The application of soil mixture in concrete footing design using the linear regression model

Abstract

The economical and safe design of a concrete footing is considered in geotechnical engineering projects. The selection appropriate dimension of the concrete footing is a critical decision that needs to be made by professional engineering, and the accuracy of this decision plays a vital role in the economical and safe design of a geotechnical engineering project. In this study, the engineering judgment for the width design of concrete footing when different soil mixture configuration is rested beneath the concrete footing guided using linear regression and histogram models. The size of 1 (m), 1.3 (m), 1.6 (m), 1.9 (m), 2.2 (m), and 2.5 (m) is numerically selected to design width of concrete footing. The linear regression analysis applied to predict economical footing width with higher accuracy in considering all soil mixture designs. The results reveal the higher width of the concrete footing exhibit with higher accuracy. In this study, the proposed models guide the geotechnical engineers in the selection suitable width of concrete footing in a geotechnical engineering project. This study makes the bridge between the analytical method and the application of soil mixture in concrete footing design. The prediction width of concrete footing with high accuracy supports economically a structure and enhances the stability of the structure as well.

Sustainable Cement Stabilization of Plastic Clay Using Ground Municipal Solid Waste: Enhancing Soil Properties for Geotechnical Applications

“…In addition, random data were selected from all produced data for the training to have a reliable prediction assessment. ANNs and linear regression analysis are two methods that have been applied to prediction generation in geotechnical engineering with respect to the mixing soil method [59,60]. The data training and reproduction phases are the two main parts of ANNs for the prediction.…”

“…ANNs [59] and regression analysis [60] have been adopted to predict the mixing soil method results to solve the problem of soil weakness. There is no universal method for explaining ANN architectural design to predict a phenomenon in geotechnical engineering.…”

“…The cohesion of the mixed soil plays a main role in predicting the safe bearing capacity of the soil mixture [59]. In addition, the linear regression results show how the appropriate soil mixing designs are accompanied by selecting the proper width of a concrete footing, resulting in the development of a safe concrete footing design [60]. ANNs can be suggested for the prediction accuracy of any soil improvement design.…”

The impact of mesh structural design on nonlinear numerical simulation of geo‐structure: A seismic analysis

“…The nonlinear numerical analysis was applied to explain the concept of the strain energy in geotechnical earthquake engineering for design embankment‐subsoil and soil foundation 1–4 . The statistical method was applied to predict geotechnical engineering design for support engineering judgment 5,6 . The mesh design has been explained in solving a scientific problem 7 .…”

Forecasting bearing capacity of the mixed soil using artificial neural networking

“…There are several types of research on the analytical, experimental and numerical analysis of the soil foundation, and the soil dynamic and static response evaluated with experimental, analytical and numerical results are reported in the literature [1][2][3][4][5][6][14][15]. On the other hand, different prediction techniques were applied on mild steel pressure vessel, crack propagation, compressive failure surface of cement concrete, natural stone and concrete footing design [17][18][19][20][21][22]. To identify and apply the best results in the geotechnical engineering design the advanced technique for decision making is needed.…”