Three-dimensional realizations of flood flow in large-scale rivers using the neural fuzzy-based machine-learning algorithm

TL;DR

This paper demonstrates that an adaptive neural fuzzy inference system (ANFIS) can accurately generate three-dimensional flood flow fields in large-scale rivers, offering a data-driven approach validated against large-eddy simulation results.

Contribution

The study introduces the application of ANFIS to produce 3D flood flow realizations in large rivers, trained on LES data, and validates its effectiveness across different geometries and flow conditions.

Findings

ANFIS accurately reproduces 3D flood flow fields.

The method generalizes well to different river geometries.

Error analysis confirms the model's reliability.

Abstract

Machine learning methods have been extensively used to study the dynamics of complex fluid flows. One such algorithm, known as adaptive neural fuzzy inference system (ANFIS), can generate data-driven predictions for flow fields but has not been applied to natural geophysical flows in large-scale rivers. Herein, we demonstrate the potential of ANFIS to produce three-dimensional (3D) realizations of the instantaneous flood flow field in several large-scale, virtual meandering rivers. The 3D dynamics of flood flow in large-scale rivers were obtained using large-eddy simulation (LES). The LES results, i.e., the 3D velocity components, were employed to train the learnable coefficients of an ANFIS. The trained ANFIS, along with a few time-steps of LES results (precursor data) were then used to produce 3D realizations of flood flow fields in large-scale rivers with geometries other than the one the ANFIS was trained with. We also used the trained ANFIS to generate 3D realizations of river flow at a discharge other than that the ANFIS was trained with. The flow field results obtained from ANFIS were validated using separate LES runs to assess the accuracy of the 3D instantaneous realizations of the machine learning algorithm. An error analysis was conducted to quantify the discrepancies among the ANFIS and LES results for various flood flow predictions in large-scale rivers.