Machine learning application with Bayesian regularization for predicting pressure drop in R134a's annular evaporation and condensation

• Published in: Journal of the Brazilian Society of Mechanical Sciences and Engineering Vol. 47; no. 5
• Main Authors: Çolak, Andaç Batur, Bacak, Aykut, Karakoyun, Yakup, Koca, Aliihsan, Dalkilic, Ahmet Selim
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2025; Springer Nature B.V
• Subjects: Artificial intelligence; Artificial neural networks; Bayesian analysis; Condensation; Data points; Deviation; Differential pressure; Engineering; Evaporation; Heat exchangers; Machine learning; Mechanical Engineering; Network analysis; Neural networks; Pressure drop; Regularization; Technical Paper; Vaporization; Evaporation; Bayesian regularization; Pressure drop; Condensation; Machine learning

The study of condensation and evaporation in plain pipes is a significant area of engineering and scientific inquiry, as it has relevance for enhancing and developing various industrial procedures. This study utilized a Bayesian artificial intelligence method to determine the pressure drop in a vert...