Eun Taek Shin, Se Hyuck An, Sung Won Park, Seung Oh Lee, Chang Geun Song
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引用次数: 0
Abstract
Accurate parameter selection is crucial for reliable predictions in fluid dynamics, environmental transport, and urban flood prediction. Traditional manual methods are time-consuming and prone to errors. This study introduces an automated algorithm to optimize roughness and viscosity coefficients in two-dimensional flow analysis models. Our algorithm automates the simulation process within specified parameter ranges, using Root Mean Square Error (RMSE) to compare results with experimental data. Applied to a diverging channel and an abruptly widening channel, the algorithm successfully identified optimal parameters, accurately matching experimental observations. Heatmaps visualize RMSE values, facilitating optimal parameter identification. This advancement enhances model efficiency and accuracy, streamlining the parameter determination process and offering a robust method for hydraulic modeling.
期刊介绍:
Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.