Theoretical assessment of the mechanical properties of fiber concrete using the dispersion analysis method

This paper examines how the type of fiber and the amount of fiber in concrete impacts the mechanical characteristics of fiber-reinforced concrete (FRC) by both experimental testing and statistical modelling. Basalt, polypropylene, and steel fiber reinforced concrete specimen were cast at different percent ratios (0, 0.1, 0.2 and 0.3) and subjected to laboratory conditions to measure compressive strength. At every dose and fiber type, three specimens were tested, and average values of the strengths were computed. OriginPro was used to fit the data in polynomial regression models (second degree) to quantify the connections between the parameters of this fiber and compressive strength. The most important statistical indicators provided in the assessment of the model accuracy were coefficients of determination ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow> <mml:mi>R</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> </mml:math> ), adjusted <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow> <mml:mi>R</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>F</mml:mi> </mml:math> -statistics, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> -values, and residual analysis. The results revealed that the models were all characterized by high predictive accuracies ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow> <mml:mi>R</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> <mml:mo>=</mml:mo> </mml:math> 0.72, 0.93) and found to be significant using ANOVA ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> <mml:mo>&lt;</mml:mo> </mml:math> 0.0001). Results validated that the type of fiber along with the dosage were critical in the effectiveness of strength with optimal amount enhancing performance and loads beyond or below those levels decreasing the matrix bonding. The produced models offer a predictive predicting model that would be helpful in FRC mixture optimization. The study presents significant information in the field of structural engineering where a newly established structure will be needed to have superior durability, dependability, and load capacity.