基于风洞试验成果的大跨度网壳结构优化

以某大跨度网壳结构为研究对象,对建筑结构进行了风洞试验.将风洞试验体型系数结果引入大跨度网壳结构并优化设计.应用复形法建立了网壳结构目标函数,初步拟定网壳结构的网格尺寸、网壳厚度、网壳矢高,以杆件的截面面积为设计变量,杆件的强度和最小截面尺寸为约束条件,并编制了相应的程序,对三圆弧网壳结构外形尺寸进行多种方案的优化设计,比较试验与规范风载体型系数优化结果,为类似网壳结构设计提供参考.     

单层球面网壳的优化设计

提出了针对单层球面网壳结构的一种优化设计方法,它是一种以网壳的总造价为目标函数,取网壳的网格数、矢高、杆件截面面积和节点体积作为优化设计变量,采取直接搜索法与准则法相结合的优化设计方法.基于用Fortran90软件编制的优化设计程序,对单层球面网壳结构进行了大量的计算,用回归分析得出网壳最优网格数、矢高、杆件截面面积和节点体积,同时使杆件面积规格化,以便直接用于实际工程.     

单层球面网壳的优化设计

提出了单层球面网壳结构的一种优化设计方法 ,它是一种以网壳的总造价为目标函数 ,取网壳的网格数、矢高、杆件截面面积和节点体积作为优化设计变量 ,采取直接搜索法与准则法相结合的优化设计方法 .基于用 Fortran90软件编制的优化设计程序 ,对单层球面网壳结构进行了大量的计算 ,用回归分析得出网壳最优网格数、矢高、杆件截面面积和节点体积 ,同时使杆件面积规格化 ,以便直接用于实际工程     

单层球面网壳选型优化设计

采用改进的自适应遗传算法来解决单层球面网壳结构构件截面优化问题,并采用VC＋＋语言编写了相应的自适应遗传算法和有限元计算程序,可以实现单层球面网壳结构的自动优化设计。设计了不同类型、跨度和矢跨比的网壳优化算例;并通过对按照现行相关规范优化设计的单层球面网壳和符合现行相关规范要求但未经优化设计的单层球面网壳用ANSYS软件进行考虑几何非线性的屈曲分析,分别确定其屈曲荷载与设计荷载之比,以比较它们的受力和安全性能。结果表明采用自适应遗传算法进行离散变量的网壳结构截面优化设计容易收敛,优化效果良好。如果综合考虑经济和安全因素,设计网壳时,其矢跨比取1／6～1／5比较合适。     

ANSYS环境下的网壳结构优化设计

以大型通用有限元分析软件ANSYS作为运行环境,介绍了ANSYS中结构优化的方法及步骤、网架优化设计中设计变量、状态变量及目标函数的选取.将网壳结构的杆件截面面积作为设计变量,以网壳结构的总质量为目标函数,同时考虑网壳结构的强度、刚度、稳定性、杆件截面尺寸等约束条件,以塔里木油田分公司塔里木生活基地体育馆工程中的球类馆为工程实例,分别在恒载 活载和风荷载两种工况下,对六榀主拱桁架用到的14种钢管截面进行优化,取得了较明显的效果.     

基于离散变量的大跨度钢桁架网壳优化设计

以大型通用有限元软件ANSYS为运行环境,以杆件截面为设计变量,以工程造价为目标函数,采用基于离散变量的满应力法中的应力比法对大跨度空间网架结构进行截面优化设计。同时考虑网架结构的强度、刚度、稳定性、杆件截面尺寸等约束条件。采用FORTRAN语言编制网架优化程序与ANSYS接口。以某煤炭工业厂房的大跨度空间筒壳结构为工程实例,对其进行优化设计,取得了较明显的效果。     

基于APDL的大跨度圆柱面网壳结构优化设计

以三心圆柱面网壳结构为例,采用通用有限元分析软件ANSYS的二次开发语言APDL为开发工具,将网壳结构的杆件截面积和厚度作为离散型设计变量,以网壳结构的总质量作为目标函数,并考虑网壳的强度、稳定、挠度以及截面规格等约束条件,采用改进的一维搜索算法和满应力准则法对网壳结构进行优化。工程实例表明,该优化设计原理简单,收敛速度快。     

基于离散变量的桁架结构截面优化及软件实现

以杆件横截面为设计变量,以结构重量为目标函数,采用基于离散变量的序列两级优化方法对桁架结构进行优化设计;在优化设计过程中采用了0阶修正,并且利用PCL语言在有限元软件MSC．NASTRAN和MSC．PATRAN上开发出了解决含应力约束和位移约束的桁架结构离散截面优化问题的程序。     

双层双曲线形网壳结构冷却塔的优化研究

采用了满应力法对应用于冷却塔的双层双曲线形网壳结构进行了杆件截面的优化设计 ,建立了以结构的自重为最小目标函数的空间网壳数学模型 ,详细介绍了优化的实施步骤 ,同时利用VisualBasic6.0编制了该竖向网壳的杆件截面优化程序 ,并用该程序对具体的工程实例进行优化设计 ,并对优化后的杆件截面进行了几种荷载组合的内力分析 ,而且比较了几种荷载组合的分析结果 ,得到了一些有实用价值的结论     

拉索网壳结构优化设计的快速方法

探讨了以预应力和截面尺寸为设计变量的拉索网壳结构优化设计问题.建立了拉索网壳结构提高承载力的线性规划模型,提出了拉索网壳结构优化设计的序列线性规划法,优化方法采用单纯型法和准则法.算例表明该方法具有较好的计算效率和收敛性.     

Novel decoupled framework for reliability-based design optimization of structures using a robust shifting technique

In a reliability-based design optimization (RBDO), computation of the failure probability (P_f) at all design points through the process may suitably be avoided at the early stages. Thus, to reduce extensive computations of RBDO, one could decouple the optimization and reliability analysis. The present work proposes a new methodology for such a decoupled approach that separates optimization and reliability analysis into two procedures which significantly improve the computational efficiency of the RBDO. This technique is based on the probabilistic sensitivity approach (PSA) on the shifted probability density function. Stochastic variables are separated into two groups of desired and non-desired variables. The three-phase procedure may be summarized as: Phase 1, apply deterministic design optimization based on mean values of random variables; Phase 2, move designs toward a reliable space using PSA and finding a primary reliable optimum point; Phase 3, applying an intelligent self-adaptive procedure based on cubic B-spline interpolation functions until the targeted failure probability is reached. An improved response surface method is used for computation of failure probability. The proposed RBDO approach could significantly reduce the number of analyses required to less than 10% of conventional methods. The computational efficacy of this approach is demonstrated by solving four benchmark truss design problems published in the structural optimization literature.     

Structural optimization of filament wound composite pipes

An optimization procedure is developed for obtaining optimal structural design of filament wound composite pipes with minimum cost utilized in pressurized water and waste-water pipelines. First, the short-term and long-term design constraints dictated by international standards are identified. Then, proper computational tools are developed for predicting the structural properties of the composite pipes based on the design architecture of layers. The developed computational tools are validated by relying on experimental analysis. Then, an integrated design-optimization process is developed to minimize the price as the main objective, taking into account design requirements and manufacturing limitations as the constraints and treating lay-up sequence, fiber volume fraction, winding angle, and the number of total layers as design variables. The developed method is implemented in various case studies, and the results are presented and discussed.     

Controllability analysis as a pre-selection method for sensor placement in water distribution systems

Detection of contamination events in water distribution systems is a crucial task for maintaining water security. Online monitoring is considered as the most cost-effective technology to protect against the impacts of contaminant intrusions. Optimization methods for sensor placement enable automated sensor layout design based on hydraulic and water quality simulation. However, this approach results in an excessive computational burden. In this paper we outline the application of controllability analysis as preprocessing method for sensor placement. Based on case studies we demonstrate that the method decreases the number of decision variables for subsequent optimization dramatically to app. 30 to 40 percent.     

Safety analysis of structures with probability and evidence theory

In safety analysis of structures, classical probabilistic analysis has been a popular approach in engineering. However, it is not always to obtain sufficient information to model all uncertain parameters of structures system by probability theory, especially at early stage of design. Under this circumstance, probability theory (used to model random uncertainty) combined with evidence theory (used to model epistemic uncertainty) may be utilized in safety analysis of structures. This paper proposed a novel method for safety analysis of structures based on probability and evidence theory. Firstly, Bayes conversion method is used as the way for precision of evidence body, and the mean and variance of epistemic uncertain variables is defined. Then epistemic uncertainty variables is transformed to normal random variables by reflection transformation method, and the checking point method (J-C method) is used to solve most probability point and reliability. A numerical example and two engineering examples are given to demonstrate the performance of the proposed method. The results show both precision and computational efficiency of the method is high. Moreover, the proposed method provides basis for reliability-based optimization with the hybrid uncertainties.     

Optimization of variables in air conditioning control systems: Applications of simulations integrating CFD analysis and response factor method

The integration of three-dimensional spatial distributions into building simulations is of significant interest, and computational fluid dynamics (CFD) analysis is widely employed in building design processes. For example, based on the experience of architects and engineers, CFD analyses are often conducted under steady boundary conditions to determine the degree of attainment of indoor environments. However, CFD analyses have large calculation costs and cannot be often used for simulations with unsteady boundary conditions such as energy simulations in the building design processes. Thus, we developed a method that calculates sensitivities from heat sources to an arbitrary point in an indoor environment and integrates them into simulations with unsteady boundary conditions. In the proposed method, CFD analysis is employed under steady boundary conditions to calculate the response factors, and the resulting sensitivities are integrated into simulations under unsteady boundary conditions. In the present study, the proposed method was applied to optimize the variables of an air conditioning control system. With our method, temperature changes at a sensor over time are calculated from the time series of air supply temperature. In total, 800 calculations were conducted, and the optimal variables that allow the temperature at the sensor to reach the target value quickly were obtained. Except for the time required to calculate the response factors, the optimization in the present study took only a few seconds. If only CFD analysis was used for the optimization, the calculations would take a year. Thus, calculating the sensitivities via CFD analysis and utilizing the results in simulations is a useful approach for solving optimization problems. Moreover, the proposed method is applicable to simulations that require three-dimensional spatial distributions to enhance the accuracy of the calculation such as energy simulations.     

Direct computation of the design point of a stochastic structure using a finite element code

In a probabilistic analysis of a stochastic structure, it is important to identify the design point—the point of most probable failure. When both the resistance and load term of the limit state function are random, a modified joint probability density function is formulated, and the design point is obtained by searching for the maximum point of this function. The modification is done by introducing the finite element solution for the load term into the original basic joint probability density function of the random variables. For threshold value problems, the design point is obtained by searching for the maximum point of the original joint probability function, conditional upon the finite element solution being equal to the threshold value. Once the design point is identified, the index of reliability can be found using known techniques for structures with independent and dependent random variables, normally and non-normally distributed. The solution is obtained without the need for any derivatives of the load term with respect to the random variables, thus no modifications are required in the finite element code used. The solution requires an algorithm that finds the maximum value of the objective function in a well defined variable space. Several numerical examples are presented, including cases of random fields, which are discretized by stochastic finite element into random variables. The library module of design optimization of the finite element code employed (ANSYS) is used to find the design point. Applying the proposed method permits the designer to perform probabilistic analysis with computational tools already available.     

钢筋混凝土框架梁基于可靠度理论的抗震优化设计

基于现行建筑抗震设计规范 ,把设计变量 (荷载、材料强度和几何尺寸 )看作随机变量 ,针对钢筋混凝土框架梁进行优化设计。目的是使设计的梁在满足现行规范要求的基础上 ,能保持一致的可靠性 ,同时使设计造价达到最小。文中可靠度分析和优化计算都基于Monte Carlo随机模拟方法。     

张拉薄膜结构的形态优化设计

在张拉膜结构形态分析概念的基础上 ,提出了对该类结构的优化设计的思想 ,结合遗传算法的基本概念提出了适用于张拉膜结构的优化算法 ,并编制了相应的计算程序。结合两个具体验证性算例 ,对张拉膜结构优化设计的概念和方法作了进一步的说明     

预应力局部单双层扁网壳的参数分析与近似优化

预应力局部单、双层扁网壳具有较好的室内视觉效果和良好的经济性。其结构参数的确定属多级别优化问题,实施困难。为满足初步设计的需要,提出采用均匀设计法进行结构的参数分析与近似优化。它可利用现有软件来实现。作为算例,对一个柱支承预应力扁网壳进行了参数分析,得到了网壳用钢量、变形和极限荷载系数与三个主要设计参数(单层部分材料设计应力折减系数、单层部分范围和预应力值)之间的近似函数关系,并找出了满足规范要求的各参数之间的较理想的最优水平组合。设计检验说明了分析结果的可靠性。该方法可为解决类似优化问题提供参考。