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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Speeding up turbulent reactive flow simulation via a deep artificial neural network: A methodology study
Yi Ouyang, Laurien A. Vandewalle, Lin Chen, et al.
Chemical Engineering Journal (2021) Vol. 429, pp. 132442-132442
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors
Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, et al.
Industrial & Engineering Chemistry Research (2022) Vol. 61, Iss. 28, pp. 9901-9949
Open Access | Times Cited: 133
Prediction of instantaneous yield of bio-oil in fluidized biomass pyrolysis using long short-term memory network based on computational fluid dynamics data
Hanbin Zhong, Zhenyu Wei, Yi Man, et al.
Journal of Cleaner Production (2023) Vol. 391, pp. 136192-136192
Open Access | Times Cited: 44
Quo vadis multiscale modeling in reaction engineering? – A perspective
Gregor D. Wehinger, Matteo Ambrosetti, Raffaele Cheula, et al.
Process Safety and Environmental Protection (2022) Vol. 184, pp. 39-58
Open Access | Times Cited: 49
Current and emerging deep-learning methods for the simulation of fluid dynamics
Mario Lino, Stathi Fotiadis, Anil A. Bharath, et al.
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (2023) Vol. 479, Iss. 2275
Open Access | Times Cited: 19
Intensification of catalytic reactors: A synergic effort of Multiscale Modeling, Machine Learning and Additive Manufacturing
Mauro Bracconi
Chemical Engineering and Processing - Process Intensification (2022) Vol. 181, pp. 109148-109148
Closed Access | Times Cited: 24
A hybrid deep learning framework driven by data and reaction mechanism for predicting sustainable glycolic acid production performance
Xin Zhou, Zhiyang Li, Xiang Feng, et al.
AIChE Journal (2023) Vol. 69, Iss. 7
Closed Access | Times Cited: 12
A simulation study on NOx reduction efficiency in SCR catalysts utilizing a modern C3-CNN algorithm
Peilun Han, Xiaoqian Shen, Boxiong Shen
Fuel (2024) Vol. 363, pp. 130985-130985
Closed Access | Times Cited: 4
Automatic validation and analysis of predictive models by means of big data and data science
Edoardo Ramalli, Timoteo Dinelli, Andrea Nobili, et al.
Chemical Engineering Journal (2022) Vol. 454, pp. 140149-140149
Closed Access | Times Cited: 20
Identifying key features in reactive flows: A tutorial on combining dimensionality reduction, unsupervised clustering, and feature correlation
Marc Rovira, Klas Engvall, Christophe Duwig
Chemical Engineering Journal (2022) Vol. 438, pp. 135250-135250
Open Access | Times Cited: 14
Development of intensified reactors: A process intensification methodology perspective
Yi Ouyang, Geraldine J. Heynderickx, Kevin M. Van Geem
Chemical Engineering and Processing - Process Intensification (2022) Vol. 181, pp. 109164-109164
Open Access | Times Cited: 12
Optimal design of wavy microchannel heat sinks based on prediction and multi-objective optimization algorithm
Yuguo Fu, Xueling Liu, Jian‐Sheng Wang
Energy and AI (2023) Vol. 14, pp. 100260-100260
Open Access | Times Cited: 6
Micromixing intensification by gas introduction in a miniaturized annular rotating flow mixer (MARFM)
Qingchuan Chen, Yubin Wang, Jian Deng, et al.
Chemical Engineering Science (2023) Vol. 272, pp. 118610-118610
Closed Access | Times Cited: 5
High-order models for convection–diffusion-reaction transport in multiscale porous media
Hong Zuo, Ying Yin, Zhiqiang Yang, et al.
Chemical Engineering Science (2023) Vol. 286, pp. 119663-119663
Closed Access | Times Cited: 5
Integrated DNN and CFD model for real-time prediction of furnace waterwall slagging of coal-fired boiler
Hengyu Yin, Xin Liu, Ming Li, et al.
Fuel (2024) Vol. 383, pp. 133847-133847
Closed Access | Times Cited: 1
A Data-Driven Framework for Computationally Efficient Integration of Chemical Kinetics Using Neural Ordinary Differential Equations
Shubhangi Bansude, Farhad Imani, Reza Sheikhi
ASME Open Journal of Engineering (2023) Vol. 2
Closed Access | Times Cited: 3
Deep learning for drag force modelling in dilute, poly-dispersed particle-laden flows with irregular-shaped particles
Soohwan Hwang, Jianhua Pan, Liang‐Shih Fan
Chemical Engineering Science (2022) Vol. 266, pp. 118299-118299
Open Access | Times Cited: 5
Increasing Computational Efficiency of CFD Simulations of Reactive Flows at Catalyst Surfaces through Dynamic Load Balancing
Daniele Micale, Mauro Bracconi, Matteo Maestri
ACS Engineering Au (2024) Vol. 4, Iss. 3, pp. 312-324
Open Access
Acceleration of the complex reacting flow simulation with a generalizable neural network based on meta-learning
Tianzi Bai, Ying Huai, Tingting Liu, et al.
Fuel (2024) Vol. 372, pp. 132173-132173
Closed Access
Gas–liquid and liquid–liquid vortex technology for process intensification
Afroditi Kourou, Siyuan Chen, Yi Ouyang
Current Opinion in Chemical Engineering (2024) Vol. 46, pp. 101056-101056
Closed Access
PEDM: A 3D Position Encoding Diffusion Model for Industrial Cracking Furnace Scalar Field Data Generation
Jian Ding, Hui Cheng, Guihua Hu
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 34, pp. 15276-15290
Closed Access
Artificial Neural Networks and Multivariate Statistical Process Control to improve ammonia removal on membrane bioreactors treating refinery wastewater
Amanda Vitória Santos, Míriam Cristina Santos Amaral, Sílvia Maria Alves Corrêa Oliveira
Journal of Water Process Engineering (2024) Vol. 67, pp. 106126-106126
Closed Access
Integration of Observed Data and Reaction Mechanisms in Deep Learning for Designing Sustainable Glycolic Acid
Xin Zhou
(2024), pp. 105-143
Closed Access
A Data-Driven Framework for Computationally Efficient Integration of Chemical Kinetics Using Neural Ordinary Differential Equations
Shubhangi Bansude, Farhad Imani, Reza Sheikhi
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 1
Automatic Validation and Analysis of Predictive Models By Means of Big Data and Data Science
Edoardo Ramalli, Timoteo Dinelli, Andrea Nobili, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 1
A Simulation Study on Nox Reduction Efficiency in Scr Catalysts Utilizing a Modern C3-Cnn Algorithm
Peilun Han, Xiaoqian Shen, Boxiong Shen
(2023)
Closed Access
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