A Multi Expression Programming Application to High Performance Concrete

High performance concrete (HPC) is a class of concretes that provides superior performance than those of conventional types. The enhanced performance characteristics of HPC are generally achieved by the addition of various cementitious materials and chemical and mineral admixtures to conventional concrete mix designs. These additives considerably influence the compressive strength and workability properties of HPC mixes. To avoid testing several mix proportions to generate a successful mix and also to simulate the behaviour of strength and workability improvement efficiently that often lead to saving in cost and time, it is idealistic to develop predictive models so that the performance characteristics of HPC mixes can be evaluated from the influencing parameters. Accordingly, the main focus of the present study is to propose new formulations of compressive strength and slump flow of HPC mixes for the first time in the literature by means of a promising variant of genetic programming (GP) which is known as multi expression programming (MEP). The models are developed using an experimental database including compressive strength and slump flow of HPC test results obtained from the previously published literature. The results of proposed formulations are compared with other existing models and formulas found in the literature. The results demonstrate that the formulas obtained by the MEP method are able to predict the strength and slump flow to high degree of accuracy.