Influence of Light Weight Coarse Aggregate on the Mechanical Properties of Concrete

Light weight concrete has significant importance in the field of construction. The main purpose of using light weight concrete is to reduce the dead load of concrete structure. Light weight concrete is prepared by using light weight aggregate and weight of light weight concrete is less than the weight of normal concrete. In this research cement, fly ash, fine aggregate, bottom ash, coarse aggregate and light weight aggregate have been used as a main ingredient in making concrete. To compose concrete as lightweight, the light weight aggregate such as Light Expanded Clay Aggregate (LECA) and Lytag light weight aggregate are used in place of coarse aggregate. Practical study on concrete mix M20 is carried out by substituting fly ash in place of cement, bottom ash in place of fine aggregate and LECA in place of coarse aggregate at the rate of 5 %, 10 %, 15 %, 20 %, 25 %, 30 % and 35 %. In the same way an additional practical study on concrete mix M20 is carried out by substituting fly ash in place of cement, fine aggregate (no replacement) and Lytag light weight aggregate in place of coarse aggregate at the rate of 5 %, 10 %, 15 %, 20 % and 25 %. In the above mentioned study, the concrete cube and cylinder are used analyze their Split Tensile Strength (STS), Compressive Strength (CS) at 7, 28 and 56 day. The Flexural Strength (FS) and Deflection (D) of concrete beam were discussed on the basis of optimum dosage of replacement in compressive strength and split tensile strength of concrete. The result came from the concrete made with 5 % substitution of LECA and for concrete made with 10 % substitution of Lytag was found to be good performance in CS, STS and FS of concrete. After this evaluation process, the important intention of the projected technique is to frame the mathematical modelling with help of optimization technique. Mathematical modelling is used to forecast the CS, STS, for 7, 28 and 56 days and deflection (D) of the concrete. The mathematical model is used to forecast the strength with minimum error. The techniques likes Particle Swarm Optimization (PSO), Artificial Fish Swarm Optimization (AFSO) and Harmony Search (HS) are used to optimize the result that the attained error values between the output of the practical and the forecasted value are nearly equal to zero in the designed model. From the result, the accuracy of 95.56 % on LECA based concrete and 94.23 % on Lytag based concrete is find by mathematical modelling in AFSO algorithm.