UUV耐压结构多目标优化设计

UUV(unmanned underwater vehicle,无人水下航行器)在海洋民用与军事领域具有广阔的应用前景。UUV耐压结构作为影响UUV负载能力及保障UUV航行任务安全高效执行的重要部件,其优化设计有重要意义。为了最大程度地实现减重目标,有效平衡耐压结构质量、结构强度和稳定性之间的矛盾,进而提升UUV综合性能,提出一种基于组合加权响应面法的多目标优化方法。通过试验设计得到初始采样点,利用有限元工具计算响应值并构建代理模型;然后,以折衷规划法对子目标进行归一化处理,采用组合加权法设定子目标权重系数,以进行耐压结构的多目标优化设计。以某型UUV为例,利用所提方法对其梯形肋骨耐压结构进行多目标优化设计,优化后耐压结构质量减轻了6.6%,肋骨应力下降了6.7%,同时满足稳定性要求。在此基础上,分别以质量为优化目标和以质量、结构强度和稳定性为综合优化目标,对不同肋骨形式耐压结构进行优化设计。结果表明:梯形肋骨耐压结构的综合优化效果最佳。该研究方法适用于UUV耐压结构的多目标优化,研究结果可为UUV耐压结构优化设计提供理论指导,具有实际工程意义。     

基于疲劳寿命的旋翼气动弹性多目标优化研究

基于Hamilton原理基础上推导了旋翼桨叶有限元动力学模型和疲劳寿命计算模型。以动力学特性的固有频率,自转惯量为约束,以剖面特性参数的挥、摆、扭刚度及桨叶线性密度为设计变量,进行最小质量及最大疲劳寿命的多目标优化。采用满足溢出分析的优化算法（Satisficing Trade-off Analysis）。结果在满足各约束条件下,实现旋翼桨叶质量减少7.27％,疲劳寿命循环次数由3.98 108次到4.73 108次,寿命提高了18.7%,优化效果明显。     

基于声振耦合的装载机驾驶室多目标形貌优化设计

对某装载机驾驶室及室内声腔进行建模得到声振耦合模型,通过SIMO法模态试验验证所建模型的准确性,测取悬置点激励力并进行频响分析及室内噪声预测。结合耦合模态频率和噪声曲线峰值频率确定关键优化频率,在驾驶室的最大扭矩工况下进行静力学分析,采用折衷规划法和平均频率法将驾驶室静态整体刚度和多阶关键频率归一为Euclidean距离的多目标函数,对驾驶室进行多目标形貌优化。结果表明:此优化方法在驾驶室结构优化上的应用综合提高了结构整体刚度和多阶关键固有频率,避免了单频优化时频率震荡现象,得到了优化目标的整体Pareto最优解,室内噪声总声压级降低了3.03 d B。     

机械基础结构多目标拓扑优化设计方法

机械的基础结构在保证具有足够的刚度、强度和稳定性的条件下,经济性也必须要好,因此机械基础结构常采用内部布置有加筋板的箱体结构。以某机械基础结构为例,分别用基于经验设计的内部筋板布置方法和多目标拓扑优化方法进行优化设计,得到了2 种设计方案;比较了2 种方案的动静态力学性能。结果表明,多目标拓扑优化设计的基础结构比一般经验设计的结构,刚度有所提高,而结构质量减小11. 21%,一阶固有频率提高25. 07%。     

基于多工况并行任务的摩托车悬架参数多目标优化

应用摩托车动力学软件BikeSim建立了人-车系统仿真模型,对加速/制动工况下的车身俯仰角和B级路面工况下等速行驶的整车平顺性分别进行了仿真;以加速/制动工况下的俯仰角最大值和等速B级路面工况下的车身垂向、俯仰振动加速度均方根值为优化目标,以悬架特性参数为设计变量,采用iSIGHT集成BikeSim和MATLAB建立两种工况的并行计算任务,对摩托车悬架系统进行了多目标优化,根据Pareto前沿提出了一种确定目标权重的方法,得到了最优解。优化前后结果对比表明：加速/制动俯仰角和平顺性均有改善。     

基于代理模型的空投装备气囊缓冲系统多目标优化

基于有限元法和控制体积法建立装备-气囊系统有限元模型,并采用试验数据对模型进行验证。复杂气囊系统着陆缓冲过程仿真计算资源消耗大,难以应用传统迭代方法进行参数优化。为克服这些问题,结合扩展拉丁超立方设计,以最大着陆冲击加速度和最大翻转角度为响应,采用径向基函数构建代理模型。在代理模型基础上,利用多目标遗传算法对主气囊高度、横向宽度及排气孔面积等气囊缓冲系统参数进行了多目标优化。优化结果表明:优化后最大冲击加速度减小了15.5%,最大翻转角度减小了70.3%,缓冲性能与横向稳定性均有所提高。     

汽车乘员舱多层吸声材料的多目标优化

建立了汽车的统计能量分析模型,进行仿真与实验的误差分析,验证了所建模型的有效性,然后选取四层吸声材料布置于乘员舱顶棚,采用优化拉丁方法,以其厚度为设计变量,为降低驾驶员耳旁噪声和满足汽车结构轻量化和低成本的要求,以驾驶员头部声腔A声级降低幅度、吸声材料重量、降噪效率、材料价格和性价比为优化目标,选取30个样本点进行试验设计并通过计算得到全部响应值,之后建立了Kriging近似模型,为验证该近似模型模拟精度,任选三个新的样本点分析近似模型和仿真结果间的误差,最后以近似模型为基础执行多目标优化,与吸声材料初始组合相比,A声级降低幅度反而减小了0.289dB,但重量降低了54.8%,降噪效率提高了85.6%,材料价格降低了21.1%,性价比提高了6.0%。     

频率双向渐进优化方法中新的插值技术

研究了拓扑结构优化中的插值技术。针对传统的频率双向渐进优化方法所采取的代数外插方式只能用于规则的矩形单元或长方体单元的情形,根据当前结构的主振型,建立静力平衡方程组,从而计算出边界单元新增加结点的模态位移。这种插值技术可以将双向渐进优化方法推广运用于任意形状的单元。仿真算例表明,该方法有效可行。     

基于动响应约束的结构材料优化设计

针对于随机荷载作用下动响应为约束的结构材料优化问题,基于结构拓扑优化思想,提出了一种变动响应约束的结构材料优化方法。采用分式有理式和幂函数识别结构材料单元特性参数,以微观单元拓扑变量倒数为设计变量,导出了频率及振型对微观单元设计变量的一阶导数,进而得到了随机荷载作用下结构均方响应的一阶近似展开式。结合变约束限的思想,建立了以结构质量作为目标函数,均方响应作为约束条件的连续体微结构拓扑优化近似模型,并采用对偶方法进行求解。对典型结构进行了考虑单个和多个动响应约束的结构材料优化设计,优化所得结果验证了该方法的有效性和可行性。     

基于遗传算法和拓扑优化的结构多孔洞损伤识别

鉴于拓扑优化和遗传算法在结构损伤识别中各自的优点,本文将遗传算法、有限元和拓扑优化三种方法相结合,提出了一种用于二维结构多损伤识别的新方法。这种方法将拓扑优化的设计变量和遗传算法的参数统一化,将拓扑优化中的目标函数和约束方程与遗传算法的适应度函数联系起来,并以拓扑优化的约束方程作为控制条件参与整个遗传运算的控制。采用二进制编码遗传算法代替连续变量拓扑优化的方式对发生孔洞损伤形式的二维结构进行损伤识别,避免了利用连续变量拓扑优化进行损伤识别时参数阈值的确定可能给识别结果带来的不良影响。通过对两个二维结构模型的多损伤识别仿真计算,结果显示本方法能够很好地识别二维结构中多个位置的损伤,对于仅用拓扑优化法很难识别的轻微孔洞损伤情况,该方法也能得出与实际情况吻合良好的结果。     

Multi-objective optimization design using amended particle swarm optimization and Taguchi method for a six-phase copper rotor induction motor

A multi-objective optimization design technique for a six-phase copper rotor induction motor is proposed. The amended particle swarm optimization (PSO) and Taguchi methods combined with finite element analysis are used in this design technique. The objectives in the first-stage optimization are the minimization of manufacturing cost and starting current. In the second-stage optimization, the objectives are the maximization of efficiency, power factor and output torque. The Taguchi method can optimize the machine parameters of performance characteristics in electrical discharge machining. The experimental results are further transformed into the signal-to-noise ratios and amended PSO coefficients based on amended PSO analysis with regard to multiple performance characteristics index values. The results of the optimizations showed significant reduction in terms of the use of magnets as well as improvement in the machine performance. Finally, the experimental results confirm the validity of the proposed optimization design approach.     

飞机总体设计中的一种多目标鲁棒优化方法

 提出一种基于灵敏度的多目标鲁棒优化方法。针对各维设计变量存在扰动的情况,在原约束多目标优化模型上,附加偏差目标函数,并采用最差估计法对约束条件进行鲁棒可行性调整。采用全局敏度方程方法来计算目标函数和约束函数对设计变量的敏度,进而采用Pareto遗传算法搜索约束多目标优化问题的非劣解集,设计者可以根据不同的设计准则从中选择合适的设计点。将上述方法用于飞机总体参数优化设计,并与采用常规优化方法所得的优化结果进行了分析和比较。     

Multi-objective optimization based on meta-modeling by using support vector regression

Practical engineering design problems have a black-box objective function whose forms are not explicitly known in terms of design variables. In those problems, it is very important to make the number of function evaluations as few as possible in finding an optimal solution. So, in this paper, we propose a multi-objective optimization method based on meta-modeling predicting a form of each objective function by using support vector regression. In addition, we discuss a way how to select additional experimental data for sequentially revising a form of objective function. Finally, we illustrate the effectiveness of the proposed method through some numerical examples.     

基于GA-NLP的剪刀式折叠桥梁展桥机构多目标优化设计

针对新型剪刀式折叠桥梁展桥机构的优化设计问题,首先建立了展桥机构的运动学和静力学模型,然后以展桥机构关键铰点位置和岸桥节与竖直方向所成夹角为优化设计变量,以展桥机构的空间位置为主要约束条件,以展桥油缸、连杆、关键铰点受力峰值最小为优化目标,通过正规化和加权处理构造了展桥机构多目标优化分析模型,并采用遗传算法（genetic algorithm, GA）和非线性规划(nonlinear programming, NLP)混合算法对该优化分析模型进行求解。最后,利用ADAMS（automatic dynamic analysis of mechanical systems,机械系统动力学自动分析）软件验证了展桥机构多目标优化分析模型的正确性。结果表明,优化后展桥油缸承载的拉力与推力峰值分别减小了57.9%和25.3%,连杆承载的拉力与压力峰值分别减小了26.1%和55.2%,展桥机构2个关键铰点受力峰值分别减小了23.5%和26.8%。研究结果可为展桥机构的改进设计提供理论依据。     

Geometrical design of thermoelectric generators based on topology optimization

This paper discusses an application of the topology optimization method for the design of thermoelectric generators. The proposed methodology provides the optimized geometry in accordance with various arbitrary conditions such as the types of materials, the volume of materials, and the temperature and shape of the installation position. By considering the coupled equations of state for the thermoelectric problem, we introduce an analytical model subject to these equations, which mimics the closed circuit composed of thermoelectric materials, electrodes, and a resistor. The total electric power applied to the resistor and the conversion efficiency are formulated as objective functions to be optimized. The proposed optimization method for thermoelectric generators is implemented as a geometrical optimization method using the solid isotropic material with penalization method used in topology optimizations. Simple relationships are formulated between the density function of the solid isotropic material with penalization method and the physical properties of the thermoelectric material. A sensitivity analysis for the objective functions is formulated with respect to the density function and the adjoint equations required for calculating it. Depending on the sensitivity, the density function is updated using the method of moving asymptotes. Finally, numerical examples are provided to demonstrate the validity of the proposed method. Copyright © 2012 John Wiley & Sons, Ltd.     

基于多场耦合方法的厚截面复合材料固化过程的多目标优化

针对厚截面复合材料固化过程温度峰值过大所引起的材料力学性能降低及残余应力过大等问题,建立了基于多场耦合方法的复合材料固化过程多目标优化模型,用以降低固化温度峰值和缩短固化时间.首先建立包含热化学子模型、树脂黏度子模型和流动压实子模型的固化温度多场耦合模型,用以准确描述固化过程复合材料内部温度及构件厚度的演化规律.通过与...     

Multi-objective ceramic matrix composite material design using the variable fidelity model management optimization framework

The increasing computational requirements of advanced numerical tools for simulating material behaviour can prohibit direct integration of these tools in a design optimization procedure where multiple iterations are required. Therefore, a design approach is needed that can incorporate multiple simulations (multi-physics with different input variables) of varying fidelity in an iterative model management framework that can significantly reduce design cycle times. In this research, a material design tool based on a variable fidelity model management framework is applied to obtain the optimal size of a second phase, consisting of silicon carbide (SiC) fibres, in a silicon-nitride (Si₃N₄) matrix to obtain continuous fibre SiC-Si₃N₄ ceramic composites (CFCCs) with maximum high temperature strength and high temperature creep resistance. This investigation shows how models with different dimensions and input design variables can be handled and integrated efficiently by the trust region model management framework, while significantly reducing design cycle times in application to the design of multiphase composite materials.     

A structural optimization method based on the level set method using a new geometry‐based re‐initialization scheme

Structural optimization methods based on the level set method are a new type of structural optimization method where the outlines of target structures can be implicitly represented using the level set function, and updated by solving the so‐called Hamilton–Jacobi equation based on a Eulerian coordinate system. These new methods can allow topological alterations, such as the number of holes, during the optimization process whereas the boundaries of the target structure are clearly defined. However, the re‐initialization scheme used when updating the level set function is a critical problem when seeking to obtain appropriately updated outlines of target structures. In this paper, we propose a new structural optimization method based on the level set method using a new geometry‐based re‐initialization scheme where both the numerical analysis used when solving the equilibrium equations and the updating process of the level set function are performed using the Finite Element Method. The stiffness maximization, eigenfrequency maximization, and eigenfrequency matching problems are considered as optimization problems. Several design examples are presented to confirm the usefulness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.