Experimental and Statistical Evaluation of Mechanical Properties of Green Cement Concretes – Taguchi Integrated Supervised Learning Approach

Balakrishna Maddodi,1

Radhika P Bhandary,1

Vivek Sharma,2

Jitendra Singh Yadav,2

Smaranika Mohapatra,3

Asha Uday Rao,1,*Email

Prasanna M Kumar,1

Prakash Rao Gurpur,4

Shivani Chougule5

Dhanaraj Bharathi Narasimha6

1Department of Civil Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104 India.
2Department of Computer & Communication Engineering, Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan 303007, India.
3Department of Information Technology, Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan 303007, India.
4Manipal School of Architecture and Planning, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India.
5School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
6Department of Environment Impact Assessment, Horizon Ventures, Bengaluru, Karnataka 560094, India.

 

Abstract

Globally, rapid infrastructure development and environmental challenges associated with the higher carbon footprints of ordinary Portland cement (OPC) based concretes have increased the usage of green cement-based concrete (GCC) to reduce energy consumption and provide a sustainable option. Even though GCC is a superior alternative to OPC, only a few publications have addressed optimizing process parameters in GCC manufacturing to optimize mechanical properties. The Taguchi method is well-known as one of the most effective methods for optimizing predictors to get the desired level of response. Additionally, in the modern era, data-driven supervised machine learning approaches have been used extensively to develop mathematical models to establish relationships between the variables. As a result, the Taguchi method was used in this study to obtain the best mix design targeting a compressive strength of greater than 40 MPa. Numerous design combinations have been tested, and a process for selecting the most effective combination has been established. The analysis aided in comprehending the individual contributions of the major components to the mechanism of strength gain. The observations confirmed the Taguchi method's ability to predict the design mix proportions of the GCC and the ability of machine learning to relate the variables mathematically.

Experimental and Statistical Evaluation of Mechanical Properties of Green Cement Concretes – Taguchi Integrated Supervised Learning Approach