Prediction of critical stress intensity factor for high strength and ultra high strength concrete beams using support vector regression - Yuvaraj, P.; Murthy, A. Ramachandra; Iyer, Nagesh R.; Samui, Pijush; Sekar, S.K. (Journal of Structural Engineering, 2024)
This paper examines the applicability of support vector machine (SVM) based regression to predict the critical stress intensity factor for high strength and ultra high strength concrete beams. Characterization of mix and testing of beams of high strength and ultra strength concrete have been described briefly. Procedure to compute critical stress intensity factor has been outlined. Critical stress intensity factor has been obtained by employing two parameter facture model which uses loading and unloading compliances. Support vector regression (SVR) is based on the computation of a linear regression function in a high dimensional feature space where the input data are mapped through a nonlinear function. SVR model has been developed using MATLAB software for training and prediction of KIC. SVR has been trained with about 70% of the total 87 data sets and tested with about 30% of the total data sets. It is observed that the predicted values of critical stress intensity factor are in good agreement with those of the experimental values.