Deep learning-based approach to R-134a bubble detection and analysis for geothermal applications

Deep learning-based approach to R-134a bubble detection and analysis for geothermal applications

This study utilized deep learning to analyse bubble images of R134a fluid produced on bare and novel oleophilic coated stainless steel heat exchanger plates to compare the heat transfer performance in terms of bubble parameters. This work was carried out as a part of the GeoHex project. The vapour b...

Full description

Bibliographic Details
Main Authors: M. Ahmed, A. Habib, M.M. Nawal, M.M.H. Saikot, M.A.H. Chowdhury, M.A. Hoque, A.K.M. Asaduzzaman, H. Pálsson, P. Björnsson
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Case Studies in Thermal Engineering
Subjects:
Bubble detection
R134a bubble
Image processing
Deep learning
Mask RCNN model
Bubble parameters
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X23006834

Internet

http://www.sciencedirect.com/science/article/pii/S2214157X23006834

Similar Items