The Shiono and Knight method (SKM) is a simple depth-averaged flow model, based on the RANS equations which can be used to estimate the lateral distributions of depth-averaged velocity and boundary shear stress for flows in straight prismatic channels with the minimum of computational effort. However, in order to apply the SKM, detailed knowledge relating to the lateral variation of the friction factor (f), dimensionless eddy viscosity (λ) and a sink term representing the effects of secondary flow (Γ) are required. In this paper a multi-objective evolutionary algorithm is used to study the lateral variation and value of these parameters for simple trapezoidal channels over a wide range of aspect ratios through the model calibration process. Based on the available experimental data, four objectives are selected and the NSGA-II algorithm is applied to several datasets. The best answer for each set is then selected based on a proposed methodology. Rules relating f, λ and Γ to the wetted parameter ratio (Pb/Pw) for a variety of situations have been developed which provide practical guidance for the engineer on choosing the appropriate parameters in the SKM model.
A novel application of a multi-objective evolutionary algorithm in open channel flow modelling
S. Sharifi, M. Sterling, D. W. Knight; A novel application of a multi-objective evolutionary algorithm in open channel flow modelling. Journal of Hydroinformatics 1 January 2009; 11 (1): 31–50. doi: https://doi.org/10.2166/hydro.2009.033
Download citation file: