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首页> 外文期刊>Practice periodical on structural design and construction >Prediction of Inelastic Mechanisms Leading to Seismic Failure of Interior Reinforced Concrete Beam-Column Connections
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Prediction of Inelastic Mechanisms Leading to Seismic Failure of Interior Reinforced Concrete Beam-Column Connections

机译：导致内部钢筋混凝土梁柱连接处地震破坏的非弹性机制的预测

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摘要

Inelastic mechanisms leading to failure in interior reinforced concrete beam-column (RCBC) connections, designed on the concept of strong column-weak beam philosophy, primarily result from failure of the joint region and yielding of longitudinal reinforcement in beams. In this manuscript, two novel easy-to-use probabilistic methodologies have been developed that can determine with sufficient accuracy the occurrence of either of these inelastic mechanisms leading to failure, given the geometric, material and loading parameters of an experimental investigation. One model was developed by using the relevance vector machine method, a machine learning methodology that uses a Bayesian formulation and results in a sparse representation. Another model was binomial logistic regression, which can relate the qualitative event of inelastic mechanism resulting in failure initiation with several experimentally obtained independent parameters. It can also quantify the relative importance of each of these independent parameters. Both methods show good predictive efficiency and can be utilized by a designer, engineer, or researcher to obtain a preliminary probabilistic estimate of inelastic mechanisms that lead to failure of interior RCBC connections. This manuscript also presents comparative evaluations of utilizing these two models.
机译：基于强柱弱梁原理的概念而设计的导致内部钢筋混凝土梁柱（RCBC）连接失效的非弹性机制，主要是由于节点区域的失效和梁的纵向钢筋屈服所致。在本手稿中，已经开发出两种新颖的易于使用的概率方法，可以给定实验研究的几何，材料和载荷参数，以足够的精度确定导致失效的这些非弹性机制中任何一种的发生。通过使用关联向量机方法（一种使用贝叶斯公式表示并导致稀疏表示的机器学习方法）开发了一个模型。另一个模型是二项式逻辑回归，它可以将导致失败开始的非弹性机制的定性事件与几个通过实验获得的独立参数联系起来。它还可以量化每个独立参数的相对重要性。两种方法都显示出良好的预测效率，并且可以被设计人员，工程师或研究人员用来获得对导致内部RCBC连接失败的非弹性机制的初步概率估计。该手稿还介绍了利用这两种模型的比较评估。

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