On the computational study of a fully wetted longitudinal porous heat exchanger using a machine learning approach

HIGHLIGHTS

• who: Hosam Alhakami et al. from the Department of Computer Science, College of Computer and Information Systems, Al-Qura University, Makkah, Saudi Arabia have published the article: On the Computational Study of a Fully Wetted Longitudinal Porous Heat Exchanger Using a Machine Learning Approach, in the Journal: Entropy 2022, 24, 1280. of /2022/
• what: In this paper, numerical solutions for fully wetted longitudinal porous heat exchangers with different thermal conductivities are calculated based on the simple concept of artificial_intelligence (AI), implemented through the application of neural_networks and optimization procedures of meta-heuristic techniques . The authors . . .
  

   

  

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