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RESEARCH PAPER · Industrial & Engineering Chemistry Research · 2022

Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors

Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, Wei‐Cheng Yan, He Lei, Zhe Chen, Zheng‐Hong Luo

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Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and ReactorsOriginalMachine learning for full spatiotemporal acceleration of gas-particle flow simulations29Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform11Machine learning and deep learning modeling and simulation for predicting PM2.5 concentrations91Visualization on the meso-scale particle flow in turbulent fluidized bed reactors with lower H0/D ratios via image processing3Quantitative Structure–Property Relationship Model for Predicting the Propagation Rate Coefficient in Free-Radical Polymerization29Identification of the reaction network for the synthesis of adipic acid using machine learning coupling with target factor analysis3Machine learning-based modeling approaches for estimating pyrolysis products of varied biomass and operating conditions30Decoding of Auditory Imagination Activity Based on Machine Learning Methods1Linear Vector Quantization for the Diagnosis of Ground Bud Necrosis Virus in Tomato3Trans-level multi-scale simulation of porous catalytic systems: Bridging reaction kinetics and reactor performance16Computational Fluid Dynamics5Development of machine learning based droplet diameter prediction model for electrohydrodynamic atomization systems30Data-driven discovery of the governing equation of granular flow in the homogeneous cooling state using sparse regression9Machine learning for hydrothermal treatment of biomass: A review147Machine Learning and Data-Driven Modeling to Discover the Bed Expansion Ratio Correlation for Gas–Liquid–Solid Three-Phase Flows14Prediction of Ammonia Concentration in a Pig House Based on Machine Learning Models and Environmental Parameters38Prediction of Multiphase Flow Rate for Reservoir Modeling Using Deep Neural Networks: Study of Thermal Effects0Prediction of instantaneous yield of bio-oil in fluidized biomass pyrolysis using long short-term memory network based on computational fluid dynamics data60Computer Vision and Machine Learning Methods for Heat Transfer and Fluid Flow in Complex Structural Microchannels: A Review44Machine Learning for Two-Phase Flow Separation in a Liquid–Liquid Interface Manipulation Separator13Oxidative Dehydrogenation of Ethane with CO 2 over the Fe-Co/Al 2 O 3 Catalyst: Experimental Data Assisted AI Models for Prediction of Ethylene Yield18A Review of Physics-Informed Machine Learning in Fluid Mechanics248Machine-learning-aided thermochemical treatment of biomass: a review150Development of Framework of Data-Driven Cavitation Model using CFD Data2Optimization and performance study of bidirectional Savonius tidal turbine cluster with deflectors33Machine learning-aided characterization of microbubbles for venturi bubble generator20A review of high-solid anaerobic digestion (HSAD): From transport phenomena to process design66Development of Gradient Boosting Machines for Estimation of Total and Dynamic Liquid Holdup in Trickle Bed Reactor6Revolutionizing municipal solid waste management (MSWM) with machine learning as a clean resource: Opportunities, challenges and solutions95A hybrid safety monitoring framework for industrial FCC disengager coking rate based on FPM, CFD, and ML27Faster Response Chemical Reaction Using Machine Learning0Novel Correlation for Critical Speed for Solid Suspension in Stirred Tanks Developed Using Machine Learning Models Trained on Literature Data7Smart manufacturing inspired approach to research, development, and scale-up of electrified chemical manufacturing systems9Development of Effective Voidage Correlations in Pilot-Scale Liquid–Solid Fluidized Bed Based on Data-Driven Modeling5Homogeneous drag models in gas–solid fluidization: Big data analytics and conventional correlation5Editorial: Multiphase flow in energy studies and applications—A special issue for MTCUE-20229Regional Logistics Routing Optimization System Based on Fractional Differential Equation Modeling1Numerical Simulation on Effects of Biomass Type on Its Fast Pyrolysis in Fluidized Bed Reactor10CFD-based deep neural networks (DNN) model for predicting the hydrodynamics of fluidized beds34Computer-Aided Bubble Size Control for a Swirling-Flow Bubble Generator4Interpretation of Drop Size Predictions from a Random Forest Model Using Local Interpretable Model-Agnostic Explanations (LIME) in a Rotating Disc Contactor10Development and Evaluation of Deep Learning Models for Predicting Instantaneous Mass Flow Rates of Biomass Fast Pyrolysis in Bubbling Fluidized Beds11Interpolation of probability‐driven model to predict hydrodynamic forces and torques in particle‐laden flows7Physics-informed neural network for modeling force and torque fluctuations in a random array of bidisperse spheres19DNS-Based Turbulent Closures for Sediment Transport Using Symbolic Regression10Optimization of Yield and Conversion Rates in Methane Dry Reforming Using Artificial Neural Networks and the Multiobjective Genetic Algorithm33In Silico Prediction of the Temperature-Dependent Decomposition Rate Coefficients of Symmetrical Azo Compounds6Review of the current status and the potential of machine learning tools in boiling heat transfer21Virtual Issue: A Multiscale View on Molecular and Process Design0Thermodynamic study of magnesium (Mg) production by the Pidgeon process: The distribution of MgO and axial thermal field14Application of the combination on data-driven and discrete element model: Particle segregation prediction and classification in rotary drums12A data-driven model of drop size prediction based on artificial neural networks using small-scale data sets15Accelerating discrete particle simulation of particle-fluid systems14Combining genetic algorithm and deep learning to optimize a chemical kinetic mechanism of ammonia under high pressure17Characterizing Flow and Transport in Biological Vascular Systems: A Review from Physiological and Chemical Engineering Perspectives24Optimization of a Gas–Liquid Dual-Impeller Stirred Tank Based on Deep Learning with a Small Data Set from CFD Simulation20Analysis of cohesive particles mixing behavior in a twin-paddle blender: DEM and machine learning applications13Data driven reduced modeling for fluidized bed with immersed tubes based on PCA and Bi-LSTM neural networks24Retracted: Uncovering the Link Between Deep Learning and Data Science Practices0Bubble Detection with Semantic Segmentation for Multiphase Flow Particle Image Velocimetry0A Deep-Learning Model to Predict the Transient Remediation Efficiency of Oil-Drilling Cuttings by Ozonation0Volume of Fluid Method: A Brief Review29Machine learning applications for biochar studies: A mini-review71Data-Driven Reduced-Order Model for Bubbling Fluidized Beds22AI and machine learning in climate change research: A review of predictive models and environmental impact54Mechanism-enhanced data-driven method for the joint optimization of boiler combustion and selective catalytic reduction systems considering gas temperature deviations23Soft measurement model for wet gas flow rate based on ultrasonic and differential pressure sensing5GPU-accelerated discrete element simulation of granular and gas-solid flows17Learning dense gas-solids flows with physics-encoded neural network model22A deep-learning model for predicting spatiotemporal evolution in reactive fluidized bed reactor17Machine Learning Assisted Characterization of Local Bubble Properties and Its Coupling with the EMMS Bubbling Drag14A hybrid spatial-temporal deep learning prediction model of industrial methanol-to-olefins process9Machine learning rather than trial and error to close morphodynamical tuneable parameters: Application to a two-phase/two-layer model2Machine learning prediction of bio-oil production from the pyrolysis of lignocellulosic biomass: Recent advances and future perspectives44Fundamentals and Applications of Surface Wetting88Deep learning based spraying pattern 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machine learning for biomass pyrolysis45Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows20Identification of gas-solid flow regimes using convolutional neural network techniques23Multiscale Modeling and Artificial Intelligence for Multiphase Flow Science11An improved neural operator framework for large-scale CO2 storage operations12Computational Fluid Dynamics–Deep Neural Network (CFD-DNN) Surrogate Model with Graphical User Interface (GUI) for Predicting Hydrodynamic Parameters in Three-Phase Bubble Column Reactors14Machine Learning for Chemical Looping: Recent Advances and Prospects20Retracted: Exploring the Benefits of Deep Learning for Data Science Practices1A hybrid simulation method integrating CFD and deep learning for gas–liquid bubbly flow27Customized Software Package for the Simultaneous Prediction of Multiple Fluidization Characteristic Parameters in Liquid–Solid Fluidized Beds2Towards random pore model for non-catalytic 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learning methods2A machine learning approach to predict CO2 diffusivity in liquid H2O over a wide pressure and temperature range3Symbolic Regression-Dimensionless Learning Data-Driven Coupled Modeling of the Interpretable Bed Expansion Ratio in a Liquid–Solid Fluidized Bed4An innovation framework for investigating the performance of proton exchange membrane fuel cells: a perspective of the EANN model toward lower emission0Artificial intelligence-driven advances in photocatalytic hydrogen production19Bridging the molecular mechanism and industrial process of zeolite-catalyzed methanol conversion to olefins and ethanol using advanced solid-state NMR spectroscopy17Characterizing Trends in Metering Techniques for Wet Gas Measurement: A Critical Review0Machine Learning Applications in Predicting Co₂ Bubble Dynamics and Mass Transfer Behavior: A Comparative Analysis of Multiple Models0Optimization Model for Reactor Operation Simulation Based on Deep Learning Technology1Progress and Perspectives of Physics-Informed Neural Networks for Tribological Applications with Multiphysics Awareness1Data-driven modelling of spray flows: Current status and future direction11Integrating Order-of-Magnitude Analysis to Physics-Informed Neural Networks for Linear Chromatographic Models5Reactor modeling strategy for the droplet flow reaction system and its application to Prileschajew epoxidation2Experimental study and machine learning prediction of frost characteristics on inclined cold plates0A Machine Learning Approach to Volume Tracking in Multiphase Flow Simulations3Leveraging data-driven strategy for redesigning the tubular fixed bed propane dehydrogenation reactor5CFD-DEM modelling of dense gas-solid reacting flow: Recent advances and challenges73Continuous flow wastewater induced plasma microbubbles for the enhancement of mass transfer and degradation of dye pollutants in a bubble column reactor8From PINNs to PIKANs: recent advances in physics-informed machine learning239Hybrid modelling incorporating reaction and mechanistic data for accelerating the development of isooctanol oxidation2Enhancing random forest model prediction of gas holdup in internal draft airlift loop contactors with genetic algorithms tuning and interpretability6Spatio-temporal transfer learning for multiphase flow prediction in the fluidized bed reactor9

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