[HTML][HTML] A Review of Non-Uniform Load Distribution and Solutions in Data Centers: Micro-Scale Liquid Cooling and Large-Scale Air Cooling

Y Li, C Zhu, X Li, B Yang - Energies, 2025 - mdpi.com
Nowadays, the number of transistors on electronic components is increasing exponentially
leading to an ultra-high heat flux (106~ 107 W/m2). The non-uniform load distribution on the …

Machine learning-inspired study of dynamical parameters of single vapor bubble under nucleate flow boiling regime

M Moiz, R Prajapat, A Srivastava… - Applied Thermal …, 2025 - Elsevier
Heat transfer performance of nucleate boiling is interlinked with the departure dynamics of
vapor bubbles, which also serves as the basis for heat transfer partitioning schemes and …

Nonintrusive identification of boiling regimes enabled by deep learning based on flow boiling acoustics

K Zhang, J Yang, C Huang, X Huai - International Journal of Heat and Mass …, 2025 - Elsevier
Monitoring two-phase cooling systems and identifying corresponding boiling regimes are
vital to avoid device failure owing to thermal runaway. Boiling acoustic characteristics can be …

Mass transfer estimation in gas–liquid systems through integration of hydrodynamic model and computer vision algorithms

P Mikushin, I Nizovtseva, I Starodumov… - The European Physical …, 2024 - Springer
A novel methodology for estimation of mass transfer in bubbly flows is investigated. The key
advantage of the research is integration of the developed theoretical model of absorption …

Effect of aliphatic alcohol-based and polyglycol polymer-based foaming agents on the water-liquid-vapor interface by means of molecular dynamics

F Retamal, C Solar, JH Saavedra, GR Quezada… - Journal of Molecular …, 2024 - Elsevier
The effect of foaming agents, or frothers, on the water-liquid-vapor interface is studied
through molecular dynamics at different frother concentrations. The frothers are aliphatic …

[HTML][HTML] Bubble Detection in Multiphase Flows Through Computer Vision and Deep Learning for Applied Modeling

I Nizovtseva, P Mikushin, I Starodumov, K Makhaeva… - Mathematics, 2024 - mdpi.com
An innovative method for bubble detection and characterization in multiphase flows using
advanced computer vision and neural network algorithms is introduced. Building on the …

BubbleID: A Deep Learning Framework for Bubble Interface Dynamics Analysis

C Dunlap, C Li, H Pandey, N Le, H Hu - arxiv preprint arxiv:2405.07994, 2024 - arxiv.org
This paper presents BubbleID, a sophisticated deep learning architecture designed to
comprehensively identify both static and dynamic attributes of bubbles within sequences of …