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Heat exchangers are equipment for energy transfer within industrial processes. The implementation of artificial neural networks (ANN) in this type of device aims to predict thermal behavior and gather more data through a validated ANN model, subsequently optimizing the equipment and/or process. In this work, a model with an ANN was developed to predict the outlet temperatures of working fluids in a laboratory-scale countercurrent heat exchanger. Through a three-level experimental design, data are obtained for training, validating, and testing the ANN model. The results present a statistical analysis for model selection (MSE, MAE, RMSE, and R2).

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Artificial Neural Network Modeling for Predicting Thermal Behavior in a Laboratory-Scale Concentric Tube Heat Exchanger

  • 会议论文

  • 发表日期：

    2026年

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  • Víctor Manuel Zezatti Flores,
  • Miriam Navarrete Procopio,
  • Erick Omar Castañeda Magadán,
  • Omar A. Gómez Rodríguez,
  • Angel Tlatelpa Becerro,
  • Carlos Alberto Ochoa Ortiz

摘要

Heat exchangers are equipment for energy transfer within industrial processes. The implementation of artificial neural networks (ANN) in this type of device aims to predict thermal behavior and gather more data through a validated ANN model, subsequently optimizing the equipment and/or process. In this work, a model with an ANN was developed to predict the outlet temperatures of working fluids in a laboratory-scale countercurrent heat exchanger. Through a three-level experimental design, data are obtained for training, validating, and testing the ANN model. The results present a statistical analysis for model selection (MSE, MAE, RMSE, and R2).