Machine Learning for Identifying Characteristics of Isolated, Clustered, and Pulsed Vapor Bubbles on a Heated Surface under Non-Stationary Boiling Conditions › Research Explorer

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Machine Learning for Identifying Characteristics of Isolated, Clustered, and Pulsed Vapor Bubbles on a Heated Surface under Non-Stationary Boiling Conditions

Research output: Contribution to journal › Article › peer-review

Laboratory of Physical and Technical Basics of Energy Generation

DOI

https://doi.org/10.25729/esr.2025.04.0006
Final published version

Original language	English
Article number	6
Pages (from-to)	54-64
Number of pages	11
Journal	Energy Systems Research
Volume	8
Issue number	4
DOIs	https://doi.org/10.25729/esr.2025.04.0006
Publication status	Published - 29 Dec 2025

Research areas

Nucleate boiling, image segmentation, machine learning, maximum bubble diameter, nucleation frequency, nucleation site density, time-averaging

OECD FOS+WOS

2.07 ENVIRONMENTAL ENGINEERING

ID: 74603521