浅谈异形柱框架结构的设计

通过最近对异形柱框架结构的设计,深刻认识了普通混凝土框架结构与异形柱框架结构设计的特殊要求,并做突出强调,阐述了使用异形柱的优点,指出异形柱是低层住宅比较理想的结构柱形。     

探讨异形柱框架结构的设计

以某住宅建筑采用的异形柱结构设计为例,介绍了异形柱框架结构的设计特点和结构布置的设计原则,以及异形柱框架结构的计算方法,从异形框架柱和梁柱节点两方面阐述了主要构造措施,以期提高异形柱框架结构的设计水准。     

宾馆建筑异形柱框架结构设计探讨

主要对宾馆建筑异形柱及其结构的概念、异形柱的应用及适应范围、异形柱的性能、框架结构的常见问题以及异形柱结构的设计要点进行论述,进一步探讨宾馆建筑异形柱框架结构设计问题.     

浅析异形柱框架结构设计中应该注意的问题

鉴于异形柱框架结构是一种新型住宅结构,通过对异形柱框架结构受力特点的分析,总结了在异形柱框架结构设计中应该注意的几个问题,并提出了设计建议,从而保证异形柱框架结构的安全适用性。     

探析异形柱框架结构的设计要点

为提高精品住宅的空间灵活性和方便性,异形柱框架结构是一种较好的结构形式,近年来得到了快速发展。本文介绍了异形柱框架结构的概念和特点,从结构建模、结构计算、结果分析、结构配筋四个设计流程阐述了异形柱框架结构的设计要点,供广大工程技术人员参考。     

浅谈异形柱框架结构设计

住宅设计中采用混凝土异形柱框架结构越来越多。本文详述了混凝土异形柱框架结构中受力特点,针对异形柱受力破坏机理。指出合理的结构布置、结构计算及构造措施,以确保结构的安全可靠。     

异形柱框架结构设计常见问题

以《混凝土异形柱结构设计规程》为依据,通过分析异形柱框架结构的受力特点以及构造特点,详细归纳了异形柱框架结构设计应注意的问题,以期确保异形柱结构安全可靠、经济适用。     

异形柱框架结构的应用

简要介绍了我国目前异形柱框架结构的应用情况;总结了异形柱框架结构的几个特点,根据几个地方规程阐述了异形柱结构的有关规定及构造;提出了设计异形柱框架结构时要注意的几个问题.     

混凝土异形柱框架结构的受力特点及在住宅设计中的应用

住宅设计中采用混凝土异形柱框架结构越来越多。阐述了混凝土异形柱框架结构中受力特点,针对异形柱受力破坏机理,指出合理的结构布置、结构计算及构造措施,以确保结构的安全可靠。     

异型柱结构体系的设计及其在工程实践的应用

1前言 随着人民物质文化生活水平的提高，人们对于自己的安居之所提出了越来越多的要求，所要求的层次也越来越高，这便对我们的设计提出了“水涨船高”的要求。异形柱结构体系，便是这种“讲究”中所产生的结构形式。 现浇框架结构的多层及高层住宅，为了使建筑在使用功能上获得较美观、实用的平立面，在居室中影响使用及美观的地方面布置异形柱。随着异形柱设计及施工工艺的日趋成熟，异形柱的应用也愈见广泛。     

城市交通网络设计问题中的双层规划模型

城市交通网络设计问题的主要内容就是通过规划的思想建立数学模型,通过优化计算方法寻找最优的用于道路网络新建或改善的交通建设投资决策方案,即研究如何能用最少的资金投入达到使整个交通网络中某种指标最优的目的。这些具体的系统性能指标可以是使整个网络中的系统总阻抗最小、交通拥挤程度最低、能源消耗最少等,从而为交通规划部门和决策人员提供科学、系统、合理、有效的决策方案和决策数据,使政府有限的资金投入能取得最佳的投资效益。本文首先简单介绍了城市交通网络设计问题研究的主要内容,然后给出了城市交通网络设计中一般形式的双层规划模型及其推广形式。     

A genetic-algorithms based evolutionary computational neural network for modelling spatial interaction dataNeural network for modelling spatial interaction data

Building a feedforward computational neural network model (CNN) involves two distinct tasks: determination of the network topology and weight estimation. The specification of a problem adequate network topology is a key issue and the primary focus of this contribution. Up to now, this issue has been either completely neglected in spatial application domains, or tackled by search heuristics (see Fischer and Gopal 1994). With the view of modelling interactions over geographic space, this paper considers this problem as a global optimization problem and proposes a novel approach that embeds backpropagation learning into the evolutionary paradigm of genetic algorithms. This is accomplished by interweaving a genetic search for finding an optimal CNN topology with gradient-based backpropagation learning for determining the network parameters. Thus, the model builder will be relieved of the burden of identifying appropriate CNN-topologies that will allow a problem to be solved with simple, but powerful learning mechanisms, such as backpropagation of gradient descent errors. The approach has been applied to the family of three inputs, single hidden layer, single output feedforward CNN models using interregional telecommunication traffic data for Austria, to illustrate its performance and to evaluate its robustness.     

Optimal Road User Charging Cordon Design: A Heuristic Optimization Approach

Abstract:   This article addresses the optimal design problem of selecting a charging cordon in a general traffic network. A charging cordon is a set of tolled links surrounding a designated area so that all travelers entering or passing through this area will be tolled. Travelers in the network are assumed to respond to the tolls imposed by adjusting their behaviors to achieve a new equilibrium following Wardrop's equilibrium condition. The necessity of this equilibrium condition is imposed as one of the constraints in the optimal charging cordon design problem. This problem can be categorized as a Mathematical Program with Equilibrium Constraints (MPEC). This article presents an innovative Genetic Algorithm (GA) based method to tackle the problem. A new framework, called branch–tree framework, is developed to represent a closed charging cordon so that the method of GA can be used. The method is tested with a network of Edinburgh. Although the proposed algorithm is a heuristic-based method, the optimization result in the test is very promising. The optimal closed charging cordon as found by the algorithm produces a significantly higher benefit than that of judgmental cordons .     

裂隙岩体三维渗流网络搜索及稳定渗流场分析

 从实际工程结构面统计资料以及结构面本身渗流特性出发,结合逾渗理论分析裂隙岩体渗流网络的组成特点,研究三维块体切割技术与逾渗理论在裂隙类型分类上的相似性问题,进而在既有三维块体切割技术基础上增加渗流面阻水特性判断等模块,形成三维渗流网络搜索算法,解决三维渗流网络难以建立的问题。并在此基础上,根据Louis公式和广义达西定律编制裂隙岩体三维渗流网络搜索及恒定流分析程序3D-Network-Seepage.f90,用于裂隙岩体三维渗流网络构建与恒定渗流计算分析。然后,结合算例对该方法进行验证,结果表明：所提方法不仅能够生成客观、正确的渗流网络,还能准确地反映裂隙面水流的运动规律以及裂隙网络中实际水流的流动趋势,但该方法还有待于在实际工程中进行验证。     

一种基于神经网络的材料成分模型

为研究如何利用神经网络预测材料化合物构成，建立了一个4层前向型网络，这种网络通过改变神经元非线性变换函数的参数，使连接权调整线性化，从而可提高学习速度，减少计算量，并避免了BP网络存在的易陷入局部极小和收敛速度慢的问题，以CaO-Al2O3-SiO2系统为例进行的仿真研究结果表明，该网络可成功包含材料化合物的构成信息。     

Solving a nonlinear bilevel programming model of the equilibrium network design problem for Korea

A network design problem solves for link improvements or additions to an existing transportation network provided that a certain objective function such as social welfare is maximised. In addition, an equilibrium network design problem specifically requires each link to have user equilibrium flows.In this paper, two equilibrium transportation network design problems are formulated in a nonlinear bilevel programming framework; one with a budget constraint and one without. A bilevel programming formulation allows explicit consideration of the interaction between the public sector which supplies transportation facilities and the private sector which uses the given facilities. This paper presents a descent-type algorithm to solve an equilibrium network design problem formulated in the nonlinear bilevel programming model for Korea. Numerical analysis using network data for a simplified Korean highway system is reported.     

Neural Network–Spreadsheet Integration for Earth-Moving Operations

Abstract: This paper examines the potential to combine trained artificial neural networks with application development software to expand their applicability to construction management problems. The problem of determining optimal equipment combinations for the dozer/scraper earth-moving team, under various physical conditions of the haul road, was chosen for its limited scope and lack of effective solution methods currently available. An introduction to the problem provides the current state of technology for handling this problem. The problem is analyzed to determine the information and resource requirements as well as the input and output forms that would be desirable for such a program. The paper proceeds through the design process and development of the program schematic. Programming of the system is examined, including the development process used to train the neural network, conversion of the network to a spreadsheet form, and spreadsheet manipulation of the network outputs. The paper concludes with recommendations for expansion of the program for more complex haul road conditions and equipment types.     

Architectural layout optimization using annealed neural network

The facility layout problem is concerned with finding feasible locations for a set of interrelated objects that meet all design requirements and maximize design quality in terms of design preferences. The contribution of this paper is a new framework, named annealed neural network, for efficiently finding competitive solutions for the facility layout problem. This framework arises from the combination of Hopfield neural networks and simulated annealing. The first is a representation model of the layout problem and the second is a search algorithm for finding the optimum or near optimum solutions. The annealed neural network combines characteristics of the simulated annealing algorithm and the Hopfield neural network. Annealed neural network exhibits the rapid convergence of the neural network, while preserving the solution quality afforded by simulated annealing. Strategies for setting reasonable penalty factor in objective function and temperature in simulated annealing procedure were proposed. A case study of a hospital building with 28 facilities was employed to demonstrate that this model is rather efficient to solve the architectural layout problem, and it is amenable to fast computation for large layout problems.     

Neural Network Approaches to Aid Simple Truss Design Problems

Abstract: Diverse problems in engineering may be solved accurately with computers. In structural engineering, many solution techniques exist. Over the past few years, neural networks have evolved as a new computing paradigm, and many engineering applications have been studied. This paper describes configuring and training of a neural network for a truss design application and explores the possible roles for neural networks in structural design problems. The specific problem considered is a simple truss design where, given a geometry and a loading, economical cross-sectional areas of all the members are to be selected. For this problem, a two-layer neural network is trained using the back-propagation algorithm with patterns representing optimal designs for diverse loading conditions. The performance of the trained neural network is evaluated with a sample problem.     

Optimum budget allocation method for projects with critical risks

In this paper, the authors analyze the trade-off problem between project budgets and critical risks. Project managers face the problem to balance cash flows and risks when preventive risk response plans require additional costs. Mathematical modeling approach is used with a metric called risk-based project value (RPV). RPV is an evaluation of projects calculated with cash flows and risk probabilities of activities that constitute the project network diagram. There exists an optimal solution for the budget allocation problem that maximizes the expected project value. There is a condition where additional budgets can improve the project value. The study result suggests that there should be an integrated process to optimize the budget plan with the risk management plan. Methods are developed to obtain optimum budget allocations for projects with various types of activity networks. Evaluation of the marginal cost sensitivity on the RPV supports project manager's decisions on reallocation of budgets.