基于SLP方法的框架全约束优化

探讨了钢筋混凝土框架结构整体优化,并考虑了最大层间位移角的约束,在SLP优化方法的思路上,编制了框架优化程序和内力计算程序。通过算例验证,该方法对小型框架结构具有一定的可行性,而且可以看出,框架结构整体优化较能合理分配刚度。最后,对框架结构整体全约束优化提出了自己的看法。     

A nonlinear projection method for constrained optimization

An algorithm is presented for the solution of nonlinear optimization problems involving locally differentiable functions with known analytical expressions. The algorithm is based on perturbation methods of system analysis and develops from a set of easy to implement procedures designed to detect and solve the activation and deactivation of constraints while selecting the steepest feasible trajectory and the largest step length. Numerical applications are presented to illustrate the performance of the algorithm.     

Bridge design with reserve and residual reliability constraints

System reliability is evolving as an important design method for selecting components and topology. It should be used to investigate the original intact structure behavior as well as providing sufficient reserve capacity under likely accident and damage scenarios. Highway bridges are an area of special concern since effort to optimize the cost of construction may not provide adequate redundant capacity. The paper describes an example in which a typical girder bridge structure is optimized (both size and girder spacing) to achieve target system performance. System reliability constraints are imposed on the behavior of the intact structure under highway loads. Also, residual system reliability constraints are imposed to control safety under specified accident scenarios corresponding to damage and “lost” members due to corrosion, fatigue, fire or accidental collisions. An optimal design framework for controlling safety under all these life cycle situations is thus provided.     

Reliability-based design optimization using convex linearization and sequential optimization and reliability assessment method

In this study, an effective method for reliability-based design optimization (RBDO) is proposed enhancing sequential optimization and reliability assessment (SORA) method by convex linearization. In SORA, reliability estimation and deterministic optimization are performed sequentially. And the sensitivity and function value of probabilistic constraint at the most probable point (MPP) are obtained in the process of finding reliability information. In this study, the convex linearization is constructed by utilizing the sensitivity and function value of the probabilistic constraint at the MPP. So no additional evaluation of the probabilistic constraint is required in the deterministic optimization in SORA. The proposed RBDO method is applied to numerical examples and compared to various RBDO methods. It is shown that the proposed method is very efficient with similar accuracy.     

A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization

In solving optimization problems for building design and control, the cost function is often evaluated using a detailed building simulation program. These programs contain code features that cause the cost function to be discontinuous. Optimization algorithms that require smoothness can fail on such problems. Evaluating the cost function is often so time-consuming that stochastic optimization algorithms are run using only a few simulations, which decreases the probability of getting close to a minimum. To show how applicable direct search, stochastic, and gradient-based optimization algorithms are for solving such optimization problems, we compare the performance of these algorithms in minimizing cost functions with different smoothness. We also explain what causes the large discontinuities in the cost functions.     

A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

Integrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently.Many multi-objective optimization algorithms have been developed;however few of them are tested in solving building design problems.This paper compares performance of seven commonly-used multi-objective evolutionary optimization algorithms in solving the design problem of a nearly zero energy building(n ZEB) where more than 1.610 solutions would be possible.The compared algorithms include a controlled non-dominated sorting genetic algorithm witha passive archive(p NSGA-II),a multi-objective particle swarm optimization(MOPSO),a two-phase optimization using the genetic algorithm(PR_GA),an elitist non-dominated sorting evolution strategy(ENSES),a multi-objective evolutionary algorithm based on the concept of epsilon dominance(ev MOGA),a multi-objective differential evolution algorithm(sp MODE-II),and a multi-objective dragonfly algorithm(MODA).Several criteria was used to compare performance of these algorithms.In most cases,the quality of the obtained solutions was improved when the number of generations was increased.The optimization results of running each algorithm20 times with gradually increasing number of evaluations indicated that the PR_GA algorithm had a high repeatability to explore a large area of the solution-space and achieved close-to-optimal solutions with a good diversity,followed by the p NSGA-II,ev MOGA and sp MODE-II.Uncompetitive results were achieved by the ENSES,MOPSO and MODA in most running cases.The study also found that 1400-1800 were minimum required number of evaluations to stabilize optimization results of the building energy model.     

商业综合体的疏散设计问题与优化措施

对某商业综合体进行疏散模拟,通过分析其人员疏散过程,发现该商业综合体的疏散走道中存在“瓶颈现象”、不平滑拐角的堵塞现象以及“T”形或“Y”形汇合处的集聚现象。分别采取增大瓶颈的宽度、改变走道轮廓线形状、适当扩大汇合处宽度形成缓冲区的措施进行优化,优化效果良好。此外,该商业综合体的安全出口、楼梯利用率较低。通过协调各出口的疏散宽度,使各安全出口的疏散同步进行,可以提高安全出口的利用率;将疏散利用率相差较大的相邻楼梯合并,可大幅度提高楼梯的疏散效率。     

A multi-objective structural optimization method for serviceability design of tall buildings

Structural optimization design aims to identify optimal design variables corresponding to a minimum objective function with constraints on performance requirements. To this end, many optimization frameworks have been proposed to determine optimal structural systems that are subjected to seismic and wind hazards in isolation. However, some modern tall buildings are sensitive to seismic and wind excitation owing to their complex structural systems and geographic regions. Therefore, a proper structural optimization method for such buildings is required to ensure that the expected performance is achieved in a multi-hazard scenario. This study proposes a multi-objective serviceability design optimization methodology for buildings in multi-hazard seismic and wind environments by combining optimality criteria and the nondominated sorting genetic algorithm II (NSGA-II). Seismic and wind effects can be instantaneously updated due to changes in the structural dynamic properties during the optimal design process. A neural-network-based surrogate model with self-updating is proposed to predict the structural natural frequency so that the overall computation time of the optimization process can be reduced. The proposed method was used to optimize a 50-story frame-tube building and was compared against the general genetic algorithm and general NSGA-II to verify the feasibility and effectiveness.     

System reliability theory based multiple-objective optimization model for construction projects

Although the system reliability theory has a high capability in quality quantification, while system reliability optimization (SRO) has been well developed in manufacturing engineering, seldom can their applications be found in the construction industry. This study aims to develop a system reliability theory based multiple-objective optimization model to conduct SRO, and then identify the cost–quality trade-off solution for construction projects. First, the whole construction project is treated as a system composed of different work packages. Second, the reliability function is employed to quantify the quality performance and the nonlinear cost-reliability function is set up. Moreover, according to the physical arrangements among each work package, the system reliability structural function is determined. Third, the total construction cost minimization and system reliability maximization are defined as multiple-objectives. The particle swarm optimization algorithm is employed to search for the Pareto-optimal solutions, from which the final cost–quality trade-off solution can be selected. A real construction case is used to evaluate the workability of the proposed model and the results have fully proven its validity and practicality.     

A simulation-based method for effective workface planning of industrial construction projects

The generation of well-defined and moderately sized field installation work packages for the construction workforce, referred to as workface planning, has been recently employed to plan large-scale industrial construction projects under tight schedules. However, traditional CPM-based scheduling of several thousand work packages (e.g. 5000 activities multiply by 10 work packages per activity on average) is a tedious, error prone process. Defining proper logics and controlling congestion among work packages crossing several work areas, and also effective resource allocation over time are other major challenges in workface planning. This paper presents a novel simulation-based framework to implement workface planning for large-scale industrial construction projects. This framework proposes a time-stepped discrete event simulation-based modelling for dynamic resource allocation based on congestion and other constraints on the job site. The proposed method is demonstrated and tested against traditional CPM-based solutions based on an actual case study.     

基于可靠度的桥梁结构优化研究

介绍了确定性设计与概率设计,进行了基于可靠度的桥梁结构优化研究,给出了基于可靠度的桥梁结构优化模型,指出只有采用以结构可靠度概率为依据的概率设计方法,才能得到真正符合客观实际的设计方案。     

盖挖法地铁车站设计问题的探讨

从设计方面对采用盖挖法施工的地铁车站所涉及到的若干问题进行了讨论,包括主体与围护结构的结合形式、盖挖中间支承柱的选择、车站顶板与围护结构连接形式等,从而完善采用盖挖法施工的地铁车站设计。     

基于约束多目标优化算法的盾构隧道设计方法

当前盾构隧道的设计仍主要依托于经验确定设计参数,然后对其安全性进行校核,难以定量的考虑成本和控制指标(收敛变形等)的关系。以衬砌厚度、截面配筋率、横向接头螺栓直径为设计参数,以成本及结构的水平收敛变形为优化目标,结合多目标优化的算法,进行了盾构隧道的横断面设计。采用非支配原理,通过引入约束违反函数,实现了基于NSGA-Ⅱ算法的复杂约束条件处理。最后通过具体算例,完成了满足截面安全性要求的限制条件下,完整Pareto前沿面的获取工作,并与无约束优化结果进行了分析对比,说明了迭代过程的收敛性,阐述了所得Pareto前沿面的价值意义,得到了不同设计条件下的最优解。     

钢框架结构基于整体优化策略的非线性抗震设计

针对现有抗震优化设计很少考虑结构非线性反应的缺点,提出了整体优化策略,并运用到钢框架结构造价最小的抗震优化设计中。以结构构件截面尺寸为设计变量,结构构件的总体积为目标函数,整体优化策略在以结构弹性强度和弹性变形为约束条件的基础上,增加弹塑性变形为约束条件,与我国抗震设计规范两阶段设计方法相对应,因此基于整体优化策略的优化设计结果可以作为最终的结构设计方案。整体优化策略不仅能够考虑结构的非线性反应,而且可以采用我国抗震规范的相关规定作为约束条件,适用于钢框架结构造价最小的抗震优化设计。     

基于目标可靠度的公路土质边坡设计方法研究

综合考虑了工程与经济因素，以工程总费用现值作为可靠性优化的目标函数，建立公路土质边坡可靠性设计的优化模型，从而确定了公路土质边坡的目标可靠度推荐值，并给出了基于目标可靠度的公路土质边坡设计方法。     

装载机动臂强度可靠性设计方法探讨

以应力－强度干涉理论为依据，介绍了装载阻力与动臂强度为任意分布的动臂强度可靠性设计的基本原理和方法，给了一定实用的动臂静强度可靠性设计的近似方法，并进行了实例计算。     

Application of kriging method to structural reliability problems

Approximation methods are widely used to alleviate the computational burden of engineering analyses. For structural reliability analyses, the common approach is to use the response surface method (RSM) based on the least square regression. However, another approximation method based on kriging has gained popularity especially in the field of deterministic optimization. However, the application of the kriging method to structural reliability problems has not been realized until recently. Therefore, this paper investigates the use of the kriging method for structural reliability problems by comparing it with the most common RSM. The effects of the kriging parameters are also examined on the basis of the β computation and fitting behavior. It can be deduced from the results given in this paper that using the most common approach in the literature to find the kriging parameters does not guarantee a good result for the structural reliability problems. As a result, some advantages as well as disadvantages of the kriging method are reported, based on the results obtained from the application of the kriging method to the examples from the literature. Finally, this paper suggests the points for which the kriging model could be improved to get better results for structural reliability problems.     

基于非线性有限元的膜结构初始形态设计

阐明了膜结构初始形态设计的内涵，论述了形和态之间的关系。根据非线性大位移理论，推导了膜结构的几何非线性有限元方程，在此基础上，给出了基于非线性有限元法的两种初始形态设计方法。数值算例表明，初始形态设计方法是有效、正确的。     

Structural reliability assessment based on particles swarm optimization

The PSO algorithm is very efficient to solve global optimization problems with continuous variables. Its use in the structural reliability field presents not only the advantage of its facility of implementation, but also the possibility to obtain the design point and the failure probability with a good accuracy. Several examples of the literature studied in this paper show that the results yielded by PSO are quasi-exact with respect to those yielded by MC and response surface methods. The low computing time of this zero order algorithm is also a great advantage to solve optimization problem. Therefore, this algorithm can be considered as an additional efficient algorithm to those existing in the literature based on gradient method.     

A Kriging-based hybrid optimization algorithm for slope reliability analysis

First, the artificial bee colony (ABC) algorithm was used to optimize the Kriging model. A typical example was given to validate a good function fitting performance of the ABC-optimized Kriging model. Next, a structural reliability optimization method was proposed on the basis of the Kriging surrogate model, combined with the artificial bee colony optimization method and penalty function method. A nonlinear limit-state function example was provided to validate the accuracy and efficiency of the hybrid algorithm by comparing the algorithm’s solution with the exact solution of the example. Finally, the proposed method was applied to earth slope reliability analysis using a commercial finite difference program to calculate the slope’s factor of safety. Comparison of the results between the proposed method and the other methods shows that the proposed algorithm is the most suitable for slope reliability analysis.