Neural Network calibration method for VARANS models to simulate wave-coastal structures interaction
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URI: http://hdl.handle.net/10498/32134
DOI: 10.1016/J.COASTALENG.2023.104443
ISSN: 0378-3839
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2024Department
Ingeniería Industrial e Ingeniería CivilSource
Coastal Engineering - 2024, Vol. 188, artículo número 104443Abstract
This study develops a calibration method for the porous media to properly model the interaction between waves and coastal structures using VARANS models. The proposed method estimates the porosity, np, and the optimum values of the Forchheimer coefficients, α and β, that best represent the wave-structure interaction for a complete set of laboratory tests. Physical tests were conducted in a 2D wave flume for a homogeneous mound breakwater under regular wave conditions. Numerical tests were carried out using the IH-2VOF model to simulate the corresponding physical tests and incident wave conditions (HI, T). The numerical tests covered a wide range of Forchheimer coefficients found in the literature, α and β, and the porosity, np, with a total of 555 numerical tests. The results of 375 numerical tests using IH-2VOF were used to train a Neural Network (NN) model with five input variables (HI, T, np, α and β) and one output variable (KR2). The NN model explained more than 90% (R2 > 0.90 and RMSE <5%) of the variance of the squared coefficient of reflection, KR2. This NN model was used to estimate the KR2 in a wide range of np, α and β, and the error (εa) between the physical measurements with regular waves and the NN estimations of KR2 was calculated. The results of εa as function of np, α and β showed that for a given porosity, np, it was difficult to obtain a pair of α and β values that gave a common low error if few physical tests are used for calibration. Then to calibrate properly a VARANS model it seems necessary to check the results obtained for each combination of α and β with many laboratory {HI, T} tests. The minimum root-mean-square error of KR2 (εrms) was calculated to find the optimum values of porosity and Forchheimer coefficients: np = 0.44, α = 200 and β = 2.825 for the tested structure. Blind tests were conducted with the remaining 180 numerical tests using IH-2VOF to validate the proposed method for VARANS models. In this study, eight or more physical tests were required to find adequate values of np, α and β for VARANS models related to the best performance of wave-porous structure interaction.
Subjects
IH-2VOF; Mound breakwaters; Neural Network; Numerical modelling; Porous media; VARANS equationsCollections
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