Mathematical Model for Strength Prediction of Concrete under Influence of GGBS and Fly Ash
Krishan Kumar Saini1, Tarun Gehlot2, Suresh Singh Sankhla3
1Krishan kumar saini*, structural department, MBM Engineering College or Jai Narain Vyas University, jodhpur, India.
2Tarun gehlot, department, structural department, MBM Engineering College or Jai Narain Vyas University, jodhpur, India.
3Dr Suresh Singh Sankhla, department, structural department, MBM Engineering College or Jai Narain Vyas University, jodhpur, India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4670-4675 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6834018520/2020©BEIESP | DOI: 10.35940/ijrte.E6834.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There are many variables of concrete that affect its strength gaining characteristics. This study is a research to use the early compressive strength test result to evaluate compressive strength at different ages. Proper use of the early day compressive strength result to predict characteristic strength of normal weight concrete has been investigated. A simple model capable of predicting the compressive strength of concrete at any age is proposed for locally available aggregate concrete. The model develops a rational polynomial equation having only two coefficients. This study also proposes a simple justified relationship between the coefficient (strength at infinite time) with the strength values of concrete of a particular day. This relation almost make simple to understand and reliable to any the concrete strength prediction model. The developed model is validated for commonly used for local aggregate concrete. Data used in this study are collect from some previous studies of research scholars and recent experimental works of us at RCC lab of MBM Engineering College Jodhpur. along with data sets of conventional concrete (CC), we have also considered influence and variation of GGBS and FLYASH in Conventional concrete and we have selected the various data sets for M1 ( GGBS & FLY ASH ),M2( GGBS ) & M3( FLY ASH) member group .The research carried with the model using different data exhibit reliable prediction of concrete strength at different ages (7, 14, 28 days.) with good accuracy.
Keywords: Strength Prediction, Concrete, Ground Granulated Blast Furness Slag, Fly Ash .
Scope of the Article: Regression and Prediction