Modelling for digital twins—potential role of surrogate models
The application of white box models in digital twins is often hindered by missing knowledge,
uncertain information and computational difficulties. Our aim was to overview the difficulties …
uncertain information and computational difficulties. Our aim was to overview the difficulties …
Current trends in fluid research in the era of artificial intelligence: a review
Computational methods in fluid research have been progressing during the past few years,
driven by the incorporation of massive amounts of data, either in textual or graphical form …
driven by the incorporation of massive amounts of data, either in textual or graphical form …
Numerical investigation and deep learning-based prediction of heat transfer characteristics and bubble dynamics of subcooled flow boiling in a vertical tube
Subcooled flow boiling presents an enormous ability of heat transfer rate, which is extremely
important in the heat-dissipating systems of many industrial applications, such as power …
important in the heat-dissipating systems of many industrial applications, such as power …
[HTML][HTML] An artificial neural network model for the prediction of entrained droplet fraction in annular gas-liquid two-phase flow in vertical pipes
The entrained droplet fraction (e) is an important quantity in annuar gas-liquid two-phase
flows as it allows more precise calculation of the gas core density. This results in more …
flows as it allows more precise calculation of the gas core density. This results in more …
Application of artificial neural network to multiphase flow metering: A review
S Bahrami, S Alamdari, M Farajmashaei… - Flow Measurement and …, 2024 - Elsevier
Multiphase flow has many applications, such as oil and gas industries. Flow meter devices
must be calibrated with field or laboratory data. One of the best methods to calibrate the …
must be calibrated with field or laboratory data. One of the best methods to calibrate the …
[HTML][HTML] An artificial neural network visible mathematical model for real-time prediction of multiphase flowing bottom-hole pressure in wellbores
Accurate prediction of multiphase flowing bottom-hole pressure (FBHP) in wellbores is an
important factor required for optimal tubing design and production optimization. Existing …
important factor required for optimal tubing design and production optimization. Existing …
A CFD-based surrogate model for predicting slurry pipe flow pressure drops
Slurry pipelines are extensively employed in most mining operations to transport raw
materials and tailings. The aim of the paper is twofold: on the one hand, to develop a …
materials and tailings. The aim of the paper is twofold: on the one hand, to develop a …
[HTML][HTML] An adaptive neuro-fuzzy inference system white-box model for real-time multiphase flowing bottom-hole pressure prediction in wellbores
The majority of published empirical correlations and mechanistic models are unable to
provide accurate flowing bottom-hole pressure (FBHP) predictions when real-time field well …
provide accurate flowing bottom-hole pressure (FBHP) predictions when real-time field well …
Enhanced predictive modeling of Nusselt number in boiler tubes: numerical simulations and machine learning for water and SiO2/water
This research investigates the complex phenomenon of nanofluid flow boiling and its
associated heat transfer characteristics. Employing advanced numerical simulations and …
associated heat transfer characteristics. Employing advanced numerical simulations and …
Convex and concave envelopes of artificial neural network activation functions for deterministic global optimization
In this work, we present general methods to construct convex/concave relaxations of the
activation functions that are commonly chosen for artificial neural networks (ANNs). The …
activation functions that are commonly chosen for artificial neural networks (ANNs). The …