Gene Expression Models for the Prediction of Longitudinal Dispersion Coefficients in Transitional and Turbulent Pipe Flow

Longitudinal dispersion in pipelines leads to changes in the characteristics of contaminants. It is critical to quantify these changes because the contaminants travel through water networks or through chemical reactors. The essential characteristics of longitudinal dispersion in pipes can be described by the longitudinal dispersion coefficient. This paper presents the application of evolutionary gene expression programming (GEP) to develop new empirical formulas for the prediction of longitudinal dispersion coefficients in pipe flow using 220 experimental case studies of the dispersion coefficient with a R range of 2,000-500,000 spanning transitional and turbulent pipe flow. Gene expression programming is used to develop empirical relations between the longitudinal dispersion coefficient and various control variables, including the Reynolds number, the average velocity, the pipe friction coefficient, and the pipe diameter. Four GEP models are developed, and the weight and importance of each control variable is presented. The prediction uncertainties of all of the developed GEP models are quantified and compared with those of existing models. Finally, a parametric analysis is performed for further verification of the developed GEP models. The results indicate that the proposed relations are simple and can effectively evaluate the longitudinal dispersion coefficients in pipe flow. (C) 2013 American Society of Civil Engineers.