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索梁组合体系桥梁施工索力确定的割线迭代法 被引量:4

Secant Iterative Method for Determining Construction Cable Forces of Combined-system Bridge with Cable and Girder
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摘要 索梁组合体系桥梁属于高次超静定结构,由于各种非线性因素的影响,该类桥梁施工索力的确定有着很高的技术要求,针对索梁组合体系桥梁中主梁采用满堂支架施工的情况,提出了割线迭代算法,该方法思路清晰,计算简单,收敛性好,本质上属于正装迭代算法。通过对拱梁组合体系桥梁和斜拉桥算例的研究表明:对于主梁采用满堂支架施工的索梁组合体系桥梁,采用割线迭代法确定施工阶段拉索张拉力是可行的,迭代得到的成桥状态内力与合理成桥状态内力吻合得很好;在确定合理成桥状态时,考虑与不考虑收缩徐变作用都是可行的,但考虑收缩徐变作用可以使得割线迭代法效果更好;割线迭代法对初始迭代力的选取要求很宽松,但选取合适的初始迭代力可以减少迭代次数。 Combined-system bridges with cable and girder belong to higher-order statically indeterminate structure, which are affected by some nonlinear factors, so determining construction cable forces of the bridges is a technical job. According to the characteristic of combined-system bridges with cable and girder which main girder is constructed with support construction method, secant iterative method was put forward. The method which is a forward-iteration one has the characteristics of clear thought, easy calculation and well convergence. The analysis of combined-system bridge with arch and girder and cable-stayed bridge indicates that (I) the inner force in completion state iterated by using secant iterative method is similar to that of rational finished state for combined-system bridge with arch and girder which main girder constructed with support construction method, and secant iterative method is workable for determining construction cable forces of the bridge ; (2) considering the effect of shrinkage and creep or not are both practicable for determining the rational completion state, but secant iterative method may produce better result when the effect of shrink'age and creep is considered; (3) secant iterative method is not strict with the initial iterative force, but choosing appropriate initial iterative force can reduce the iteration times.
出处 《公路交通科技》 CAS CSCD 北大核心 2012年第6期81-86,92,共7页 Journal of Highway and Transportation Research and Development
关键词 桥梁工程 索梁组合体系桥梁 割线迭代法 索力优化 K bridge engineering combined-system bridge with cable and girder secant iterative method cable force optimization
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