Integrating machine learning with sensor technology for multiphase flow measurement: A review

M Bao, M Wang, K Li, X Jia - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
This article reviews the integration of machine learning (ML) techniques with sensor-based
technologies for multiphase flow measurement in industrial applications. Accurate …

A Flow Rate Estimation Method for Gas-liquid Two-Phase Flow Based on Transformer Neural Network

Y Jiang, H Wang, Y Liu, L Peng, Y Zhang… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Accurately estimating the flow rate of gas–liquid two-phase flow is crucial for reducing costs,
improving efficiency, and optimizing management in multiphase industries. However, due to …

Flow Velocity computation in solid-liquid two-phase flow by convolutional neural network

N Liu, S Yue, Y Wang - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Flow velocity calculation is one of main tasks in the solid-liquid two-phase parameter
detection in dredging engineering. The existing calculation methods for flow velocity mainly …

A Flowrate Estimation Method for Gas-Water Two-Phase Flow Based on Multimodal Sensors and Hybrid LSTM-CNN Model

Y Jiang, Y Liu, B Mao, X Lu, Y Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Accurate flowrate estimation in gas-water two-phase flow is pervasive and important in the
energy industry for monitoring and optimizing the production process. How to accurately …

[HTML][HTML] Deep learning based liquid level extraction from video observations of gas–liquid flows

M Olbrich, L Riazy, T Kretz, T Leonard… - International Journal of …, 2022 - Elsevier
The slug flow pattern is one of the most common gas–liquid flow patterns in multiphase
transportation pipelines, particularly in the oil and gas industry. This flow pattern can cause …

Interior void classification in liquid metal using multi-frequency magnetic induction tomography with a machine learning approach

I Muttakin, M Soleimani - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Identification of gas bubble, void detection and porosity estimation are important factors in
many liquid metal processes. In steel casting, the importance of flow condition and phase …

A flow rate estimation method for gas–liquid two-phase flow based on filter-enhanced convolutional neural network

Y Jiang, Y Liu, L Peng, Y Li - Engineering Applications of Artificial …, 2025 - Elsevier
Accurate estimation of flow rate in gas–liquid two-phase flow is crucial for various industrial
processes. How to accurately estimate flow rate remains a challenging problem. Previously …

One-dimensional convolutional neural network with adaptive moment estimation for modelling of the sand retention test

NNA Razak, SJ Abdulkadir, MA Maoinser… - Applied Sciences, 2021 - mdpi.com
Stand-alone screens (SASs) are active sand control methods where compatible screens and
slot sizes are selected through the sand retention test (SRT) to filter an unacceptable amount …

A study on the anomaly detection of engine clutch engagement/disengagement using machine learning for transmission mounted electric drive type hybrid electric …

Y Ji, S Jeong, Y Cho, H Seo, J Bang, J Kim, H Lee - Applied Sciences, 2021 - mdpi.com
Transmission mounted electric drive type hybrid electric vehicles (HEVs) engage/disengage
an engine clutch when EV↔ HEV mode transitions occur. If this engine clutch is not …

[HTML][HTML] A deep learning computational fluid dynamics solver for simulating liquid hydrogen jets

D Bhatia, J Loukas, A Cabrera, K Lyras - Physics of Fluids, 2024 - pubs.aip.org
Modeling and simulating the sudden depressurization of liquids inside nozzles is a
significant challenge because of the plethora of the associated complex phenomena. This …