Development of a hybrid methodology of computational simulation and deep learning for the optimization of the design of advanced composite plate and fin heat exchangers in the cryogenic condensation of natural gas.

Authors

Keywords:

hybrid computational simulation methodology - deep learning - plate and fin heat exchanger design - advanced composites - cryogenic condensation - natural gas.

Author Biographies

David Molina Ortiz, National Experimental Polytechnic University "Antonio José de Sucre"

Doctoral candidate in Engineering Sciences at the National Experimental Polytechnic University "Antonio José de Sucre"

José Eduardo Rengel Hernández , National Experimental Polytechnic University "Antonio José de Sucre"

Doctoral candidate in Engineering Sciences at the National Experimental Polytechnic University "Antonio José de Sucre"

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Published

2026-03-30

How to Cite

Molina Ortiz, D. ., & Rengel Hernández , J. E. . (2026). Development of a hybrid methodology of computational simulation and deep learning for the optimization of the design of advanced composite plate and fin heat exchangers in the cryogenic condensation of natural gas. Metropolis | Global University Studies Journal, 7(1), 3491-3564. Retrieved from https://metropolis.metrouni.us/index.php/metropolis/article/view/375

Issue

Vol. 7 No. 1 (2026): Metropolis | Journal of Global University Studies | January-June

Section

Artículos

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