Surrogate model with a deep neural network to evaluate gas-liquid flow in a horizontal pipe

HIGHLIGHTS

• who: Yongho Seong et al. from the Department of Energy and Resources Engineering, Kangwon National University, Chuncheon have published the research: Surrogate Model with a Deep Neural Network to Evaluate Gas-Liquid Flow in a Horizontal Pipe, in the Journal: Energies 2020, 13, 968 of /2020/
• what: This study discusses the characteristics of gas-liquid multiphase flows that are easily identified using only five simple input parameters.
• how: Both performances of training with validation loss and the predictability with the testing dataset were examined by changing the number of nodes in the hidden . . .
  

   

  

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