Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors
Authors
Keywords
-
Journal
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
Volume 61, Issue 28, Pages 9901-9949
Publisher
American Chemical Society (ACS)
Online
2022-07-07
DOI
10.1021/acs.iecr.2c01036
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- 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
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started