A comparative study between linear regression analysis and various codes for predicting the mechanical characteristics of poly-mer concrete using R-sand and M-sand

Candassamy K; Sreerambabu  J; Sasikumar  P

doi:10.7764/RDLC.23.1.129

Authors

Candassamy K Thanthai Periyar Government Institute of Technology, Anna University, Vellore (India)
Sreerambabu J Thanthai Periyar Government Institute of Technology, Anna University, Vellore (India)
Sasikumar P Kumaraguru College of Technology, Anna University, Coimbatore (India)

DOI:

https://doi.org/10.7764/RDLC.23.1.129

Keywords:

polymer concrete, linear regression analysis, strength properties, R-sand, M-sand.

Abstract

Numerous research studies have concentrated on advancing a sustainable construction industry through innovative concrete methods and materials. In this context, the present research specifically investigates polymer concrete, utilizing both River sand (R-sand) and Manufacturing sand (M-sand). The polymer content was incorporated into the concrete mix based on the weight of the cement, with varying percentages specifically 2%, 4%, 5%, 6%, and 8%. A slump cone test was conducted to assess the workability of the polymer concrete. Based on experimental studies, the optimal polymer percentage was determined to be 5%. This optimal dosage of polymer content significantly improved the mechanical properties of the polymer concrete. The Compressive Strength (CS), Split Tensile Strength (STS), Flexural Strength (FS), and Modulus of Elasticity (ME) were evaluated at both 7 and 28 days. When using R-sand, the mechanical properties of CS, STS, and FS increased by 13.65%, 12.20%, and 11.42%, respectively. Conversely, employing M-sand led to even greater improvements in strength properties: 19.18% for CS, 12.54% for STS, and 11.67% for FS. Based on the experimental results, the strength properties of polymer concrete M-sand mixes outperformed the R-sand mixes. Linear regression analysis and various codes were employed to predict the strength properties of CS, STS, FS and ME. The regression analysis and various codes successfully forecasted the strength properties of polymer concrete, with the predicted results closely correlated with the experimental results. Based on experimental investigations, the determined mix proportions are recommended for practical applications in various environmental conditions.Numerous research studies have concentrated on advancing a sustainable construction industry through innovative concrete methods and materials. In this context, the present research specifically investigates polymer concrete, utilizing both River sand (R-sand) and Manufacturing sand (M-sand). The polymer content was incorporated into the concrete mix based on the weight of the cement, with varying percentages specifically 2%, 4%, 5%, 6%, and 8%. A slump cone test was conducted to assess the workability of the polymer concrete. Based on experimental studies, the optimal polymer percentage was determined to be 5%. This optimal dosage of polymer content significantly improved the mechanical properties of the polymer concrete. The Compressive Strength (CS), Split Tensile Strength (STS), Flexural Strength (FS), and Modulus of Elasticity (ME) were evaluated at both 7 and 28 days. When using R-sand, the mechanical properties of CS, STS, and FS increased by 13.65%, 12.20%, and 11.42%, respectively. Conversely, employing M-sand led to even greater improvements in strength properties: 19.18% for CS, 12.54% for STS, and 11.67% for FS. Based on the experimental results, the strength properties of polymer concrete M-sand mixes outperformed the R-sand mixes. Linear regression analysis and various codes were employed to predict the strength properties of CS, STS, FS and ME. The regression analysis and various codes successfully forecasted the strength properties of polymer concrete, with the predicted results closely correlated with the experimental results. Based on experimental investigations, the determined mix proportions are recommended for practical applications in various environmental conditions.

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