在互联网上进行结构系统协同优化的信息交流与进程调控

 由于异地分布式复杂产品系统的分系统是由不同设计单位分别进行优化设计的。一般说来，这样组集起来的产品系统并不能得到真正优化． 为得到整个分布式结构系统的优化设计就必须进行网络化全局协调优化设计．以互联网的电子邮件为基础，研究了在互联网上进行结构系统全局协调优化设计的信息交流与进程调控技术及其实现途径，并利用VB计算机语言开发了一个实用软件系统． 一个卫星结构系统全局协调优化设计的应用实例表明了分布式结构系统网络化协同优化的必要性和所开发软件的有效性．这项技术对于复杂产品的全球化协同设计具有重要意义．     

Design optimization of a centrifugal compressor vaneless diffuser

Centrifugal compressors are used in many heat pumps and refrigeration systems. Radial vaneless diffuser is a principal component in these compressors. Therefore, the present research aims at improving the centrifugal compressor performance by optimizing the design of the radial vaneless diffuser. Two radial vaneless diffuser geometries were proposed, investigated and numerically optimized. The optimization aimed at minimizing the diffuser loss coefficient and maximizing the pressure coefficient. Simulations were performed by solving the Reynolds averaged Navier–Stokes equation under 2D axisymmetric condition. A genetic optimization algorithm was implemented in order to conclude the optimum diffuser geometry. 2D axisymmetric simulations with air and R134a as working fluids showed that the optimized geometry reduced the diffuser loss coefficient by up to 10% and increased the pressure coefficient by up to 3.8%. Additional 3D simulations with an impeller located before the diffuser were performed. These 3D simulations showed that the optimized diffuser geometry reduced the diffuser loss coefficient by up to 4.7% and increased the pressure coefficient by up to 6.6% under jet-wake and swirl flow conditions.     

内燃机噪声优化对车内声学的影响研究

提出了内燃机结构辐射噪声的仿真与优化方法,评价了内燃机噪声优化前后车内噪声的变化。建立了内燃机和前围板的有限元模型,通过模态分析验证了模型的精度。采用柔性多体动力学方法计算了内燃机的振动响应,并结合边界元算法得到了结构辐射噪声。完成了机体的结构优化,通过提升刚度使整体模态频率与激励峰值频率分离,从而降低机体结构响应,减小辐射噪声。搭建了内燃机与前围板的声学耦合模型,计算得到经机体结构优化前后的内燃机辐射噪声通过前围板后进入车内的声功率。结果显示,机体的优化方案大幅降低了其辐射噪声,从而减小了整机的辐射噪声。研究内燃机噪声与车内噪声的传递路径后,发现车内噪声有了明显的下降,从而证实了优化设计的可行性和有效性。     

An optimization design of vehicle axle system based on multiobjective cooperative optimization algorithm

ABSTRACT

To address multiobjective, multi constraint and time-consuming structural optimization problems in a vehicle axle system, a multiobjective cooperative optimization model of a vehicle axle structure is established. In light of the difficulty in the nondominated sorting of the NSGA-II algorithm caused by inconsistent effects of the uniformity objective function and physical objective function, this paper combines a multiobjective genetic algorithm with cooperative optimization and presents a strategy for handling the optimization of a vehicle axle structure. The uniformity objective function of the sub discipline is transformed to its self-constraint. Taking the multiobjective optimization of a vehicle axle system as an example, a multiobjective cooperative optimization design for the system is carried out in ISIGHT. The results show that the multiobjective cooperative optimization strategy can simplify the complexity of optimization problems and that the multiobjective cooperative optimization method based on an approximate model is favorable for accuracy and efficiency, thereby providing a theoretical basis for the optimization of similar complex structures in practical engineering.     

基于响应面法的刀口金属密封结构优化设计

以有限元数值模拟为手段,通过一阶响应面建模,确定了满足密封判据的刀口金属密封结构设计参数的范围。采用均匀设计,建立了以设计参数为变量,以有效密封面宽、最大接触应力为响应的二阶响应面模型,并利用多目标优化方法和遗传算法,对响应面模型进行了优化求解,得到了优化的设计参数组合。有限元验证结果显示,优化后的密封结构具有更好的密封性能。     

A surrogate-assisted particle swarm optimization algorithm based on efficient global optimization for expensive black-box problems

Evolutionary algorithms cannot effectively handle computationally expensive problems because of the unaffordable computational cost brought by a large number of fitness evaluations. Therefore, surrogates are widely used to assist evolutionary algorithms in solving these problems. This article proposes an improved surrogate-assisted particle swarm optimization (ISAPSO) algorithm, in which a hybrid particle swarm optimization (PSO) is combined with global and local surrogates. The global surrogate is not only used to predict fitness values for reducing computational burden but also regarded as a global searcher to speed up the global search process of PSO by using an efficient global optimization algorithm, while the local one is constructed for a local search in the neighbourhood of the current optimal solution by finding the predicted optimal solution of the local surrogate. Empirical studies on 10 widely used benchmark problems and a real-world structural design optimization problem of a driving axle show that the ISAPSO algorithm is effective and highly competitive.     

Performance enhancement of a compressive thermoelastic cooling system using multi-objective optimization and novel designs

Thermoelastic cooling is a recently proposed, novel solid-state cooling technology. It has the benefit of not using high global warming potential (GWP) refrigerants which are used in vapor compression cycles (VCCs). Performance enhancements on a thermoelastic cooling prototype were investigated. A few novel design options aiming to reduce the cyclic loss were proposed. It was found that the maximum temperature lift increased from 6.6 K to 27.8 K when applying the proposed novel designs, corresponding to 0–152 W cooling capacity enhancement evaluated under 10 K water–water system temperature lift. In addition, a multi-objective optimization problem was formulated and solved using the genetic algorithm to maximize the system capacity and coefficient of performance (COP). With all the novel designs, the optimization could further enhance 31% COP, or 21% cooling capacity, corresponding to COP of 4.1 or 184 W maximum cooling capacity.     

Automated structural optimization system for integrated topology and shape optimization

Abstract

This paper combines previously developed techniques for image‐preprocessing and characteristic image‐interpreting together with a newly proposed automated shape‐optimization modeling technique into an integrated topology‐optimization and shape‐optimization system. As a result, structure designers are provided with an efficient and reliable automated structural optimization system (ASOS). The automated shape‐optimization modeling technique, the key technique in ASOS, uses hole‐expanding strategy, interference analysis, and hole shape‐adjusting strategy to automatically define the design variables and side constraints needed for shape optimization. This technique not only eliminates the need to manually define design variables and side constraints for shape optimization, but during the process of shape optimization also prevents interference between the interior holes and the exterior boundary. The ASOS is tested in three different structural configuration design examples.     

结构拓扑优化中敏度过滤技术研究

为了抑制连续体结构拓扑优化结果中的棋盘格和灰度单元问题,借鉴粒子群优化算法中粒子状态的更新方法,提出一种改进的敏度更新技术.以结构的柔度最小为优化目标,构建了基于固体各项同性微惩罚结构的结构拓扑优化模型,根据结构的力学响应分析,采用优化准则法进行设计变量更新,进行载荷作用下二维连续体结构的拓扑优化设计,得到了材料在设计域内的最优分布.通过与已有敏度过滤技术的对比分析,验证了文中方法的正确性和有效性．     

结构主动控制的一体化多目标优化研究

基于Pareto多目标遗传算法提出了结构主动控制系统的一体化多目标优化设计方法,对作动器位置与主动控制器进行同步优化设计.外界激励采用平稳过滤白噪声来模拟,在状态空间下通过求解Lyapunov方程,得到结构响应和主动控制力的均方值.主动控制器采用LQG控制算法来进行设计.以结构位移和加速度均方值最大值与相应无控响应均方值的最大值之比,以及所需控制力均方值之和作为多目标同步优化的目标函数.优化过程还考虑了结构与激励参数对优化结果的影响.最后以某6层平面框架有限元模型为例进行了计算机仿真分析,结果表明所提出的主动控制系统多目标一体化优化方法简单,高效,实用,具有较好的普适性.     

基于ESO的夹层阻尼圆锯片减振降噪拓扑优化设计

针对夹层阻尼圆锯片的减振降噪拓扑优化设计,基于渐进拓扑ESO（evolutionary structural optimization）算法,寻求阻尼材料最佳布局. 导出了单元删除方法和损耗因子灵敏度计算方法,建立了拓扑优化流程,将损耗因子灵敏度作为衡量单元对结构损耗因子贡献量大小的标准,通过判断阻尼材料各单元对整体结构的减振效果,删除无效单元,得到满足刚度条件下的夹层阻尼圆锯片结构最优配置,使其在减振降噪的同时达到一定的刚度要求. 通过3种圆锯片模型的阻尼损耗因子对比,验证了优化后的圆锯片具有最佳的减振降噪效果．     

An integrated reliability-based design optimization of offshore towers

After recognizing the uncertainty in the parameters such as material, loading, geometry and so on in contrast with the conventional optimization, the reliability-based design optimization (RBDO) concept has become more meaningful to perform an economical design implementation, which includes a reliability analysis and an optimization algorithm. RBDO procedures include structural analysis, reliability analysis and sensitivity analysis both for optimization and for reliability. The efficiency of the RBDO system depends on the mentioned numerical algorithms. In this work, an integrated algorithms system is proposed to implement the RBDO of the offshore towers, which are subjected to the extreme wave loading. The numerical strategies interacting with each other to fulfill the RBDO of towers are as follows: (a) a structural analysis program, SAPOS, (b) an optimization program, SQP and (c) a reliability analysis program based on FORM. A demonstration of an example tripod tower under the reliability constraints based on limit states of the critical stress, buckling and the natural frequency is presented.     

Design, optimization and manufacturing of wood–plastic composite pallet

This paper presents the application of an innovative method of optimization to the design of an I-shape profile used in a wood–plastic composite (WPC) pallet. The pallet was made via assembling three WPC extruded profiles manufactured in the extrusion process. The middle profile was considered to be I-shaped, a design which known to have a high load bearing capability. However, due to the characteristics of WPC products, a delicate design and thus optimization is highly required. A multi-objective-optimization program of micro-genetic algorithm was developed in Visual Basic environment to accomplish the optimization task. By specifying the dimensional variables of the profile section and applying finite elements analysis on the profile and then using the optimization program, an optimal profile section was obtained. The objective was to withstand the maximum load while yielding the minimum deflection and mass. The optimized design was used to manufacture a die and then the product was produced to validate the design. The comparison of simulations and experimental results indicted that the given design method is reasonably reliable. The final mass of the produced pallet was less than 20 kg whereas its strength against bending and distributed smooth restraint loading were greater than 500 kg and 2000 kg, respectively.     

Cost effective simulation-based multiobjective optimization in the performance of an internal combustion engine

Solving real-life engineering problems can be difficult because they often have multiple conflicting objectives, the objective functions involved are highly nonlinear and they contain multiple local minima. Furthermore, function values are often produced via a time-consuming simulation process. These facts suggest the need for an automated optimization tool that is efficient (in terms of number of objective function evaluations) and capable of solving global and multiobjective optimization problems. In this article, the requirements on a general simulation-based optimization system are discussed and such a system is applied to optimize the performance of a two-stroke combustion engine. In the example of a simulation-based optimization problem, the dimensions and shape of the exhaust pipe of a two-stroke engine are altered, and values of three conflicting objective functions are optimized. These values are derived from power output characteristics of the engine. The optimization approach involves interactive multiobjective optimization and provides a convenient tool to balance between conflicting objectives and to find good solutions.     

A transformation system for interactive reformulation of design optimization strategies

Automatic design optimization is highly sensitive to problem formulation. The choice of objective function, constraints and design parameters can dramatically impact on the computational cost of optimization and the quality of the resulting design. The best formulation varies from one application to another. A design engineer will usually not know the best formulation in advance. To address this problem, we have developed a system that supports interactive formulation, testing and reformulation of design optimization strategies. Our system includes an executable, data-flow language for representing optimization strategies. The language allows an engineer to define multiple stages of optimization, each using different approximations of the objective and constraints or different abstractions of the design space. We have also developed a set of transformations that reformulate strategies represented in our language. The transformations can approximate objective and constraint functions, abstract or reparameterize search spaces, or divide an optimization process into multiple stages. The system is applicable in principle to any design problem that can be expressed in terms of constrained optimization; however, we expect the system to be most useful when the design artifact is governed by algebraic and ordinary differential equations. We have tested the system on problems of racing yacht design and jet engine nozzle design. We report experimental results demonstrating that our reformulation techniques can significantly improve the performance of automatic design optimization. Our research demonstrates the viability of a reformulation methodology that combines symbolic program transformation with numerical experimentation. It is an important first step in a research program aimed at automating the entire strategy formulation process.     

进气系统微穿孔管消声器设计与优化

针对某车型进气系统在高转速时的宽频带进气噪声问题,提出了一种多腔微穿孔管消声器结构。根据传递矩阵法,建立了有流条件下多腔微穿孔管消声器传递损失计算模型;针对研究车型进气口噪声的频谱特性,采用多种群遗传算法对多腔微穿孔管消声器的结构参数进行优化设计,通过阻抗管台架和实车测试验证了消声器消声效果。结果表明,优化的多腔微穿孔管消声器能够有效拓宽降噪频带,消声器传递损失预测结果与实验测试结果一致,验证了所提出的传递损失计算模型的准确性及优化算法的有效性;在实车进气系统中采用该微穿孔管消声器后,进气噪声在600~1800 Hz中高宽频段以及200~400 Hz低频段均有明显降低,证实了所提出的多腔微穿孔管消声器的实际宽频消声特性。     

高速静压内置式电主轴系统稳定性分析及优化

针对高效精密机床电主轴系统的高速化,讨论液体静压主轴系统失稳机理,并对高速静压内置式电主轴系统进行稳定性分析;提出基于遗传算法的电主轴系统稳定性优化方法。以系统稳定性评价指标为优化目标、电主轴系统轴向尺寸参数为设计变量,采用高效微型遗传算法实现电主轴系统稳定性优化。该方法既能高效解决增强轴系稳定性优化问题,又可避免复杂结构参数修改;通过某高速磨床静压内置式电主轴系统稳定性分析及优化对该方法进行验证。结果表明,稳定性分析及优化后系统稳定性得到明显提高。     

Genetic particle swarm parallel algorithm analysis of optimization arrangement on mistuned blades

This article introduces a method of mistuned parameter identification which consists of static frequency testing of blades, dichotomy and finite element analysis. A lumped parameter model of an engine bladed-disc system is then set up. A bladed arrangement optimization method, namely the genetic particle swarm optimization algorithm, is presented. It consists of a discrete particle swarm optimization and a genetic algorithm. From this, the local and global search ability is introduced. CUDA-based co-evolution particle swarm optimization, using a graphics processing unit, is presented and its performance is analysed. The results show that using optimization results can reduce the amplitude and localization of the forced vibration response of a bladed-disc system, while optimization based on the CUDA framework can improve the computing speed. This method could provide support for engineering applications in terms of effectiveness and efficiency.     

Aerothermal shape optimization for a double row of discrete film cooling holes on the suction surface of a turbine vane

A multiple-objective optimization is implemented for a double row of staggered film holes on the suction surface of a turbine vane. The optimization aims to maximize the film cooling performance, which is assessed using the cooling effectiveness, while minimizing the corresponding aerodynamic loss, which is measured with a mass-averaged total pressure coefficient. Three geometric variables defining the hole shape are optimized: the conical expansion angle, compound angle and length to diameter ratio of the non-diffused portion of the hole. The optimization employs a non-dominated sorting genetic algorithm coupled with an artificial neural network to generate the Pareto front. Reynolds-averaged Navier–Stokes simulations are employed to construct the neural network and investigate the aerodynamic and thermal optimum solutions. The optimum designs exhibit improved performance in comparison to the reference design. The optimization methodology allowed investigation into the impact of varying the geometric variables on the cooling effectiveness and the aerodynamic loss.     

基于流场分析的某割草车节能优化设计

为了提高某割草车的工作效率,降低其长时间工作时的能源损耗,对其割台中的刀盘和刀片进行建模与仿真分析,通过对刀盘角区和刀片形状进行优化,达到节能的效果。首先,对割草过程中刀盘内的流场情况进行数值模拟,分析了刀片和刀盘所受的压力、刀片的速度以及刀片所受扭矩;其次,基于流场分析规律,对刀盘角区和刀片的形状进行优化,提出3个优化方案;然后,以扭矩的大小作为方案是否节能的主要评价指标,并与原方案进行对比分析,得到节能效果最优的设计方案;最后,将优化后的刀片加工成形,装在实车上进行试验,试验结果与仿真结果的误差小于5%,说明仿真结果正确,同时试验结果验证了该优化方案具有良好的节能效果。仿真与试验结果表明：刀片形状对割草机工作过程中的流场及扭矩等有重要影响,异形刀片有助于减小流场涡流与风阻,从而减小刀片上的扭矩,达到节能提效的目的。