Turbulent wake flow prediction of marine hydrokinetic turbine arrays in large-scale meandering river using physics-informed convolutional neural network

  • Zhang, Zexia (Stony Brook University)
  • Khosronejad, Ali (Stony Brook University)

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This work presents a physics-informed convolutional neural network (PICNN) algorithm for reconstructing the mean flow and turbulence statistics in the wake of marine hydrokinetic (MHK) turbine arrays installed in large-scale meandering rivers, underscoring the potential of PICNN to develop reduced order models for control co-design and optimization of MHK turbine arrays in natural riverine environments.