能力较低的弱点,利用将遗传算法与实时扰动随机逼近方法(SPSA算法)为基础的随机梯度算法相结合而产生的随机梯度遗传算法建立了可用于气动外形优化设计的设计方法.并运用此算法开展了有关翼型的气动优化研究.相关结果表明,将随机梯度遗传算法用于气动外形优化设计,不仅可以提高优化效率,同时由于增强了局部搜索能力,因此,在有限的搜索条件下,可以提高优化设计结果的质量.     

基于稳健性和多目标优化的车顶结构轻量化设计研究

针对国内外顶结构轻量化的研究多是单目标优化,且没有考虑不确定性因素影响的问题,提出了一种基于多目标优化和6σ稳健性设计的车顶结构轻量化设计方法。通过参数试验设计进行了灵敏度分析,筛选出了对车顶响应贡献量较大的结构件厚度作为设计变量;采用最优拉丁超立方设计和响应面法建立了车顶各响应的近似模型;以设计变量总质量、覆雪强度、抗凹性能为优化目标,前三阶模态频率为约束条件,基于近似模型,运用第二代非支配排序遗传算法(NSGA-Ⅱ)进行了确定性多目标优化,得到确定性多目标优化结果;运用蒙特卡洛模拟技术对确定性多目标优化结果进行了6σ质量分析,并进行了6σ稳健性多目标优化。优化结果表明,车顶结构在满足各性能要求的情况下实现了轻量化,质量减轻3.77 kg,且覆雪强度提高,同时车顶结构各工况性能的稳健性提高,达到6σ质量水平。     

Novel steel wheel design based on multi-objective topology optimization

This paper aims to propose a multi-objective topology optimization methodology for steel wheel, in which both the compliance and eigenfrequencies are regarded as static and dynamic optimization objectives. Compromise programming method is employed to define the objectives of multi-objective and multi-stiffness topology optimizations, whereas mean-frequency formulation is adopted to settle eigenfrequencies of free vibration optimization. To obtain a clear and useful topology optimization result, cyclical symmetry and manufacturing constraints are set, the influences of which on the outcomes are also discussed. With an appropriate value of the minimum member size, a rough topology optimization of the steel wheel is obtained. The optimization result is modified according to the actual structure and manufacturing process. Moreover, based on this result, eight different steel wheel modes are established to analyze the influence of the manufacturing process and draw beads on the wheel performance through finite element simulation. Simulation results are verified by conducting a stress test of a commercially available wheel. Compared with its initial design, the optimized wheel disc exhibited decreased mass at 0.15 Kg at percentage of 4.57%, manifesting the effectiveness of the proposed method.     

带式输送机普通V带传动多目标优化设计

针对带式输送机中V带传动的生产实际,根据优化设计理论,以V带的根数最少、小带轮直径最小、中心距最小为优化目标,建立了多目标优化设计数学模型,运用线性加权和法的加权因子建立评价函数,基于VC＋＋语言编程,采用复合形法进行优化设计,得到的最优传动方案使V带的根数比原来减少了40％。     

基于振动特性的多学科多目标摩托车优化

以摩托车强度、刚度、轻量化为约束条件,以响应面法为基础建立多学科多目标优化方案.运用Hypermesh建立有限元模型,通过Radioss进行计算,并以Hyperstudy为优化平台.采用正交实验设计对优化变量进行灵敏度分析,运用拉丁方实验设计获取采样数据点,利用移动最小二乘法构建响应面模型,结合多学科、多目标优化设计方法进行结构优化,实现提高车架结构特性和摩托车动态特性的目标.     

基于多目标优化的楔环连接结构尺寸设计

有限元方法与最优化方法是工程设计与分析的两个常用方法,将两者结合起来,可以很好地实现楔环连接结构的多目标优化设计.基于响应面法确定楔环连接结构的4个几何参数的各种组合样本,利用有限元分析软件ANSYS时不同参数组合样本的楔环连接结构进行应力场分析,然后以既降低结构最大应力又减轻结构质量为目标,通过MAT-LAB中的多目标优化设计工具计算得到楔环连接结构的4个几何参数的最优值.数值计算结果表明,优化几何参数后的楔环连接结构比原结构最大应力下降13.6%,质量下降12.5%.     

无人机自主着陆纵向控制律设计

针对无人机的自主高精度定点着陆,应用自适应内模控制(AIMC)原理设计了自主着陆纵向飞行控制律。以轮式无人机为平台,将纵向非线性模型解耦并线性化。然后,以地速和下沉率为控制目标,应用AIMC理论设计了纵向飞行控制律。通过对AIMC滤波参数进行自调整改善了系统的动态特性,基于对模型的辨识增强了系统的鲁棒性。在顺逆风6m/s的条件下对AIMC系统进行了数字仿真,结果显示其落点精度达到前后向30 m范围内。与传统内模控制(IMC)系统相比,提出的自适应内模控制(AIMC)系统在动态性能和落点精度等方面均有明显提高。最后,搭建了半物理测试平台,通过半物理仿真测试复现了系统数字仿真结果,验证了系统功能的完整性和协调性。     

A multi-objective optimization for HAWT blades design by considering structural strength

The challenge of wind turbine blade design is to balance the conflict between high capacity and heavy system loads introduced by the large scale rotor. To solve this problem, we present a multi-objective optimization method to maximize the Annual energy production (AEP) and minimize the blade mass. The well-known Blade element momentum (BEM) theory is employed to predict the aerodynamic performance and AEP of the blade. The blade is simplified as a thin Bernoulli beam. The cross section is modelled as a combination of composite layer, shear webs and spar caps typically. The strain of every cross section has been considered as a constraint to minimize the spar cap thickness for minimizing the blade mass. An improved genetic algorithm (NSGA-II) is applied to obtain the Pareto front set. Several solutions of the Pareto set are selected to compare with the reference blade (NREL 5MW blade). Performance of the rotors on design condition is simulated by STAR-CCM+ to verify the results of BEM theory. Optimal results show that the present blade, which is fully superior to the reference blade, can be selected from the Pareto set. The optimization design method can provide a superior blade with an increase by 2.48% of AEP and a reduction by 5.52% of the blade mass. It indicates the present optimization method is effective. Results of numerical simulations show that the spanwise flow would be increased obviously in tip region of the reference blade. The reason is that chord length variation in blade tip affects the flow and causes minor stall. The abrupt change of chord distribution in blade tip should be avoided to reduce the spanwise flow in initial blade design.

     

The multi-objective optimization design for the magnetic adsorption unit of wall-climbing robot

Journal of Mechanical Science and Technology - The motion stability and mass of the magnetic crawler wall-climbing robot usually affects the working performance of robot. In this study, the...     

Multidisciplinary design optimization of vehicle instrument panel based on multi-objective genetic algorithm

Typical multidisciplinary design optimization(MDO) has gradually been proposed to balance performances of lightweight, noise, vibration and harshness(NVH) and safety for instrument panel(IP) structure in the automotive development. Nevertheless, plastic constitutive relation of Polypropylene(PP) under different strain rates, has not been taken into consideration in current reliability-based and collaborative IP MDO design. In this paper, based on tensile test under different strain rates, the constitutive relation of Polypropylene material is studied. Impact simulation tests for head and knee bolster are carried out to meet the regulation of FMVSS 201 and FMVSS 208, respectively. NVH analysis is performed to obtain mainly the natural frequencies and corresponding mode shapes, while the crashworthiness analysis is employed to examine the crash behavior of IP structure. With the consideration of lightweight, NVH, head and knee bolster impact performance, design of experiment(DOE), response surface model(RSM), and collaborative optimization(CO) are applied to realize the determined and reliability-based optimizations, respectively. Furthermore, based on multi-objective genetic algorithm(MOGA), the optimal Pareto sets are completed to solve the multi-objective optimization(MOO) problem. The proposed research ensures the smoothness of Pareto set, enhances the ability of engineers to make a comprehensive decision about multi-objectives and choose the optimal design, and improves the quality and efficiency of MDO.     

基于多目标遗传优化的注射成型机性能设计

采用一种基于多目标第二代非支配排序遗传算法的大型注射成型机总体性能优化设计方法,以最大注射压力、最大注射速率和最小注射功率为优化目标,系统分析了两两组合优化和三目标并行优化时,注射油缸内径、螺杆直径、工作油压力和工作油流量等设计参数对注射机构性能的影响,以及螺杆最大塑化能力的变化趋势.对于多目标优化的Pareto集,使用基于模糊集合理论的方法在其中选择一个最优解,排除人为偏好的不确定因素.与强度Pareto进化算法相比,第二代非支配排序遗传算法能以较小的时空复杂性得到分布均匀且更加逼近最优解的Pareto前沿.最后,以HTF180X2N大型注射成型机为例,说明所得结果可为决策者在大型注射成型机方案设计阶段进行目标权衡处理提供有效的依据.