Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Combustion machine learning: Principles, progress and prospects
Matthias Ihme, Wai Tong Chung, Aashwin Mishra
Progress in Energy and Combustion Science (2022) Vol. 91, pp. 101010-101010
Open Access | Times Cited: 164

Showing 26-50 of 164 citing articles:

Projection-based reduced order modeling of multi-species mixing and combustion
Chenxu Ni, Siyu Ding, Jiabin Li, et al.
Physics of Fluids (2024) Vol. 36, Iss. 7
Closed Access | Times Cited: 5
The importance of accurately modelling soot and radiation coupling in laminar and laboratory-scale turbulent diffusion flames
Fengshan Liu, Jean-Louis Consalvi, Fatiha Nmira
Combustion and Flame (2022) Vol. 258, pp. 112573-112573
Closed Access | Times Cited: 22
High-resolution reconstruction of turbulent flames from sparse data with physics-informed neural networks
Shiyu Liu, Haiou Wang, Jacqueline H. Chen, et al.
Combustion and Flame (2023) Vol. 260, pp. 113275-113275
Closed Access | Times Cited: 12
Flame reconstruction of hydrogen fueled-scramjet combustor based on multi-source information fusion
Mingming Guo, Hao Chen, Ye Tian, et al.
International Journal of Hydrogen Energy (2023) Vol. 48, Iss. 80, pp. 31350-31365
Closed Access | Times Cited: 11
Applications of Machine Learning (ML) and Mathematical Modeling (MM) in Healthcare with Special Focus on Cancer Prognosis and Anticancer Therapy: Current Status and Challenges
Jasmin Hassan, Safiya Mohammed Saeed, Lipika Deka, et al.
Pharmaceutics (2024) Vol. 16, Iss. 2, pp. 260-260
Open Access | Times Cited: 4
Fuzzy Evaluation and Benchmarking Framework for Robust Machine Learning Model in Real-Time Autism Triage Applications
Ghadeer Ghazi Shayea, Mohd Hazli Mohammed Zabil, A. S. Albahri, et al.
International Journal of Computational Intelligence Systems (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 4
Comprehensive deep learning for combustion chemistry integration: Multi-fuel generalization and a posteriori validation in reacting flow
Han Li, Ruixin Yang, Yuan Xu, et al.
Physics of Fluids (2025) Vol. 37, Iss. 1
Closed Access
Blast loading prediction in a typical urban environment based on Bayesian deep learning
Weiwen Peng, Meilin Pan, Chunjiang Leng, et al.
Engineering Applications of Computational Fluid Mechanics (2025) Vol. 19, Iss. 1
Open Access
A Data-Driven Approach to Refine the Partially Stirred Reactor Closure for Turbulent Premixed Flames
Lorenzo Piu, Arthur Péquin, Rodolfo S. M. Freitas, et al.
Flow Turbulence and Combustion (2025)
Open Access
Clasificación de enfermedades en hojas de papa utilizando Transformadores de Visión

NOVASINERGIA REVISTA DIGITAL DE CIENCIA INGENIERÍA Y TECNOLOGÍA (2025) Vol. 8, Iss. 1, pp. 142-156
Open Access
Data-driven modelling of spray flows: current status and future direction
Fatemeh Salehi, Amin Beheshti, Esmaeel Eftekharian, et al.
Journal of the Energy Institute (2025), pp. 101991-101991
Open Access
Experimental analysis and machine learning modeling of the maximum explosion pressure and explosion index of titanium powder
Yujian Zhu, Xiangbao Meng, Jihe Chen, et al.
Journal of industrial safety. (2025)
Open Access
Data-Driven Modeling for Coarse Graining
Richard D. Sandberg, Markus Klein
Cambridge University Press eBooks (2025), pp. 202-221
Closed Access
Paradigms and Tools

Cambridge University Press eBooks (2025), pp. 3-4
Closed Access
Artificial intelligence's applicability in cardiac imaging
Joel J. P. C. Rodrigues, Abdul Razak Mohamed Sikkander, Suman Lata Tripathi, et al.
Elsevier eBooks (2025), pp. 181-195
Closed Access
Exploring surface reaction mechanism using a surface reaction neural network framework
Lin Luo, Qimin Liu, Junhao Sun, et al.
Chemical Engineering Science (2025), pp. 121307-121307
Closed Access
Implicit modeling of equivariant tensor basis with Euclidean turbulence closure neural network
Grzegorz Kaszuba, Tomasz Krakowski, Bartosz Ziegler, et al.
Physics of Fluids (2025) Vol. 37, Iss. 2
Closed Access
Prediction of Droplet Statistics in Sprays Using Deep Neural Networks
Mohsen Broumand, Sean Yun
AIAA SCITECH 2022 Forum (2025)
Closed Access
2D flame temperature and soot concentration reconstruction from partial discrete data via machine learning: A case study
Mingfei Chen, R. Zheng, Xuan Zhao, et al.
Case Studies in Thermal Engineering (2025), pp. 106005-106005
Open Access
Advancements in combustion technologies: A review of innovations, methodologies, and practical applications
Abdellatif M. Sadeq, Raad Z. Homod, Husam Abdulrasool Hasan, et al.
Energy Conversion and Management X (2025), pp. 100964-100964
Open Access
Role of machine learning for predictive modeling for Industry 5.0 and Society 5.0
Seyed Mojtaba Hosseini Bamakan, Faramarz Dehghan, Saeedeh Akbarpour
Elsevier eBooks (2025), pp. 265-285
Closed Access
A novel deep learning approach for investigating liquid fuel injection in combustion system
Syed Azeem Inam, Abdullah Ayub Khan, Noor Ahmed, et al.
Discover Artificial Intelligence (2025) Vol. 5, Iss. 1
Open Access
An improved machine learning method for thermochemistry tabulation, with application to LES-PDF simulations of piloted diffusion and swirl-bluff-body stabilised flames with NOx formation
Tianjie Ding, W.P. Jones, Stelios Rigopoulos
Combustion and Flame (2025) Vol. 277, pp. 114130-114130
Open Access
Efficient and Scalable AIxeleration of Reactive CFD Solvers Coupled with Deep Learning Inference on Heterogeneous Architectures
Fabian Orland, Ludovico Nista, Nick Kocher, et al.
(2025), pp. 45-57
Closed Access
Machine Learning and Its Application to Reacting Flows
N. Swaminathan, Alessandro Parente
Lecture notes in energy (2023)
Open Access | Times Cited: 10

Scroll to top