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

Supervised Machine Learning Algorithms for Predicting Rate Constants of Ozone Reaction with Micropollutants

(2022) Yajuan Shi et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Machine Learning-Based Operational Modeling of an Electrochemical Reactor: Handling Data Variability and Improving Empirical Models

(2022) Junwei Luo et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Application of Machine Learning-Based Models to Understand and Predict Critical Flux of Oil-in-Water Emulsion in Crossflow Microfiltration

(2022) Henry J. Tanudjaja et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Characteristics of Gas–Solid Mixture Flows through a Packed Moving Bed of Coarse Particles

(2022) Soohwan Hwang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining

(2022) Mingjian Wen et al.   Chemical Science

XAI‐MEG : Combining symbolic AI and machine learning to generate first‐principles models and causal explanations

(2022) Abhishek Sivaram et al.   AICHE JOURNAL

Measuring binary fluidization of nonspherical and spherical particles using machine learning aided image processing

(2022) Cheng Li et al.   AICHE JOURNAL

Integration of machine learning and first principles models

(2022) Lokesh Rajulapati et al.   AICHE JOURNAL

Kinetics-informed neural networks

(2022) Gabriel S. Gusmão et al.   CATALYSIS TODAY

Identifying key features in reactive flows: A tutorial on combining dimensionality reduction, unsupervised clustering, and feature correlation

(2022) Marc Rovira et al.   CHEMICAL ENGINEERING JOURNAL

Physics-inspired architecture for neural network modeling of forces and torques in particle-laden flows

(2022) Arman Seyed-Ahmadi et al.   COMPUTERS & FLUIDS

Machine Learning Assisted Spraying Pattern Recognition for Electrohydrodynamic Atomization System

(2022) Jinxin Wang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Flow Reconstruction and Prediction Based on Small Particle Image Velocimetry Experimental Datasets with Convolutional Neural Networks

(2022) Likun Ma et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

A Machine Learning Study of Predicting Mixing and Segregation Behaviors in a Bidisperse Solid–Liquid Fluidized Bed

(2022) Zhouzun Xie et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Predicting Diffusion Coefficients of Binary and Ternary Supercritical Water Mixtures via Machine and Transfer Learning with Deep Neural Network

(2022) Xiao Zhao et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Reinforcement Learning Approaches for the Optimization of the Partial Oxidation Reaction of Methane

(2022) Marius Neumann et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Application of artificial neural network to predict slug liquid holdup

(2022) Ghassan H. Abdul-Majeed et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Data-driven modeling of coarse mesh turbulence for reactor transient analysis using convolutional recurrent neural networks

(2022) Yang Liu et al.   NUCLEAR ENGINEERING AND DESIGN

BubDepth: A neural network approach to three-dimensional reconstruction of bubble geometry from single-view images

(2022) Chaoyue Gong et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Image identification for two-phase flow patterns based on CNN algorithms

(2022) Feng Nie et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Fast versus Turbulent Fluidization of Geldart Group B particles

(2021) Jia Wei Chew et al.   AICHE JOURNAL

Predicting Chemical Reaction Outcomes: A Grammar Ontology‐based Transformer Framework

(2021) Vipul Mann et al.   AICHE JOURNAL

Machine Learning based Models for Pressure Drop Estimation of Two-phase Adiabatic Air-Water Flow in Micro-finned Tubes: Determination of the Most Promising Dimensionless Feature Set

(2021) Behzad Najafi et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Machine learning for molecular thermodynamics

(2021) Jiaqi DING et al.   CHINESE JOURNAL OF CHEMICAL ENGINEERING

Uncertainty quantification for data-driven turbulence modelling with mondrian forests

(2021) Ashley Scillitoe et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Unsupervised deep learning for super-resolution reconstruction of turbulence

(2021) Hyojin Kim et al.   JOURNAL OF FLUID MECHANICS

Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network

(2021) Weiqi Ji et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm

(2021) Meisam Babanezhad et al.   Scientific Reports

Automated robotic platforms in design and development of formulations

(2021) Liwei Cao et al.   AICHE JOURNAL

A computational workflow to study particle transport and filtration in porous media: coupling CFD and deep learning

(2021) Agnese Marcato et al.   CHEMICAL ENGINEERING JOURNAL

Application of Artificial Intelligence in Computational Fluid Dynamics

(2021) Bo Wang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Prediction of Solid Holdup in a Gas–Solid Circulating Fluidized Bed Riser by Artificial Neural Networks

(2021) Hanbin Zhong et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Sparse identification of multiphase turbulence closures for coupled fluid–particle flows

(2021) S. Beetham et al.   JOURNAL OF FLUID MECHANICS

Toward neural-network-based large eddy simulation: application to turbulent channel flow

(2021) Jonghwan Park et al.   JOURNAL OF FLUID MECHANICS

Bayesian reaction optimization as a tool for chemical synthesis

(2021) Benjamin J. Shields et al.   NATURE

Multiscale digital twin for particle breakage in milling: From nanoindentation to population balance model

(2021) Li Ge Wang et al.   POWDER TECHNOLOGY

Data‐driven modeling of mesoscale solids stress closures for filtered two‐fluid model in gas–particle flows

(2021) Bo Ouyang et al.   AICHE JOURNAL

Conventional and data‐driven modeling of filtered drag, heat transfer, and reaction rate in gas–particle flows

(2021) Li‐Tao Zhu et al.   AICHE JOURNAL

Assessing the effects of fluids flow on heat transfer performance in direct contact heat transfer process through EMD-LSSVM model: An experimental study

(2021) Junwei Huang et al.   APPLIED THERMAL ENGINEERING

A Comparative Study of Machine Learning Methods for Bio-oil Yield Prediction – A Genetic Algorithm-Based Features Selection

(2021) Zahid Ullah et al.   BIORESOURCE TECHNOLOGY

An Adaptive Sampling Surrogate Model Building Framework for the Optimization of Reaction Systems

(2021) Robert E. Franzoi et al.   COMPUTERS & CHEMICAL ENGINEERING

A Neural Network-Inspired Matrix Formulation of Chemical Kinetics for Acceleration on GPUs

(2021) Shivam Barwey et al.   Energies

A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications

(2021) Navid Zobeiry et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Physics-Informed Neural Networks for Heat Transfer Problems

(2021) Shengze Cai et al.   JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME

Machine learning–accelerated computational fluid dynamics

(2021) Dmitrii Kochkov et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation

(2021) Hasan Asy’ari Arief et al.   SENSORS

Deep learning-based automated and universal bubble detection and mask extraction in complex two-phase flows

(2021) Yewon Kim et al.   Scientific Reports

Reconstruction of large‐scale flow structures in a stirred tank from limited sensor data

(2021) Kirill Mikhaylov et al.   AICHE JOURNAL

Machine learning prediction and optimization of bio-oil production from hydrothermal liquefaction of algae

(2021) Weijin Zhang et al.   BIORESOURCE TECHNOLOGY

A machine learning model for predicting the mass transfer performance of rotating packed beds based on a least squares support vector machine approach

(2021) Wei Zhang et al.   Chemical Engineering and Processing-Process Intensification

Data driven reaction mechanism estimation via transient kinetics and machine learning

(2021) M. Ross Kunz et al.   CHEMICAL ENGINEERING JOURNAL

Machine Learning for Chemical Reactions

(2021) Markus Meuwly   CHEMICAL REVIEWS

Species reaction rate modelling based on physics-guided machine learning

(2021) Ryota Nakazawa et al.   COMBUSTION AND FLAME

Investigation of the chemical vapor deposition of Cu from copper amidinate through data driven efficient CFD modelling

(2021) R. Spencer et al.   COMPUTERS & CHEMICAL ENGINEERING

“pySiRC”: Machine Learning Combined with Molecular Fingerprints to Predict the Reaction Rate Constant of the Radical-Based Oxidation Processes of Aqueous Organic Contaminants

(2021) Flávio Olimpio Sanches-Neto et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Data-Driven Prediction of Minimum Fluidization Velocity in Gas-Fluidized Beds Using Data Extracted by Text Mining

(2021) Jibin Zhou et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Estimation of Kinetic Parameters and Simulation of Methylacetylene and Propadiene Liquid-Phase Selective Hydrogenation Reactor Considering the Catalyst Deactivation

(2021) Pouria Ghasemigoudarzi et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Large-eddy simulation of droplet-laden decaying isotropic turbulence using artificial neural networks

(2021) Andreas Freund et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass

(2021) Sheng Zhao et al.   Journal of Cleaner Production

Status, Challenges, and Potential for Machine Learning in Understanding and Applying Heat Transfer Phenomena

(2021) Matthew T. Hughes et al.   JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME

Data-driven machine learning for accurate prediction and statistical quantification of two phase flow regimes

(2021) Naseem Ali et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics

(2021) Weiqi Ji et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Best practices in machine learning for chemistry

(2021) Nongnuch Artrith et al.   Nature Chemistry

Simulation of multi-species flow and heat transfer using physics-informed neural networks

(2021) R. Laubscher   PHYSICS OF FLUIDS

Performance prediction of pneumatic conveying of powders using artificial neural network method

(2021) Shijo J.S. et al.   POWDER TECHNOLOGY

A data-based soft-sensor approach to estimating raceway depth in ironmaking blast furnaces

(2021) Wangyan Li et al.   POWDER TECHNOLOGY

Machine learning prediction of pyrolytic gas yield and compositions with feature reduction methods: Effects of pyrolysis conditions and biomass characteristics

(2021) Qinghui Tang et al.   BIORESOURCE TECHNOLOGY

Machine learning based analysis of reaction phenomena in catalytic lignin depolymerization

(2021) Abraham Castro Garcia et al.   BIORESOURCE TECHNOLOGY

The role of machine learning to boost the bioenergy and biofuels conversion

(2021) Zhengxin Wang et al.   BIORESOURCE TECHNOLOGY

A flexible image processing technique for measuring bubble parameters based on a neural network

(2021) Yichuan He et al.   CHEMICAL ENGINEERING JOURNAL

Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening

(2021) Jie Li et al.   CHEMICAL ENGINEERING JOURNAL

Speeding up turbulent reactive flow simulation via a deep artificial neural network: A methodology study

(2021) Yi Ouyang et al.   CHEMICAL ENGINEERING JOURNAL

Fast estimation of standard enthalpy of formation with chemical accuracy by artificial neural network correction of low-level-of-theory ab initio calculations

(2021) Pieter P. Plehiers et al.   CHEMICAL ENGINEERING JOURNAL

Physics-informed deep learning for modelling particle aggregation and breakage processes

(2021) Xizhong Chen et al.   CHEMICAL ENGINEERING JOURNAL

ANN prediction of particle flow characteristics in a drum based on synthetic acoustic signals from DEM simulations

(2021) Yaoyu Li et al.   CHEMICAL ENGINEERING SCIENCE

Using an encoder-decoder convolutional neural network to predict the solid holdup patterns in a pseudo-2d fluidized bed

(2021) H. Bazai et al.   CHEMICAL ENGINEERING SCIENCE

Machine learning accelerated discrete element modeling of granular flows

(2021) Liqiang Lu et al.   CHEMICAL ENGINEERING SCIENCE

Data-centric Engineering: integrating simulation, machine learning and statistics. Challenges and opportunities

(2021) Indranil Pan et al.   CHEMICAL ENGINEERING SCIENCE

A hybrid mesoscale closure combining CFD and deep learning for coarse-grid prediction of gas-particle flow dynamics

(2021) Bo Ouyang et al.   CHEMICAL ENGINEERING SCIENCE

Machine learning in solid heterogeneous catalysis: Recent developments, challenges and perspectives

(2021) Yani Guan et al.   CHEMICAL ENGINEERING SCIENCE

Coupling Artificial Neural Network with EMMS drag for simulation of dense fluidized beds

(2021) Zhuo Yang et al.   CHEMICAL ENGINEERING SCIENCE

Void fraction measurement using modal decomposition and ensemble learning in vertical annular flow

(2021) Chaofan Li et al.   CHEMICAL ENGINEERING SCIENCE

Machine learning acceleration for nonlinear solvers applied to multiphase porous media flow

(2021) V.L.S. Silva et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Image Reconstruction in Electrical Capacitance Tomography Based on Deep Neural Networks

(2021) Wael Deabes et al.   IEEE SENSORS JOURNAL

Cluster Identification by a k-means Algorithm-Assisted Imaging Method in a Laboratory-Scale Circulating Fluidized Bed

(2021) Chengxiu Wang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Development of a Filtered CFD-DEM Drag Model with Multiscale Markers Using an Artificial Neural Network and Nonlinear Regression

(2021) Liqiang Lu et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Feasibility Study on the Use of Artificial Neural Networks to Model Catalytic Oxidation in a Metallic Foam Reactor

(2021) Mino Woo et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

New Smart Models for Minimum Fluidization Velocity Forecasting in the Tapered Fluidized Beds Based on Particle Size Distribution

(2021) Seyyed Hossein Hosseini et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Data-driven algebraic models of the turbulent Prandtl number for buoyancy-affected flow near a vertical surface

(2021) Xiaowei Xu et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Machine learning algorithms to predict flow boiling pressure drop in mini/micro-channels based on universal consolidated data

(2021) Yue Qiu et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Multiphase flowrate measurement with time series sensing data and sequential model

(2021) Haokun Wang et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Development of two-phase flow regime map for thermally stimulated flows using deep learning and image segmentation technique

(2021) Hibal Ahmad et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Machine learning classification of in-tube condensation flow patterns using visualization

(2021) M.K. Seal et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Progress towards machine learning reaction rate constants

(2021) Evan Komp et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Machine learning accelerated turbulence modeling of transient flashing jets

(2021) David Schmidt et al.   PHYSICS OF FLUIDS

A machine learning-based interaction force model for non-spherical and irregular particles in low Reynolds number incompressible flows

(2021) Soohwan Hwang et al.   POWDER TECHNOLOGY

Solution and Parameter Identification of a Fixed-Bed Reactor Model for Catalytic CO2 Methanation Using Physics-Informed Neural Networks

(2021) Son Ich Ngo et al.   Catalysts

Bayesian based reaction optimization for complex continuous gas–liquid–solid reactions

(2021) Runzhe Liang et al.   Reaction Chemistry & Engineering

Artificial intelligence in reaction prediction and chemical synthesis

(2021) Venkat Venkatasubramanian et al.   Current Opinion in Chemical Engineering

Machine learning based position‐rendering algorithms for Radioactive Particle Tracking (RPT) experimentation

(2020) Ashutosh Yadav et al.   AICHE JOURNAL

The Exploration of Chemical Reaction Networks

(2020) Jan P. Unsleber et al.   Annual Review of Physical Chemistry

A hybrid deep learning and mechanistic kinetics model for the prediction of fluid catalytic cracking performance

(2020) Fan Yang et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

(2020) Maziar Raissi et al.   SCIENCE

Measurement of Gas-Oil Two-Phase Flow Patterns by Using CNN Algorithm Based on Dual ECT Sensors with Venturi Tube

(2020) Zhuoqun Xu et al.   SENSORS

Using deep learning to recognize liquid–liquid flow patterns in microchannels

(2020) Chong Shen et al.   AICHE JOURNAL

Machine learning to assist filtered two‐fluid model development for dense gas–particle flows

(2020) Li‐Tao Zhu et al.   AICHE JOURNAL

Training set design for Machine Learning techniques applied to the approximation of computationally intensive first-principles kinetic models

(2020) Mauro Bracconi et al.   CHEMICAL ENGINEERING JOURNAL

BubCNN: Bubble detection using Faster RCNN and shape regression network

(2020) Tim Haas et al.   CHEMICAL ENGINEERING SCIENCE

Application of machine learning methods to understand and predict circulating fluidized bed riser flow characteristics

(2020) Jia Wei Chew et al.   CHEMICAL ENGINEERING SCIENCE

Modeling of the filtered drag force in gas–solid flows via a deep learning approach

(2020) Yu Zhang et al.   CHEMICAL ENGINEERING SCIENCE

An artificial neural network approach to recognise kinetic models from experimental data

(2020) Marco Quaglio et al.   COMPUTERS & CHEMICAL ENGINEERING

Time-resolved reconstruction of flow field around a circular cylinder by recurrent neural networks based on non-time-resolved particle image velocimetry measurements

(2020) Xiaowei Jin et al.   EXPERIMENTS IN FLUIDS

Operation and Optimization of Microwave-Heated Continuous-Flow Microfluidics

(2020) Tai-Ying Chen et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Deep Learning of Activation Energies

(2020) Colin A. Grambow et al.   Journal of Physical Chemistry Letters

A perspective on machine learning in turbulent flows

(2020) Sandeep Pandey et al.   JOURNAL OF TURBULENCE

Computational Fluid Dynamics for Fixed Bed Reactor Design

(2020) Anthony G. Dixon et al.   Annual Review of Chemical and Biomolecular Engineering

Introducing an Artificial Neural Network Energy Minimization Multi-Scale drag scheme for fluidized particles

(2020) Aristeidis Nikolopoulos et al.   CHEMICAL ENGINEERING SCIENCE

Data-Driven Surrogate Modeling ofMultiphase Flows Using Machine Learning Techniques

(2020) Himakar Ganti et al.   COMPUTERS & FLUIDS

Machine learning for heat transfer correlations

(2020) Beomjin Kwon et al.   INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER

Application of Machine Learning to Investigation of Heat and Mass Transfer Over a Cylinder Surrounded by Porous Media—The Radial Basic Function Network

(2020) Rasool Alizadeh et al.   JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME

Microstructure-informed probability-driven point-particle model for hydrodynamic forces and torques in particle-laden flows

(2020) Arman Seyed-Ahmadi et al.   JOURNAL OF FLUID MECHANICS

A mobile robotic chemist

(2020) Benjamin Burger et al.   NATURE

Multi-objective optimization of guide vanes for axial flow cyclone using CFD, SVM, and NSGA II algorithm

(2020) Yajun Deng et al.   POWDER TECHNOLOGY

CFD-based reduced-order modeling of fluidized-bed biomass fast pyrolysis using artificial neural network

(2020) Hanbin Zhong et al.   RENEWABLE ENERGY

Machine learning in experimental materials chemistry

(2020) Balaranjan Selvaratnam et al.   CATALYSIS TODAY

Sparse scattered high performance computing data driven artificial neural networks for multi-dimensional optimization of buoyancy driven heat and mass transfer in porous structures

(2020) Yan Su et al.   CHEMICAL ENGINEERING JOURNAL

Key influence of clusters of Geldart Group B particles in a circulating fluidized bed riser

(2020) Aakash M. Patel et al.   CHEMICAL ENGINEERING JOURNAL

Rapid, Automated Determination of Reaction Models and Kinetic Parameters

(2020) Connor J. Taylor et al.   CHEMICAL ENGINEERING JOURNAL

Development of Data-Driven Filtered Drag Model for Industrial-Scale Fluidized Beds

(2020) Yundi Jiang et al.   CHEMICAL ENGINEERING SCIENCE

Chemistry reduction using machine learning trained from non-premixed micro-mixing modeling: Application to DNS of a syngas turbulent oxy-flame with side-wall effects

(2020) Kaidi Wan et al.   COMBUSTION AND FLAME

Neural-network-based control of discrete-phase concentration in a gas-particle corner flow with optimal energy consumption

(2020) Xingyu Zhang et al.   COMPUTERS & MATHEMATICS WITH APPLICATIONS

Design Space Exploration of Turbulent Multiphase Flows Using Machine Learning-Based Surrogate Model

(2020) Himakar Ganti et al.   Energies

Dense particle tracking using a learned predictive model

(2020) Kevin Mallery et al.   EXPERIMENTS IN FLUIDS

CNN-LSTM based reduced order modeling of two-dimensional unsteady flows around a circular cylinder at different Reynolds numbers

(2020) Kazuto Hasegawa et al.   FLUID DYNAMICS RESEARCH

Machine learning prediction of thermal transport in porous media with physics-based descriptors

(2020) Han Wei et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Deep Learning Interfacial Momentum Closures in Coarse-Mesh CFD Two-Phase Flow Simulation Using Validation Data

(2020) Han Bao et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

(2020) Han Bao et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Machine Learning Quantum Reaction Rate Constants

(2020) Evan Komp et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Generative adversarial networks for dual-modality electrical tomography in multi-phase flow measurement

(2020) Zihan Xia et al.   MEASUREMENT

ECT Attention Reverse Mapping algorithm: visualization of flow pattern heatmap based on CNN and its impact on ECT image reconstruction

(2020) Zhuoqun Xu et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Coarse-grid simulations of full-loop gas-solid flows using a hybrid drag model: Investigations on turbulence models

(2020) Jun-Sen Li et al.   POWDER TECHNOLOGY

Bubbly flow prediction with randomized neural cells artificial learning and fuzzy systems based on k–ε turbulence and Eulerian model data set

(2020) Meisam Babanezhad et al.   Scientific Reports

Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems

(2020) Nikhil Muralidhar et al.   Big Data

Mesoscale drag modeling: a critical review

(2020) Wei Wang et al.   Current Opinion in Chemical Engineering

Formulating turbulence closures using sparse regression with embedded form invariance

(2020) S. Beetham et al.   Physical Review Fluids

Study of filtered interphase heat transfer using highly resolved CFD–DEM simulations

(2020) He Lei et al.   AICHE JOURNAL

Computational fluid dynamics analysis and optimisation of polymerase chain reaction thermal flow systems

(2020) Hazim S. Hamad et al.   APPLIED THERMAL ENGINEERING

Machine learning assisted measurement of solid mass flow rate in horizontal pneumatic conveying by acoustic emission detection

(2020) Peng Zhang et al.   CHEMICAL ENGINEERING SCIENCE

Analysis and development of homogeneous drag closure for filtered mesoscale modeling of fluidized gas-particle flows

(2020) Li-Tao Zhu et al.   CHEMICAL ENGINEERING SCIENCE

Do particle-related parameters influence circulating fluidized bed (CFB) riser flux and elutriation?

(2020) Jia Wei Chew et al.   CHEMICAL ENGINEERING SCIENCE

Super-resolution and denoising of 4D-Flow MRI using physics-Informed deep neural nets

(2020) Mojtaba F. Fathi et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Random Forest and Autoencoder Data-Driven Models for Prediction of Dispersed-Phase Holdup and Drop Size in Rotating Disc Contactors

(2020) Swetha Saraswathi K. et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Machine learning algorithms to predict flow condensation heat transfer coefficient in mini/micro-channel utilizing universal data

(2020) Liwei Zhou et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Application of generative deep learning to predict temperature, flow and species distributions using simulation data of a methane combustor

(2020) Ryno Laubscher et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Multi-task prediction and optimization of hydrochar properties from high-moisture municipal solid waste: Application of machine learning on waste-to-resource

(2020) Jie Li et al.   JOURNAL OF CLEANER PRODUCTION

Machine-learning-based spatio-temporal super resolution reconstruction of turbulent flows

(2020) Kai Fukami et al.   JOURNAL OF FLUID MECHANICS

Solvent Selection for Mitsunobu Reaction Driven by an Active Learning Surrogate Model

(2020) Chonghuan Zhang et al.   ORGANIC PROCESS RESEARCH & DEVELOPMENT

DMTO: A Sustainable Methanol-to-Olefins Technology

(2020) Mao Ye et al.   Engineering

A gray-box model for real-time transient temperature predictions in data centers

(2020) Sahar Asgari et al.   APPLIED THERMAL ENGINEERING

Analysis and development of novel data-driven drag models based on direct numerical simulations of fluidized beds

(2020) Kun Luo et al.   CHEMICAL ENGINEERING SCIENCE

Reinforcement learning based optimization of process chromatography for continuous processing of biopharmaceuticals

(2020) Saxena Nikita et al.   CHEMICAL ENGINEERING SCIENCE

Development of a deep learning-based image processing technique for bubble pattern recognition and shape reconstruction in dense bubbly flows

(2020) Rafael F.L. Cerqueira et al.   CHEMICAL ENGINEERING SCIENCE

A combined data-driven and discrete modelling approach to predict particle flow in rotating drums

(2020) Yaoyu Li et al.   CHEMICAL ENGINEERING SCIENCE

An adaptive CEEMD-ANN algorithm and its application in pneumatic conveying flow pattern identification

(2020) Jiming Li et al.   FLOW MEASUREMENT AND INSTRUMENTATION

Supervised learning method for the physical field reconstruction in a nanofluid heat transfer problem

(2020) Tianyuan Liu et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

A unified framework for the mathematical modelling, predictive analysis, and optimization of reaction systems using computational fluid dynamics, deep neural network and genetic algorithm: A case of butadiene synthesis

(2020) Dela Quarme Gbadago et al.   CHEMICAL ENGINEERING JOURNAL

Machine learning methods for turbulence modeling in subsonic flows around airfoils

(2019) Linyang Zhu et al.   PHYSICS OF FLUIDS

A supervised machine learning approach for predicting variable drag forces on spherical particles in suspension

(2019) Long He et al.   POWDER TECHNOLOGY

110th Anniversary: Commentary: CFD as a Modeling Tool for Fixed Bed Reactors

(2019) Behnam Partopour et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Zonal Eddy Viscosity Models Based on Machine Learning

(2019) R. Matai et al.   FLOW TURBULENCE AND COMBUSTION

Model Predictive Control of Phthalic Anhydride Synthesis in a Fixed-Bed Catalytic Reactor via Machine Learning Modeling

(2019) Zhe Wu et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

A machine learning approach for electrical capacitance tomography measurement of gas-solid fluidized beds

(2019) Qiang Guo et al.   AICHE JOURNAL

Discerning Complex Reaction Networks Using Automated Generators

(2019) Sergio Vernuccio et al.   AICHE JOURNAL

Flow regime identification of swirling gas-liquid flow with image processing technique and neural networks

(2019) Li Liu et al.   CHEMICAL ENGINEERING SCIENCE

Application of support vector machine on controlling the silanol groups of silica xerogel with the aid of segmented continuous flow reactor

(2019) Chuan Wang et al.   CHEMICAL ENGINEERING SCIENCE

A hybrid point-particle force model that combines physical and data-driven approaches

(2019) W.C. Moore et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Fast flow field prediction over airfoils using deep learning approach

(2019) Vinothkumar Sekar et al.   PHYSICS OF FLUIDS

Recent advances in machine learning towards multiscale soft materials design

(2019) Nicholas E Jackson et al.   Current Opinion in Chemical Engineering

Advances of machine learning in molecular modeling and simulation

(2019) Mojtaba Haghighatlari et al.   Current Opinion in Chemical Engineering

Machine learning for fast and reliable solution of time-dependent differential equations

(2019) F. Regazzoni et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Quantification of model uncertainty in RANS simulations: A review

(2019) Heng Xiao et al.   PROGRESS IN AEROSPACE SCIENCES

Machine Learning for Fluid Mechanics

(2019) Steven L. Brunton et al.   Annual Review of Fluid Mechanics

Machine learning prediction of biochar yield and carbon contents in biochar based on biomass characteristics and pyrolysis conditions

(2019) Xinzhe Zhu et al.   BIORESOURCE TECHNOLOGY

Generating Data-Driven Models from Molecular-Level Kinetic Models: A Kinetic Model Speedup Strategy

(2019) Pratyush Agarwal et al.   ENERGY & FUELS

Uncertainty quantification of two-phase flow and boiling heat transfer simulations through a data-driven modular Bayesian approach

(2019) Yang Liu et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Machine learning for predicting properties of porous media from 2d X-ray images

(2019) Naif Alqahtani et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

A Machine Learning Approach for Prediction of Rate Constants

(2019) Paul L. Houston et al.   Journal of Physical Chemistry Letters

A data-driven framework for error estimation and mesh-model optimization in system-level thermal-hydraulic simulation

(2019) Han Bao et al.   NUCLEAR ENGINEERING AND DESIGN

Uncertainty quantification of fluidized beds using a data-driven framework

(2019) V.M. Krushnarao Kotteda et al.   POWDER TECHNOLOGY

Drag coefficient prediction for non-spherical particles in dense gas–solid two-phase flow using artificial neural network

(2019) Shengnan Yan et al.   POWDER TECHNOLOGY

A robotic platform for flow synthesis of organic compounds informed by AI planning

(2019) Connor W. Coley et al.   SCIENCE

Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning

(2019) Zhihao Zhang et al.   Mathematics

On flow regime transition in trickle bed: Development of a novel deep‐learning‐assisted image analysis method

(2019) Chao Wang et al.   AICHE JOURNAL

Autonomous discovery in the chemical sciences part I: Progress

(2019) Klavs F. Jensen et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Automated self-optimisation of multi-step reaction and separation processes using machine learning

(2019) Adam D. Clayton et al.   CHEMICAL ENGINEERING JOURNAL

Machine learning-based modeling and operation for ALD of SiO2 thin-films using data from a multiscale CFD simulation

(2019) Yangyao Ding et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Numerical modelling and multi-objective optimization of the novel hydrocyclone for ultra-fine particles classification

(2019) Junxiang Ye et al.   CHEMICAL ENGINEERING SCIENCE

Computing interface curvature from volume fractions: A machine learning approach

(2019) H.V. Patel et al.   COMPUTERS & FLUIDS

Artificial Intelligence in Steam Cracking Modeling: A Deep Learning Algorithm for Detailed Effluent Prediction

(2019) Pieter P. Plehiers et al.   Engineering

Predicting heat transfer of oscillating heat pipes for machining processes based on extreme gradient boosting algorithm

(2019) Ning Qian et al.   APPLIED THERMAL ENGINEERING

Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

(2019) Georgios Kissas et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

An ingenious characterization of reaction network using sub-network reconstruction

(2019) Kexin Bi et al.   COMPUTERS & CHEMICAL ENGINEERING

Data-driven, variational model reduction of high-dimensional reaction networks

(2019) Markos A. Katsoulakis et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Machine learning methods applied to drilling rate of penetration prediction and optimization - A review

(2019) Luís Felipe F.M. Barbosa et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow

(2019) Rui Fang et al.   JOURNAL OF TURBULENCE

Two-phase flow void fraction estimation based on bubble image segmentation using Randomized Hough Transform with Neural Network (RHTN)

(2019) Pedro L.S. Serra et al.   PROGRESS IN NUCLEAR ENERGY

Machine Learning for Catalysis Informatics: Recent Applications and Prospects

(2019) Takashi Toyao et al.   ACS Catalysis

Bubble patterns recognition using neural networks: Application to the analysis of a two-phase bubbly jet

(2019) Igor Poletaev et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Particle Image Velocimetry Based on a Deep Learning Motion Estimator

(2019) Shengze Cai et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Assessment of mesoscale solid stress in coarse-grid TFM simulation of Geldart A particles in all fluidization regimes

(2018) Xi Gao et al.   AICHE JOURNAL

Machine learning for heterogeneous catalyst design and discovery

(2018) Bryan R. Goldsmith et al.   AICHE JOURNAL

Prediction of product distribution and bio-oil heating value of biomass fast pyrolysis

(2018) Xing Chen et al.   CHEMICAL ENGINEERING AND PROCESSING

Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives

(2018) Artur M. Schweidtmann et al.   CHEMICAL ENGINEERING JOURNAL

Mass transfer study of water deoxygenation in a rotor–stator reactor based on principal component regression method

(2018) Zemeng Zhao et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Random Forests for mapping and analysis of microkinetics models

(2018) Behnam Partopour et al.   COMPUTERS & CHEMICAL ENGINEERING

Application of soft computing techniques to multiphase flow measurement: A review

(2018) Yong Yan et al.   FLOW MEASUREMENT AND INSTRUMENTATION

Deep Learning-Based Inversion Method for Imaging Problems in Electrical Capacitance Tomography

(2018) Jing Lei et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Data-driven reconstruction method for electrical capacitance tomography

(2018) J. Lei et al.   NEUROCOMPUTING

Evaluation of correlations for minimum fluidization velocity ( Umf ) in gas-solid fluidization

(2018) Aditya Anantharaman et al.   POWDER TECHNOLOGY

A soft-sensor approach to mixing rate determination in powder mixers

(2018) Pesila Ratnayake et al.   POWDER TECHNOLOGY

Analysis and optimization of cyclone separators with eccentric vortex finders using large eddy simulation and artificial neural network

(2018) Lakhbir Singh Brar et al.   SEPARATION AND PURIFICATION TECHNOLOGY

Toward Constitutive Models for Momentum, Species, and Energy Transport in Gas–Particle Flows

(2018) Sankaran Sundaresan et al.   Annual Review of Chemical and Biomolecular Engineering

Physics-informed machine learning approach for augmenting turbulence models: A comprehensive framework

(2018) Jin-Long Wu et al.   Physical Review Fluids

Turbulence Modeling in the Age of Data

(2018) Karthik Duraisamy et al.   Annual Review of Fluid Mechanics

Data-driven modeling for boiling heat transfer: Using deep neural networks and high-fidelity simulation results

(2018) Yang Liu et al.   APPLIED THERMAL ENGINEERING

Application of convolutional neural networks to large-scale naphtha pyrolysis kinetic modeling

(2018) Feng HUA et al.   CHINESE JOURNAL OF CHEMICAL ENGINEERING

Optimization and Control of a Thin Film Growth Process: A Hybrid First Principles/Artificial Neural Network Based Multiscale Modelling Approach

(2018) Donovan Chaffart et al.   COMPUTERS & CHEMICAL ENGINEERING

An artificial intelligence based approach to predicting syngas composition for downdraft biomass gasification

(2018) Ali Yener Mutlu et al.   ENERGY

The promise of artificial intelligence in chemical engineering: Is it here, finally?

(2018) Venkat Venkatasubramanian   AICHE JOURNAL

Computing curvature for volume of fluid methods using machine learning

(2018) Yinghe Qi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Investigations of data-driven closure for subgrid-scale stress in large-eddy simulation

(2018) Zhuo Wang et al.   PHYSICS OF FLUIDS

Neural-network-based filtered drag model for gas-particle flows

(2018) Yundi Jiang et al.   POWDER TECHNOLOGY

Reduced-Order Modeling of Subsurface Multi-phase Flow Models Using Deep Residual Recurrent Neural Networks

(2018) J. Nagoor Kani et al.   TRANSPORT IN POROUS MEDIA

Using Machine Learning To Predict Suitable Conditions for Organic Reactions

(2018) Hanyu Gao et al.   ACS Central Science

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

The development of algebraic stress models using a novel evolutionary algorithm

(2017) J. Weatheritt et al.   INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW

Micro/meso simulation of a fluidized bed in a homogeneous bubbling regime

(2017) Amir Esteghamatian et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

(2017) Lijuan Wang et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Analysis and optimization of multi-inlet gas cyclones using large eddy simulation and artificial neural network

(2017) Lakhbir Singh Brar et al.   POWDER TECHNOLOGY

Big Data Analytics in Chemical Engineering

(2017) Leo Chiang et al.   Annual Review of Chemical and Biomolecular Engineering

To address surface reaction network complexity using scaling relations machine learning and DFT calculations

(2017) Zachary W. Ulissi et al.   Nature Communications

Optimizing Chemical Reactions with Deep Reinforcement Learning

(2017) Zhenpeng Zhou et al.   ACS Central Science

Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data

(2017) Jian-Xun Wang et al.   Physical Review Fluids

Data science: Accelerating innovation and discovery in chemical engineering

(2016) David A. C. Beck et al.   AICHE JOURNAL

CFD Investigation and neutral network modeling of heat transfer and pressure drop of nanofluids in double pipe helically baffled heat exchanger with a 3-D fined tube

(2016) Mahdi Saeedan et al.   APPLIED THERMAL ENGINEERING

Application of Filtered Model for Reacting Gas–Solid Flows and Optimization in a Large-Scale Methanol-to-Olefin Fluidized-Bed Reactor

(2016) Li-Tao Zhu et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Using statistical learning to close two-fluid multiphase flow equations for bubbly flows in vertical channels

(2016) Ming Ma et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Prediction of water holdup in vertical and inclined oil–water two-phase flow using artificial neural network

(2016) Sadra Azizi et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

A paradigm for data-driven predictive modeling using field inversion and machine learning

(2016) Eric J. Parish et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations: A data-driven, physics-informed Bayesian approach

(2016) H. Xiao et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

(2016) Julia Ling et al.   JOURNAL OF FLUID MECHANICS

Machine-learning-assisted materials discovery using failed experiments

(2016) Paul Raccuglia et al.   NATURE

Data-driven fluid simulations using regression forests

(2015) L'ubor Ladický et al.   ACM TRANSACTIONS ON GRAPHICS

Review of entrainment correlations in gas–solid fluidization

(2015) Jia Wei Chew et al.   CHEMICAL ENGINEERING JOURNAL

Pressure drop estimation in horizontal annuli for liquid–gas 2 phase flow: Comparison of mechanistic models and computational intelligence techniques

(2015) Reza Ettehadi Osgouei et al.   COMPUTERS & FLUIDS

Accuracy of Finite Volume/Staggered Grid Distributed Lagrange Multiplier/Fictitious Domain simulations of particulate flows

(2015) Anthony Wachs et al.   COMPUTERS & FLUIDS

Prediction of Two-Phase Heat Transfer Coefficients in a Horizontal Pipe for Different Inclined Positions With Artificial Neural Networks

(2015) Najmeh Sobhanifar et al.   JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME

Using statistical learning to close two-fluid multiphase flow equations for a simple bubbly system

(2015) Ming Ma et al.   PHYSICS OF FLUIDS

CFD prediction of scale-up effect on the hydrodynamic behaviors of a pilot-plant fluidized bed reactor and preliminary exploration of its application for non-pelletizing polyethylene process

(2015) Yu Che et al.   POWDER TECHNOLOGY

A combination of computational fluid dynamics (CFD) and adaptive neuro-fuzzy system (ANFIS) for prediction of the bubble column hydrodynamics

(2015) M. Pourtousi et al.   POWDER TECHNOLOGY

Automatic discovery and optimization of chemical processes

(2015) Claudia Houben et al.   Current Opinion in Chemical Engineering

Review of direct numerical simulation of fluid–particle mass, momentum and heat transfer in dense gas–solid flows

(2014) Niels G. Deen et al.   CHEMICAL ENGINEERING SCIENCE

Measurement of gas and liquid flow rates in two-phase pipe flows by the application of machine learning techniques to differential pressure signals

(2014) H. Shaban et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Multiphase flow pattern recognition in pipeline–riser system by statistical feature clustering of pressure fluctuations

(2013) Jing Ye et al.   CHEMICAL ENGINEERING SCIENCE

A novel unified correlation model using ensemble support vector regression for prediction of flooding velocity in randomly packed towers

(2013) Yi Liu et al.   JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY

CFD modeling and multi-objective optimization of cyclone geometry using desirability function, artificial neural networks and genetic algorithms

(2012) Khairy Elsayed et al.   APPLIED MATHEMATICAL MODELLING

Support vector regression models for trickle bed reactors

(2012) Shubh Bansal et al.   CHEMICAL ENGINEERING JOURNAL

Investigation of artificial neural network methodology for modeling of a liquid–solid circulating fluidized bed riser

(2012) Shaikh A. Razzak et al.   POWDER TECHNOLOGY

Large-Eddy-Simulation Tools for Multiphase Flows

(2011) Rodney O. Fox   Annual Review of Fluid Mechanics

Identification of gas/solid two-phase flow regimes using electrostatic sensors and neural-network techniques

(2011) H.L. Hu et al.   FLOW MEASUREMENT AND INSTRUMENTATION

IDENTIFICATION OF GAS–SOLID TWO-PHASE FLOW REGIMES USING HILBERT–HUANG TRANSFORM AND NEURAL-NETWORK TECHNIQUES

(2011) H. L. Hu et al.   INSTRUMENTATION SCIENCE & TECHNOLOGY

Modeling, analysis and optimization of aircyclones using artificial neural network, response surface methodology and CFD simulation approaches

(2011) Khairy Elsayed et al.   POWDER TECHNOLOGY

Flow regime recognition in spouted bed based on recurrence plot method

(2011) Chunhua Wang et al.   POWDER TECHNOLOGY

Modeling and Pareto optimization of gas cyclone separator performance using RBF type artificial neural networks and genetic algorithms

(2011) Khairy Elsayed et al.   POWDER TECHNOLOGY

Reengineering Aircraft Structural Life Prediction Using a Digital Twin

(2011) Eric J. Tuegel et al.   International Journal of Aerospace Engineering

Estimation of heat transfer coefficient in bubble column reactors using support vector regression

(2010) Ankit B. Gandhi et al.   CHEMICAL ENGINEERING JOURNAL

Prediction of Pressure Drop of Slurry Flow in Pipeline by Hybrid Support Vector Regression and Genetic Algorithm Model

(2009) S.K. Lahiri et al.   CHINESE JOURNAL OF CHEMICAL ENGINEERING

Development of Unified Correlations for Volumetric Mass-Transfer Coefficient and Effective Interfacial Area in Bubble Column Reactors for Various Gas−Liquid Systems Using Support Vector Regression

(2009) Ankit B. Gandhi et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Identification of two-phase flow regimes based on support vector machine and electrical capacitance tomography

(2009) H X Wang et al.   MEASUREMENT SCIENCE and TECHNOLOGY

An algorithm for predicting the hydrodynamic and mass transfer parameters in bubble column and slurry bubble column reactors

(2008) Romain Lemoine et al.   FUEL PROCESSING TECHNOLOGY

SVR-based prediction of point gas hold-up for bubble column reactor through recurrence quantification analysis of LDA time-series

(2008) A.B. Gandhi et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

Development of an artificial neural network correlation for prediction of hold-up of slurry transport in pipelines

(2007) S.K. Lahiri et al.   CHEMICAL ENGINEERING SCIENCE