Using the concept of information theoretic entropy, the probability density function (pdf) of shear capacity of the reinforced concrete beam with stirrup reinforcement is determined. Entropy, expressed in terms of Shannon functional, is maximized subjected to the statistical moment and normalization constraints of pdf of shear capacity. The statistical moments of shear capacity distribution are obtained using second-order approximation of shear capacity equation. The pdf so determined has strong statistical mechanics interpretation of maximum entropy principle. Also, a procedure for goodness-of-fit test has been proposed, for the given data, using the information theoretic entropy as a measure of goodness-of-fit. In the present investigation, beams of three different ranges of shear span to effective depth ratios are considered. The mechanics-based shear capacity equations, presented earlier by authors along with associated modelling errors, are used for estimating the statistical moments of shear capacity distribution. The computationally efficient approach of determination of maximum entropy distribution presented in this article can be viewed as an alternate to the process of determination of pdf using brute force Monte Carlo simulation approach.

利用信息论熵的概念，确定了带箍筋的钢筋混凝土梁抗剪承载力的概率密度函数(pdf)。以香农函数表示的熵在统计矩和抗剪承载力 pdf 的归一化约束条件下最大化。使用抗剪承载力方程的二阶近似获得抗剪承载力分布的统计矩。如此确定的pdf对最大熵原理具有很强的统计力学解释。此外，还针对给定数据提出了一种拟合优度检验程序，使用信息论熵作为拟合优度的度量。在本研究中，考虑了三种不同剪切跨距与有效深度比范围的梁。作者之前提出的基于力学的抗剪承载力方程以及相关的建模误差，用于估计抗剪承载力分布的统计矩。本文中提出的确定最大熵分布的计算有效方法可以看作是使用蛮力蒙特卡罗模拟方法确定 pdf 的过程的替代方法。