ArticleACS omega2020
Developing Intelligent Algorithm as a Machine Learning Overview over the Big Data Generated by Euler-Euler Method To Simulate Bubble Column Reactor Hydrodynamics.
Article in ACS omega, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
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- Computational fluid dynamics comparison of prevalent liquid absorbents for the separation of SOScientific reports · 2023Article
- State-of-the-Art Review on the Application of Membrane Bioreactors for Molecular Micro-Contaminant Removal from Aquatic Environment.Membranes · 2022Review
- Neural-based modeling adsorption capacity of metal organic framework materials with application in wastewater treatment.Scientific reports · 2022Article
- Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm.Scientific reports · 2021Article
- Influence of machine learning membership functions and degree of membership function on each input parameter for simulation of reactors.Scientific reports · 2021Article
- Investigation on performance of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) in a combination of CFD modeling for prediction of fluid flow.Scientific reports · 2021Article
- Investigation on performance of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) in a combination of CFD modeling for prediction of fluid flow.Scientific reports · 2021Article
- Thermal prediction of turbulent forced convection of nanofluid using computational fluid dynamics coupled genetic algorithm with fuzzy interface system.Scientific reports · 2021Article
- Velocity prediction of nanofluid in a heated porous pipe: DEFIS learning of CFD results.Scientific reports · 2021Article
- Article
- Pressure and temperature predictions of AlScientific reports · 2021Article
- Liquid temperature prediction in bubbly flow using ant colony optimization algorithm in the fuzzy inference system as a trainer.Scientific reports · 2020Article
- Multidimensional machine learning algorithms to learn liquid velocity inside a cylindrical bubble column reactor.Scientific reports · 2020Article
- Computational Modeling of Transport in Porous Media Using an Adaptive Network-Based Fuzzy Inference System.ACS omega · 2020Article
- High-performance hybrid modeling chemical reactors using differential evolution based fuzzy inference system.Scientific reports · 2020Article
- Prediction of turbulence eddy dissipation of water flow in a heated metal foam tube.Scientific reports · 2020Article
- Functional input and membership characteristics in the accuracy of machine learning approach for estimation of multiphase flow.Scientific reports · 2020Article
- RETRACTED: Mechanistic modeling and numerical simulation of axial flow catalytic reactor for naphtha reforming unit.PloS one · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A bubble column reactor is simulated by a combination of Euler-Euler and adaptive network-based fuzzy inference system (ANFIS) method to develop an understanding of the machine learning (ML) technique in describing complex behavior of multiphase flow in bubble column reactors and for deep learning of input and output connections. In the validation stage of simulations, an intelligent bubble column is created that uses artificial intelligence nodes or neural network nodes, and the results of prediction indicated excellent agreement with computational fluid dynamics (CFD) simulation results. The hydrodynamic characteristics of the air bubbles and the amount of stress inside the bubble column reactor are used as the output of the ANFIS method. This study showed that when a three-dimensional bubble column is trained by a ML method, a similar CFD simulation can be created, which is independent of CFD source data. This type of smart simulation also enables us to avoid repeating the simulations with CFD methods that are time-consuming and computationally expensive for process modeling and optimization.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.