Paper Title
Prediction Of Compressive Strength Of Light Weight Fiber Reinforced Concrete Using Artificial Neural Networks

Abstract
Fiber reinforced concrete (FRC) is a type of concrete that contains discontinuous fibers distributes randomly among the concrete block.Lightweight concretes can be produced with an over-dry density range of approximately 300 to a maximum of 2000 kg/m3. In this paper, the Artificial Neural Networks are utilized to predict the effect of the addition of steel nails as fibers on the compressive strength of lightweight concrete with crushed bricks used as coarse aggregate. The study involves testing of cubic concrete samples with various mixing proportions and water cement ratios. The results showed thatthe highest value of the compressive strength of 7 days age for (1:2:4) proportion is obtained with fiber adding percentage 5% with w/c ratio 50% for fiber size 1". While for 1.5" fiber size, the 10% fiber addition with w/c of 50% has the greatest value of concrete compressive strength. It is also shown that the highest value of the compressive strength of 28 days for (1:2:4) proportion is obtained with fiber adding percentage 10% with w/c ratio 60% for fiber size 1". While for 1.5" fiber size, the 10% fiber addition with w/c of 50% has the greatest value of concrete compressive strength. It is concluded that the highest value of the compressive strength of 7 days for (1:1.5:3) proportion is obtained with fiber adding percentage 10% with w/c ratio 60% for fiber size 1". While for 1.5" fiber size, the 10% fiber addition with w/c of 50% has the greatest value of concrete compressive strength. Also, it is found that the highest value of the compressive strength of 28 days age for (1:1.5:3) mixing is obtained with fiber adding percentage of 10% and w/c equal 50%. The results of prediction showed that for the mixing proportion (1:1.5:3), the compressive strength decreases with increasing of fiber addition and the 1" nail size gives higher values of compressive strength than 1.5" size. Also the prediction results showed that for the mixing proportion (1:2:4), the compressive strength decreases with increasing the fiber addition ration and the 1.5" nail size gives the higher compressive strength than 1". Keyword - Fiber Reinforced Concrete, Prediction of Compressive Strength, Neural Networks, Reinforced Concrete, Lightweight