Title : ( Nonlinear Regression Prediction of Mechanical Properties for SMA-Confined Concrete Cylindrical Specimens )
Authors: ُSaeed Eilbeigi Ghalani , Mohammadreza Tavakkolizadeh , Amirreza Masoodi ,Access to full-text not allowed by authors
Abstract
In order to achieve active confinement in concrete elements, researchers have recently employed smart materials called shape memory alloys (SMA). Several empirical relationships have been widely used to predict the behavior of confined concrete. To develop more accurate relations for predicting the behavior of concrete actively confined with SMA spirals, it is necessary to obtain new relations for determining the peak compressive stress and the corresponding strain in addition to the ultimate stress and strain. For this purpose, existing data from 42 specimens of plain concrete cylindrical specimens confined with SMA spirals and subjected to uniaxial compression were collected. Then, by using MATLAB and SigmaPlot software, nonlinear regression analyses were conducted to obtain the optimum relations. The best equations were selected using multiple error criteria of root mean square error (RMSE) and R-squared (R2). Finally, the accuracy of the proposed relations was compared to the existing relations for active concrete confinement which showed better accuracy.
Keywords
active confinement; SMA spirals; regression analysis; peak stress; ultimate stress; axial strain@article{paperid:1092839,
author = {Eilbeigi Ghalani, ُSaeed and Tavakkolizadeh, Mohammadreza and Masoodi, Amirreza},
title = {Nonlinear Regression Prediction of Mechanical Properties for SMA-Confined Concrete Cylindrical Specimens},
journal = {Buildings},
year = {2022},
volume = {13},
number = {1},
month = {December},
issn = {2075-5309},
pages = {112--112},
numpages = {0},
keywords = {active confinement; SMA spirals; regression analysis; peak stress; ultimate stress; axial strain},
}
%0 Journal Article
%T Nonlinear Regression Prediction of Mechanical Properties for SMA-Confined Concrete Cylindrical Specimens
%A Eilbeigi Ghalani, ُSaeed
%A Tavakkolizadeh, Mohammadreza
%A Masoodi, Amirreza
%J Buildings
%@ 2075-5309
%D 2022