"Comparison of ACI, AISC, and Basic Methods for CFTs"

B. Shahrooz, W. Zhang
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Abstract

Using experimental data from previous tests and detailed analytical studies, the applicability of ACI and AISC standard techniques for concrete-filled tubular columns (CFTs) is evaluated. The test specimens include shorter and slender CFTs made with normal and high strength steel tubes filled with normal and high strength concrete. The focus of this paper is on rectangular and square tubes. To gauge the success of the code-based methods, the capacities are also computer by the fiber analysis techniques, along with a member level iteration algorithm for analyzing members with significant length. The results indicate that the ACI and AISC methods can yield substantially different capacities. In general, the capacities from the ACI method are reasonably close to those obtained from detailed analytical methods so long as normal strength tubes are used. Both the ACI moment method and AISC method are appropriate for slender CFTs although the ACI method tends to match the analytically calculated capacities more closely. Neither the ACI nor AISC method is applicable for CFTs made with high strength steel tubes as both techniques substantially underestimate the capacity of such columns. For CFTs with high strength steel tubes, it is more appropriate to assume that the steel tube fully yields when the capacity is developed. A revised version of the ACI standard method was developed by incorporating this assumption. The revised ACI method provides a fairly close estimate of the experimentally obtained capacities and those from detailed analysis.
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cft的ACI、AISC和基本方法比较
利用以往的试验数据和详细的分析研究,评估了ACI和AISC标准技术在钢管混凝土柱(CFTs)中的适用性。试验样品包括由普通和高强度钢管填充普通和高强度混凝土制成的较短和细长的cft。本文的重点是矩形管和方形管。为了衡量基于代码的方法的成功,容量也通过纤维分析技术进行计算机化,以及用于分析具有显著长度的成员的成员级迭代算法。结果表明,ACI方法和AISC方法产生的容量有很大差异。一般情况下,只要使用标准强度管,ACI法得到的承载力与详细分析方法得到的承载力相当接近。ACI弯矩法和AISC法均适用于细长cft,但ACI法更接近解析计算的承载力。ACI法和AISC法均不适用于由高强度钢管制成的cft,因为这两种方法都大大低估了此类柱的承载力。对于采用高强度钢管的CFTs,在开发承载力时假设钢管完全屈服更为合适。ACI标准方法的修订版纳入了这一假设。修正后的ACI方法对实验得到的容量和详细分析得到的容量提供了相当接近的估计。
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