Ebid Ahmed, Deifalla Ahmed
Department of Structural Engineering and Construction Management, Future University in Egypt, New Cairo 11835, Egypt.
Materials (Basel). 2022 Apr 7;15(8):2732. doi: 10.3390/ma15082732.
Although lightweight concrete is implemented in many mega projects to reduce the cost and improve the project's economic aspect, research studies focus on investigating conventional normal-weight concrete. In addition, the punching shear failure of concrete slabs is dangerous and calls for precise and consistent prediction models. Thus, this current study investigates the prediction of the punching shear strength of lightweight concrete slabs. First, an extensive experimental database for lightweight concrete slabs tested under punching shear loading is gathered. Then, effective parameters are determined by applying the principles of statistical methods, namely, concrete density, columns dimensions, slab effective depth, concrete strength, flexure reinforcement ratio, and steel yield stress. Next, the manuscript presented three artificial intelligence models, which are genetic programming (GP), artificial neural network (ANN) and evolutionary polynomial regression (EPR). In addition, it provided guidance for future design code development, where the importance of each variable on the strength was identified. Moreover, it provided an expression showing the complicated inter-relation between affective variables. The novelty lies in developing three proposed models for the punching capacity of lightweight concrete slabs using three different (AI) techniques capable of accurately predicting the strength compared to the experimental database.
尽管许多大型项目采用轻质混凝土以降低成本并改善项目的经济状况，但研究主要集中在传统的普通重量混凝土上。此外，混凝土板的冲切剪切破坏很危险，需要精确且一致的预测模型。因此，本研究调查轻质混凝土板冲切抗剪强度的预测。首先，收集了在冲切剪切荷载作用下测试的轻质混凝土板的广泛实验数据库。然后，应用统计方法原理确定有效参数，即混凝土密度、柱尺寸、板有效深度、混凝土强度、抗弯配筋率和钢筋屈服应力。接下来，本文提出了三种人工智能模型，即遗传规划（GP）、人工神经网络（ANN）和进化多项式回归（EPR）。此外，它为未来设计规范的制定提供了指导，确定了每个变量对强度的重要性。而且，它给出了一个表达式，显示了有效变量之间复杂的相互关系。其新颖之处在于使用三种不同的（人工智能）技术开发了三种轻质混凝土板冲切承载力模型，与实验数据库相比，这些模型能够准确预测强度。
