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反求工程中对测量数据进行优化的研究 总被引:4,自引:0,他引:4
由三坐标测量机测量获得的数据具有一定的杂乱性,难以直接用于通用CAD软件的反求工程设计中。采用参数样条方法对测量数据进行优化,生成利于反求曲面重构需要的数据点,可达到提高曲面反求速度和光顺效果的目的。 相似文献
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蚁群算法良好的离散性,并行性,正反馈性和鲁棒性,非常适合于图像分割。但基本蚁群算法蚂蚁的搜索是随机的,计算量大,不利于算法的收敛,为此,本文提出了设置初始聚类中心的设想,并以小窗口为对象实施算法,由此大大减小了计算量。另外基本蚁群算法中挥发系数固定,会导致算法可能过早收敛或停滞,针对这一不足,本文将其修改为随蚂蚁通过可行路径个数动态变化,使其收敛性和稳定性有了一定提高。实验证明了方法的有效性。 相似文献
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如何解决最短路径选择问题一直是城市交通流诱导系统的关键之一.基于群体仿生理论的蚁群算法是解决此问题的一种方法,针对采用蚁群算法进行最短路径选择时易出现的陷入局部最优解问题,引入混沌理论,采用混沌蚁群算法利用混沌初始化进行改善个体质量和利用混沌扰动避免在蚁群算法搜索过程中陷入局部极值,同时降低了蚁群算法的时间复杂度,从而更好的解决了最短路径选择问题. 相似文献
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水面舰船多学科设计优化(英文) 总被引:1,自引:0,他引:1
多学科设计优化(MDO)被认为是目前处理海洋结构物设计的有效方法.中国船舶科学研究中心也开展了将多学科设计优化应用于船舶设计的研究.上一篇文章从船舶设计研究人员的角度出发对多学科设计优化的理论进行了介绍并且对一条发表了的国外舰船的模型进行了优化.在本文中,作者对国内的一艘实船的概念设计建立了多学科设计优化模型,该模型包括快速性、操纵性和船中剖面的总纵强度分析,它有37个设计变量,9个约束和两个目标.iSIGHT9.O被用来集成这些模块并执行优化,最终找到的优化设计不仅提高了该船的快速性,同时减小了船中剖面的截面积. 相似文献
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This paper presents a simplified method for the reliability- and the integrity-based optimal design of engineering systems and its application to offshore mooring systems. The design of structural systems is transitioning from the conventional methods, which are based on factors of safety, to more advanced methods, which require calculation of the failure probability of the designed system for each project. Using factors of safety to account for the uncertainties in the capacity (strength) or demands can lead to systems with different reliabilities. This is because the number and arrangement of components in each system and the correlation of their responses could be different, which could affect the system reliability. The generic factors of safety that are specified at the component level do not account for such differences. Still, using factors of safety, as a measure of system safety, is preferred by many engineers because of the simplicity in their application. The aim of this paper is to provide a simplified method for design of engineering systems that directly involves the system annual failure probability as a measure of system safety, concerning system strength limit state. In this method, using results of conventional deterministic analysis, the optimality factors for an integrity-based optimal design are used instead of generic safety factors to assure the system safety. The optimality factors, which estimate the necessary change in average component capacities, are computed especially for each component and a target system annual probability of system failure using regression models that estimate the effect of short and long term extreme events on structural response. Because in practice, it is convenient to use the return period as a measure to quantify the likelihood of extreme events, the regression model in this paper is a relationship between the component demands and the annual probability density function corresponding to every return period. This method accounts for the uncertainties in the environmental loads and structural capacities, and identifies the target mean capacity of each component for maximizing its integrity and meeting the reliability requirement. In addition, because various failure modes in a structural system can lead to different consequences (including damage costs), a method is introduced to compute optimality factors for designated failure modes. By calculating the probability of system failure, this method can be used for risk-based decision-making that considers the failure costs and consequences. The proposed method can also be used on existing structures to identify the riskiest components as part of inspection and improvement planning. The proposed method is discussed and illustrated considering offshore mooring systems. However, the method is general and applicable also to other engineering systems. In the case study of this paper, the method is first used to quantify the reliability of a mooring system, then this design is revised to meet the DNV recommended annual probability of failure and for maximizing system integrity as well as for a designated failure mode in which the anchor chains are the first components to fail in the system. 相似文献
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