Optimization of Off-Centre bracing system using Genetic Algorithm

In this paper, a method based on genetic algorithm is proposed for determining the optimum connection point with the highest lateral buckling load in the Off-Centre bracing system. This type of bracing system is mostly used in seismic areas and it allows architects to have more openings in the panel area. In this system, the non-straight diagonal member introduces eccentricity to the system and is connected to the corner of the frame by a third member. In designing this system, designers often use “trial and error” to locate the connection point of the brace elements considering various parameters affecting the design such as opening and frame dimensions, cross sectional areas of brace elements and the location of the brace element connection. Hence, finding the best connection point with maximum lateral buckling load can be problematic by the conventional methods. To demonstrate the effectiveness of the proposed GA method, examples with different frame specifications were presented.     

基于遗传算法的结构可靠度分析方法

针对结构发展需要,介绍一种智能化的可靠度分析方法——遗传算法(GAM)。通过一个例题,使用Matlab 语言编程仿真,分析 GAM 求解结构可靠度的可行性,详细阐述采用十进制编码的实现方法,以及求解约束收敛适应度的自适应调整方法,经对淘汰法则的优化,提高求解的收敛速度。     

卵形消化池内力分析及基于遗传算法的形状优化

本文以静水压力作用下卵形消化池壳体的薄膜内力为基础 ,建立以体表面积为目标函数 ,以容积、高度 ,应力等为约束条件的优化模型。使用遗传算法对以上模型进行优化 ,并引进动态罚函数和对约束条件不断逼近的方法处理约束条件。从而为初步设计阶段卵形消化池形状的设计提供了建议和参数。     

Optimization of indoor climate conditioning with passive and active methods using GA and CFD

This study aims at the development of an optimal design tool using a genetic algorithm (GA) and computational fluid dynamics (CFD). Random variables (fluctuating outdoor conditions), passive design elements (model variables) and active design elements (HVAC system) were set up to represent a realistic building environment. A combination of designs is determined based on the relationship between fluctuating outdoor conditions and the HVAC system in the optimal design search. Building environment designs should consider both active and passive design elements because the HVAC system keeps adjusting the supply air flow rate until the indoor climate reaches target conditions when outdoor conditions are changing.     

Fuzzy optimization of cold-formed steel sheeting using genetic algorithms

In this paper, genetic algorithms are applied for optimization of dimensions of cold-formed steel trapezoidal sheeting. The objective of the optimization is to obtain the minimum weight subjected to the given constraints in accordance with Eurocode 3, Part 1.3. In traditional optimization, these constraints are defined with crisp number. However, in practical engineering, constraints with a small certain percentage of violation can be acceptable. Thus, in this research, sheeting is optimized to satisfy the constraints considering the fuzziness so that the optimization is more practical from the engineering point of view. The better performance of introducing the fuzziness into a constraints-handling technique has been demonstrated with a design example.     

基于模式识别的混凝土泵车臂架壁厚优化

选取某型号泵车臂架作为研究对象,分析了固有频率对其工作性能的影响。利用Pro/Engineer软件建立臂架系统模型,改变臂架尺寸参数,导入Pro/MECHANICA模块中进行模态分析,利用Matlab的遗传函数工具箱对得到数据进行模式识别,筛选出相关变量,建立尺寸与一阶固有频率的函数关系,可针对性地对某些尺寸进行优化,对臂架系统的设计提供了参考。     

基于遗传算法优化SVM的刀具VB值预测的研究

针对刀具磨损量的预测问题,建立了基于支持向量机回归理论的刀具VB值的在线预测模型。对声发射信号和电流信号分别进行EEMD分解和小波包分解得到的能量值,把它与主轴转速、进给量和背吃刀量一起组成初始特征向量。通过主成分分析进行数据处理,把得到主元作为遗传算法优化的支持向量回归机的输入向量。结果表明,该模型精度高,运行速度快。     

多排料方案下的加工排程优化研究

结合工程机械中金属结构件的加工特点,针对金属结构件生产过程中多任务混合下料与加工排程优化问题,提出多种排料方案下的带工艺约束多目标加工排程优化模型,并设计一种蚁群--递阶遗传算法来求解该模型。该算法首先利用蚁群算法选择一组优异的排料方案,然后利用递阶遗传算法的选择、交叉、变异等操作求解作业加工顺序及机器选择问题。通过对加工排程的优化,缩短金属结构件产品生产周期,降低其在制品数量和提高设备利用率,并通过实例分析证明了该方法的有效性。     

全液压制动系统充液阀性能仿真与结构优化研究

充液阀作为全液压制动系统中的关键部件,其充液速度、充液压力等特性对整个系统的性能有直接的影响,为了系统研究结构参数对充液阀工作特性的影响,借助AMESim软件平台建立了全液压制动系统的仿真模型,并利用所搭建的全液压制动系统试验台,验证了仿真模型的有效性。在此基础上,分析了充液阀不同结构参数对充液特性的影响规律,结果表明,主阀弹簧刚度和阀芯节流孔径的改变会影响充液响应时间;控制阀的阀套夹角、钢球直径及调压弹簧刚度是决定充液压力上、下限的关键参数。依据上述结果,利用遗传算法对充液阀的主要结构参数进行了优化,结果表明,优化后的充液时间由2.8s缩短至2.0s,充液响应特性得到较大改善。