Abstract Machine learning (ML) offers a variety of techniques to understand many complex
problems in different fields. The field of heat transfer, and thermal systems in general, are …

This review article examines recent advances in the use of machine learning for process
industries. The article presents common process industry tasks that researchers are solving …

Two-phase flow regime identification is an essential transdisciplinary topic that spans digital
signal processing, artificial intelligence, chemical engineering, and energy. Multiphase flow …

Rapid and accurate identification of two-phase flow patterns in porous media is of great
significance to the chemical industry, petroleum and nuclear engineering, etc. Based on the …

The issue of increased reaction resistance due to bubble growth has always been a major
bottleneck limiting the efficiency improvement of photoelectrochemical water splitting. In this …

Accurate and fast recognition of multiphase flow regimes is an urgent requirement for the
flow assurance of oil/gas pipelines. Experiments on gas–liquid flow regimes are conducted …

Currently, workers in nuclear power plants need to monitor plant data in real time. In the
event of an emergency, due to human subjectivity, the operator cannot make accurate …

Two-phase liquid–gas flows are common in industries such as mining, energy, chemicals,
and oil. The gamma-ray absorption technique is a non-contact method widely used to …

Highlights What are the main findings? Machine learning algorithms perform more efficiently
than deep learning methods in classifying gas-liquid flow regimes in pipelines. Extreme …

Large vertical pipes are key structures connecting subsea wells to offshore platforms.
However, existing studies mainly focus on small vertical pipes. In a vertical acrylic pipe with …