A data driven deep neural network model for predicting boiling heat transfer in helical coils under high gravity
Author:
Funder
Royal Academy of Engineering
Publisher
Elsevier BV
Subject
Fluid Flow and Transfer Processes,Mechanical Engineering,Condensed Matter Physics
Reference49 articles.
1. Experimental flow visualization study using particle image velocimetry in a helical coil steam generator with changing lateral pitch geometry;Delgado;Int. J. Heat Mass Transfer,2019
2. Heat transfer enhancement and pressure drop by pulsating flow through helically coiled tube: An experimental study;Khosravi-Bizhaem;Appl. Therm. Eng,2019
3. Experimental investigation of forced convective condensation heat transfer of hydrocarbon refrigerant in a helical tube;Yu;Appl. Therm. Eng,2018
4. Experimental investigation of the heat transfer coefficient and pressure drop of R1234yf during flow condensation in helically coiled tubes;Zakeralhoseini;Int. J. Therm. Sci,2020
5. Two-phase flow condensation heat transfer characteristic of R-600a inside the horizontal smooth and dimpled helical coiled tube in shell type heat exchanger;Solanki;Int. J. Refrig,2019
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