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Performance‐based design using structural optimization

A new methodology for seismic design is proposed based on structural optimization with performance‐based constraints. Performance‐based criteria are introduced for the seismic design of new buildings. These criteria are derived from the National Guidelines for Seismic Rehabilitation of Buildings (Reference [19], Federal Emergency Management Agency (FEMA), ‘NHERP Guidelines for seismic rehabilitation of buildings’, Report Nos 273 and 274, Washington, DC, 1997) for retrofitting existing structures. The proposed design methodology takes into account the non‐linear behaviour of the structure. The goal is to incorporate in the design the actual performance levels of the structure, i.e. how much reserve capacity the structure has in an earthquake of a given magnitude. The optimal design of the structure minimizes the structural cost subjected to performance constraints on plastic rotations of beams and columns, as well as behavioural constraints for reinforced concrete frames. Uncertainties in the structural period and in the earthquake excitation are taken into account using convex models. The optimization routine incorporates a non‐linear analysis program and the procedure is automated. The proposed methodology leads to a structural design for which the levels of reliability (performance levels) are assumed to be quantifiable. Furthermore, the entire behaviour of the structure well into the non‐linear range is investigated in the design process. Copyright © 2000 John Wiley & Sons, Ltd.     

社区生活圈的新时间地理学研究框架

社区生活圈从居民日常活动及行为视角考察城市社区,是城市地理学和城市相关学科的研究前沿,也是中国国土空间规划体系创新的重要组成部分,以及中国城市社会可持续发展的重要抓手。伴随着流动性和信息化的不断深入,社区生活圈的主体日益多元化、社区活动和居民时空行为日益多样化、社区空间的功能与意义日益丰富化,亟需城市地理学的研究创新与实践引导。时间地理学是理解人与环境关系的社会—技术—生态综合方法,为早期基于时空行为与生活空间的社区生活圈研究提供了重要基础。新时间地理学重视家庭及其他组织企划的交互与时空组合,可为社区生活圈内个体—家庭—社区之间的复杂互动关系研究、时空行为的社会文化制约与多情境分析及模拟提供重要支撑。论文基于新时间地理学方法,从理论、方法和实证3个维度提出社区生活圈的新时间地理学研究框架,具体包括构建社区生活圈的时空行为理论,揭示社区生活圈的时空间结构;创新社区生活圈的时空行为分析和模拟方法;从社区生活圈时空行为优化、社区交往生活圈、社区安全生活圈等方面创新中国城市规划与管理等研究内容。     

An improved ant colony optimization (I-ACO) method for the quasi travelling salesman problem (Quasi-TSP)

Traveling salesman problem (TSP) and its quasi problem (Quasi-TSP) are typical problems in path optimization, and ant colony optimization (ACO) algorithm is considered as an effective way to solve TSP. However, when the problems come to high dimensions, the classic algorithm works with low efficiency and accuracy, and usually cannot obtain an ideal solution. To overcome the shortcoming of the classic algorithm, this paper proposes an improved ant colony optimization (I-ACO) algorithm which combines swarm intelligence with local search to improve the efficiency and accuracy of the algorithm. Experiments are carried out to verify the availability and analyze the performance of I-ACO algorithm, which cites a Quasi-TSP based on a practical problem in a tourist area. The results illustrate the higher accuracy and efficiency of the I-ACO algorithm to solve Quasi-TSP, comparing with greedy algorithm, simulated annealing, classic ant colony algorithm and particle swarm optimization algorithm, and prove that the I-ACO algorithm is a positive effective way to tackle Quasi-TSP.     

Analysis of spatial clustering optimization

Spatial clustering is widely used in many fields such as WSN (Wireless Sensor Networks), web clustering, remote sensing and so on for discovery groups and to identify interesting distributions in the underlying database. By discussing the relationships between the optimal clustering and the initial seeds, a clustering validity index and the principle of seeking initial seeds were proposed, and on this principle we recommend an initial seed-seeking strategy: SSPG (Single-Shortest-Path Graph). With SSPG strategy used in clustering algorithms, we find that the result of clustering is optimized with more probability. At the end of the paper, according to the combinational theory of optimization, a method is proposed to obtain optimal reference k value of cluster number, and is proven to be efficient.     

风沙流中沙粒起跳初速度分布的探讨

风沙流结构中起跃沙粒的初速度分布,是连接微观研究和宏观研究的桥梁。笔者分析了已有的实验数据,就沙质地表起跃沙粒的速度分布、角度分布进行了计算;并运用碰撞理论建立了一个二维碰撞模型。考虑边界条件的影响,运用概率论统计的思想计算了风沙流结构中起跃沙粒初速度的概率分布,并和实验值进行了对比,得到了较好的结果,对风沙流中起跃沙粒的速度分布有了一个定性的认识。     

干涸尾闾湖盆区泥漠地表磨蚀释尘特征

沙粒的表面磨蚀效应是地表产尘、释尘的重要机制,针对干湖盆泥漠地表开展磨蚀释尘实验研究,对理解干湖盆地表风蚀过程及盐碱尘暴形成机理具有重要意义。对采自西居延海干涸湖盆泥漠地表土样进行室内磨蚀模拟实验,研究了不同粒级（细、中、粗）沙粒不同落沙角度（30°,45°,60°）的磨蚀效应。结果表明：（1）泥漠地表磨蚀实验中能够产生明显释尘效应的沙粒粒级阈值为中沙（0.25 mm<M_d<0.50 mm）;（2）磨蚀粒径粒级相同时,磨蚀角度会对泥漠地表磨蚀释尘速率产生影响,磨蚀量的角度排序为60°>30°>45°,但同一粒级3种角度下的磨蚀释尘率差异不显著。（3）磨蚀角度为45°时,计算了泥漠地表的质量磨蚀率与能量磨蚀率,其中中沙为0.04 g·kg^-1、0.43 g·J^-1,粗沙为0.08 g·kg^-1、0.74 g·J^-1,极粗沙为0.26 g·kg^-1、2.54 g·J^-1;在磨蚀沙粒粒级倍增而磨蚀角度不变情况下,泥漠地表磨蚀释尘率与能量磨蚀率未发生正比例线性增长变化。     

一种组合优化的多边形化简方法

以多边形轮廓为目标 ,依据曲线特征点将其分解为一系列的弯曲特征 ,并对此弯曲特征集实施组合优化 ,将入围弯曲首尾相连 ,即可得到最终的化简结果     

工程建设项目的多测整合对策研究

以广州市开展联合测绘的改革成效为基础,进一步探索研究工程建设项目审批服务全链条中的测绘服务事项,重点关注优化测绘服务流程、统一测绘技术标准规范、强化对测绘成果的共享互认以及完善测绘行业管理制度等内容,通过优化测绘服务体系为审批制度改革"加速",为优化营商环境"助力",为全国各地全面推出"多测合一"改革提供可复制推广的经...     

模拟退火机制下优化离散粒子群的端元提取算法

针对离散粒子群优化(Discrete Particle Swarm Optimization,DPSO)端元提取算法初始种群质量差、收敛性能低且易于陷入局部最优,本文将模拟退火算法引入到DPSO的不同阶段,模拟退火算法能以一定的概率接受和舍弃新状态,使种群内粒子渐趋有序、达到平衡,收敛到全局最优,有效避免了搜索陷入局部最优。因此,该算法不仅保持了DPSO的全局组合优化特点,克服了初始种群质量差、易陷入局部最优等缺点,而且还提高了收敛速度和端元提取精度。