Computer vision and machine learning methods for heat transfer and fluid flow in complex structural microchannels: A review
Heat dissipation in high-heat flux micro-devices has become a pressing issue. One of the
most effective methods for removing the high heat load of micro-devices is boiling heat …
most effective methods for removing the high heat load of micro-devices is boiling heat …
Mechanisms and modeling of bubble dynamic behaviors and mass transfer under gravity: a review
S Yan, X Wang, L Zhu, X Zhang, Z Luo - Chemical Engineering Science, 2023 - Elsevier
Bubbly flow is a prototypical two-phase flow problem. The dynamic behavior of bubbles
within a reactor is intrinsically linked to their transport, distribution, and mass transfer, all of …
within a reactor is intrinsically linked to their transport, distribution, and mass transfer, all of …
Automated bubble analysis of high-speed subcooled flow boiling images using U-net transfer learning and global optical flow
JH Seong, M Ravichandran, G Su, B Phillips… - International Journal of …, 2023 - Elsevier
Capturing and analyzing the bubble dynamics is crucial to improving the understanding of
boiling heat transfer mechanisms and predicting boiling heat transfer coefficient and boiling …
boiling heat transfer mechanisms and predicting boiling heat transfer coefficient and boiling …
Machine learning based flow regime recognition in helically coiled tubes using X-ray radiography
The understanding of flow regimes in helical coils is essential in the design and operation of
modern heat exchangers and has been studied therefore intensively over the past decades …
modern heat exchangers and has been studied therefore intensively over the past decades …
Autonomous and online detection of dry areas on a boiling surface using deep learning and infrared thermometry
Capturing the dynamics of dry area patches on a boiling surface is crucial to understanding
and evaluating mechanistic heat flux partitioning and boiling crisis models. We present and …
and evaluating mechanistic heat flux partitioning and boiling crisis models. We present and …
Identification of flow regimes in boiling flow with clustering algorithms: An interpretable machine-learning perspective
The flow regime is the prerequisite to accurately modeling two-phase flow. Unsupervised
machine learning techniques enable the identification of flow regimes objectively. Previous …
machine learning techniques enable the identification of flow regimes objectively. Previous …
Flow regime classification using various dimensionality reduction methods and AutoML
Accurate identification of flow regimes is paramount in several industries, especially in
chemical and hydrocarbon sectors. This paper describes a comprehensive data-driven …
chemical and hydrocarbon sectors. This paper describes a comprehensive data-driven …
Two-phase flow regime identification using multi-method feature extraction and explainable kernel Fisher discriminant analysis
Purpose Identifying the flow regime is a prerequisite for accurately modeling two-phase flow.
This paper aims to introduce a comprehensive data-driven workflow for flow regime …
This paper aims to introduce a comprehensive data-driven workflow for flow regime …
Machine-learning-based modeling of saturated flow boiling in pin-fin micro heat sinks with expanding flow passages
For high potential flow-boiling-based thermal management systems, to better understand the
underlying flow physics and to present an effective predictive approach have critical …
underlying flow physics and to present an effective predictive approach have critical …
[HTML][HTML] Entropy generation for mixed convection flow in vertical annulus with two regions hydromagnetic viscous and Cu-Ag water hybrid nanofluid through porous …
The primary determination of this study is a numerical investigation of the entropy generation
(EG) in the steady two-region flow of viscous fluid and hybrid nanofluid (NF) in a long-infinite …
(EG) in the steady two-region flow of viscous fluid and hybrid nanofluid (NF) in a long-infinite …