Artificial intelligence (AI), machine learning (ML), and data science are leading to a
promising transformative paradigm. ML, especially deep learning and physics-informed ML …

Artificial intelligence (AI) has received a lot of attention with many publications in recent
years. Interestingly related projects in the industry are mostly still in their early stages. We …

Real-time chemical process monitoring, analysis, and control have become increasingly
important to multi-phase flow process research and development and attracted overt …

Flow patterns are essential and useful to model the interfacial structures and heat transfer in
gas-liquid two-phase flow. However, the current two-phase flow patterns classification …

The sub-millimeter bubble technique can enhance the gas–liquid inter-phase mass transfer
by significantly reducing the bubble size and increasing the gas–liquid interfacial area. To …

While investigating multiphase flows experimentally, the spatiotemporal variation in the
interfacial shape between different phases must be measured to analyze the transport …

This work presents a Convolutional Neural Network (CNN) based method for the shape
reconstruction of bubbles in bubbly flows using high-speed camera images. The bubble …

Identifying, counting and measuring particles is an important component of many research
studies. Images with particles are usually processed by hand using a software ruler …

An automated and reliable processing of bubbly flow images is highly needed to analyse
large data sets of comprehensive experimental series. A particular difficulty arises due to …

The direct reduction of iron oxide (DRI) using hydrogen is a promising method for clean
steelmaking. Previous studies used one-dimensional models to explore this non-catalytic …