基于计算智能的射孔枪结构优化设计方法

在对石油射孔枪结构进行有限元静、动力分析的基础上,利用BP神经网络对有限元分析得出的样本数据,建立射孔枪结构设计参数盲孔处的最大应力(输入)与盲孔深度、盲孔直径(输出)的全局性映射关系,获得遗传算法求解结构优化问题所需的目标函数值.最后,用改进的遗传算法进行射孔枪结构的优化设计.结果表明,基于神经网络和遗传算法的优化技术应用在射孔枪结构的优化设计中是有效、合理的.从广义的角度,作为结构优化问题求解方法的一个探讨,本文所提出的优化技术,也为工程领域中复杂、多变量,尤其是优化设计目标无法或难以表示成设计变量的显函数的优化问题的求解提供了新的思路和技术手段.     

基于多目标遗传算法的RITS物理结构优化设计

提出了RITS物理结构优化设计问题模型和基于多目标优化的解决思路。RITS结构优化设计待优化函数具有高维、多峰、非线性等特点，求解难度人。重点研究了一类基于Pareto机制的具有快速全局收敛能力的多目标遗传算法，并以紧急救援系统为例进行结构优化设计，验证了算法的有效性。     

ANSYS优化方法与遗传算法在结构优化方面的比较

以十杆桁架结构重量最轻的优化问题为基础,比较了遗传寻优结果与ANSYS(优化模块使用的是传统的优化方法)优化结果,数据对比分析结果表明,遗传算法在离散变量的结构优化方面比传统方法更容易找到全局性优化解。     

基于类桁架的多工况下平面Prager结构拓扑优化

为开展多工况下曲面结构的拓扑优化,采用两向正交类桁架连续体材料模型和有限元分析方法,以杆件在结点位置的密度和方向为优化设计变量进行结构优化。根据有限元分析结果,采用满应力准则法优化各单一工况下的材料分布。按照多工况与各单工况下材料的方向刚度最大值的差值最小为原则,优化多工况下的杆件方向和密度分布。将杆件竖直位置的质心连线作为拓扑优化的平面Prager结构,以3个算例表明该方法的有效性。     

桁架结构振动的主动模糊控制中主动杆数目与位置优化

研究了采用自适应模糊控制器抑制桁架结构振动时的主动杆数目与位置优化问题.通过定义输入能量相关矩阵优化了主动杆的数目.基于主动杆的控制能量配置准则,给出了主动杆优化配置的模型.研究基于整数编码的遗传算法用于大型离散体中的作动器组合优化问题.最后针对挠性空间智能桁架结构的振动控制仿真,使用基于整数编码的遗传算法(GAs)优化主动杆位置.结果表明对于采用自适应模糊控制律的离散体结构振动控制是行之有效的.     

智能算法在齿轮传动优化设计的应用

以齿轮优化设计为例，分别得出用传统机械设计优化方法和用遗传算法与神经网络协同求解的结果，并进行了比较，体现了遗传算法与神经网络协同求解的特点。结果表明．该方法是非常有效的，在求解优化设计时取得了较为满意的结果。     

基于Metropolis遗传算法的并联机器人结构优化设计

以六自由度Stewart并联机器人的灵巧度为目标函数,以设计空间、每条支腿的最大最小长度之比和虎克铰、球铰的极限摆角为约束条件建立了结构优化模型．将模拟退火算法中的Metropolis准则引入到实值编码遗传算法的选择操作中,产生了Metropolis遗传算法,采用该算法进行了并联机器人结构优化问题的求解．通过与采用标准遗传算法得出的结果比较,证实了Metropolis遗传算法在并联机器人结构优化设计中的有效性和优越性．     

基于遗传算法的信息系统可靠性优化设计

设备冗余是信息系统进行可靠性优化设计的常用策略之一,其主要问题在于冗余设备的选择和配置,以达到满足一定可靠性要求下实现成本最小化的目的。这是一类结构复杂的规划问题,很难采用传统的数值算法进行求解,遗传算法提供了有效的解决方法。首先运用信息系统Petri网模型的层次结构分析结果,给出区分结点重要度的系统可靠性度量公式。在此基础上提出优化模型,给出遗传算法求解优化问题的步骤,并通过实例证明了方法的有效性及实用性。     

改进的群搜索优化算法在结构优化中的应用

针对桁架结构优化设计问题,对群搜索优化算法（GSO）进行了算法修改和参数调整,并将修改后的算法应用到10杆、17杆和200杆共3个桁架结构截面优化设计算例中,同时与另一种GSO改进算法（IGSO）进行了对比分析。对于每个算例,该文改进算法和IGSO算法各运行了10次,从10次运行的统计结果可以看出,改进算法的优化效果和稳定性均好于IGSO算法。另外,改进算法也与目前结构优化中较好的其它几个算法进行了比较,总体来说,改进算法的最佳优化结果与这些算法的最佳结果相当。     

改进的群搜索优化算法在结构优化中的应用

针对桁架结构优化设计问题,对群搜索优化算法(GSO)进行了算法修改和参数调整,并将修改后的算法应用到10杆、17杆和200杆共3个桁架结构截面优化设计算例中,同时与另一种GSO改进算法(IGSO)进行了对比分析。对于每个算例,该文改进算法和IGSO算法各运行了10次,从10次运行的统计结果可以看出,改进算法的优化效果和稳定性均好于IGSO算法。另外,改进算法也与目前结构优化中较好的其它几个算法进行了比较,总体来说,改进算法的最佳优化结果与这些算法的最佳结果相当。     

An improved differential evolution based on roulette wheel selection for shape and size optimization of truss structures with frequency constraints

Structural optimization with frequency constraints is well known as a highly nonlinear and complex optimization problem with many local optimum solutions. Therefore, to solve such problems effectively, designers need to use adequate optimization methods which can make a good balance between the computational cost and the quality of solutions. In this work, a novel differential evolution (DE) is proposed to solve the shape and size optimization problems for truss structures with frequency constraints. The proposed method, called ReDE, is a new version of the DE algorithm with two improvements. Firstly, the roulette wheel selection is employed to choose members for the mutation phase instead of random selection as in the conventional DE. Secondly, an elitist selection technique is applied to the selection phase instead of basic selection to improve the convergence speed of the method. The efficiency and reliability of the proposed method are demonstrated through five numerical examples. Numerical results reveal that the proposed algorithm outperforms many optimization methods in the literature.

     

基于螺旋运动的智能优化算法研究

螺旋结构是自然界中经常出现的一种结构,螺旋结构因其特殊的运动轨迹、天然的收敛性而受到智能优化算法研究人员的关注.在螺旋动态优化算法(SDA)的基础上,提出一种基于组合螺旋和FDB选择策略的改进螺旋算法(MSPO),克服SDA的弊端,大大减小了时间复杂度、简化运算过程,提高了普适性和收敛精度.最后在八个具有代表性的基准函数上进行实验,实验结果表明,MSPO在收敛精度、收敛速度及鲁棒性上都表现出了更好的性能.同时将其运用在10杆和25杆的连续性桁架结构尺寸优化上,仿真实验表明,MSPO能很好地解决这类结构优化问题.     

管桁架设计软件开发

针对管桁架设计过程中绘图工作量大、出错率高、效率低等问题,利用．Net和ObjectARX在AutoCAD 2004中实现管桁架结构设计软件．介绍开发该软件的总体思路、构架和数据存储及基本功能．该软件将三维实体模型应用到管桁架后处理系统之中,通过对实体模型消隐来出图,可以大大减少人工绘图的工作量．     

Combined size and shape optimization of structures with a new meta-heuristic algorithm

In this study, a new meta-heuristic algorithm called teaching-learning-based optimization (TLBO) is used for the size and shape optimization of structures. The TLBO algorithm is based on the effect of the influence of a teacher on the output of learners in a class. The cross-sectional areas of the bar element and the nodal coordinates of the structural system are the design variables for size and shape optimization, respectively. Displacement, allowable stress and the Euler buckling stress are taken as the constraint for the problem considered. Some truss structures are designed by using this new algorithm to show the efficiency of the TLBO algorithm. The results obtained from this study are compared with those reported in the literature. It is concluded that the TLBO algorithm presented in this study can be effectively used in combined size and shape optimization of the structures.     

A swift technique for damage detection of determinate truss structures

In this study, a novel two-stage approach for damage detection of determinate truss structures is proposed. The method lies in the group of vibration-based methods but it just needs the first natural frequency and mode shape vector of these structures for identifying the location and severity of damage. In the first stage, the modal residual force vector for different modes of a structure is introduced and the one associated with the first mode is applied to the structure as an external nodal force vector. Then, the residual local nodal force vector can be computed for all elements of the structure. Next, the elements with non-zero residual internal force are considered as damaged elements. In the second stage, the damage severity of each damaged element is determined using a new relation which can be categorized as a force–displacement relation. To show the efficiency and simplicity of the proposed method, three truss structures including a 13-bar planar truss, a 29-bar planar truss, and a 77-bar planar truss under different damage scenarios are studied; the results of which indicate that the method is innovatively capable of suitably detecting, for determinate truss structures, not only damaged members but also their individual damage severity by carrying solely one analysis.

     

压电自适应桁架结构智能振动控制

介绍了采用模糊神经网络模型进行振动主动控制的压电自适应桁架结构设计、应用及实验结果. 设计了一种具有自适应结构技术的压电主动构件结构, 并提出了具有5层结构能够自调整隶属函数的模糊神经网络控制模型. 为了验证控制模型的有效性, 搭建了配置压电主动构件的双跨桁架结构试验平台, 通过检测误差信号, 由模糊神经网络控制模型确定主动构件的驱动输出. 试验结果证实了模糊神经网络控制模型在振动抑制方面的有效性.     

A hybrid CBO–PSO algorithm for optimal design of truss structures with dynamic constraints

The vibration domain of structures can be reduced by imposing some constraints on their natural frequencies. For this purpose optimal design of structures under frequency constraints is required which involves highly non-linear and non-convex problems. In this paper an efficient hybrid algorithm is developed for solving such optimization problems. This algorithm utilizes the recently developed colliding bodies optimization (CBO) algorithm as the main engine and uses the positive properties of the particle swarm optimization (PSO) algorithm to increase the efficiency of the CBO. The distinct feature of the present hybrid algorithm is that it requires no parameter tuning. The CBO is known for being parameter independent, and avoiding the use of the traditional penalty method to handle the constraints upholds this property. Two mathematical constrained functions taken from the literature are studied to verify the performance of the algorithm. The algorithm is then applied to optimize truss structures with frequency limitations. The numerical results demonstrate the efficiency of the presented algorithm for this class of problems.     

粒子群优化算法在桁架结构优化中的应用

介绍了粒子群优化（PSO）算法的一种改进算法：用于约束优化问题的启发式粒子群优化（HPSO）算法。针对HP-SO算法在桁架结构优化中速度较慢的问题,将HPSO算法的约束处理策略与另一种适用于粒子群算法的约束处理方法结合,并将改进后的算法应用到1个桁架结构截面优化设计算例中,同时与HPSO算法进行对比分析。对于此算例,改进算法和HPSO算法都运行了多次,从多次运行的统计分析中可以看出,改进算法的优化效果和稳定性好于HPSO算法,且结构分析的次数减少了一半左右,从而整个程序运行的速度比HPSO算法提高了将近一倍。     

Finite topology variations in optimal design of structures

The method of optimal design of structures by finite topology modification is presented in the paper. This approach is similar to growth models of biological structures, but in the present case, topology modification is described by the finite variation of a topological parameter. The conditions for introducing topology modification and the method for determining finite values of topological parameters characterizing the modified structure are specified. The present approach is applied to the optimal design of truss, beam, and frame structures. For trusses, the heuristic algorithm of bar exchange is proposed for minimizing the global compliance subject to a material volume constraint and it is extended to volume minimization with stress and buckling constraints. The optimal design problem for beam and frame structures with elastic or rigid supports, aimed at minimizing the structure cost for a specified global compliance, is also considered.     

Optimization of nonlinear trusses using a displacement-based approach

A displacement-based optimization strategy is extended to the design of truss structures with geometric and material nonlinear responses. Unlike the traditional optimization approach that uses iterative finite element analyses to determine the structural response as the sizing variables are varied by the optimizer, the proposed method searches for an optimal solution by using the displacement degrees of freedom as design variables. Hence, the method is composed of two levels: an outer level problem where the optimal displacement field is searched using general nonlinear programming algorithms, and an inner problem where a set of optimal cross-sectional dimensions are computed for a given displacement field. For truss structures, the inner problem is a linear programming problem in terms of the sizing variables regardless of the nature of the governing equilibrium equations, which can be linear or nonlinear in displacements. The method has been applied to three test examples, which include material and geometric nonlinearities, for which it appears to be efficient and robust. Received December 4, 2000