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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:

Comparison of Standalone and Hybrid Machine Learning Models for Prediction of Critical Heat Flux in Vertical Tubes
Rehan Zubair Khalid, Atta Ullah, Asifullah Khan, et al.
Energies (2023) Vol. 16, Iss. 7, pp. 3182-3182
Open Access | Times Cited: 9

Showing 9 citing articles:

Dependence of critical heat flux in vertical flow systems on dimensional and dimensionless parameters using machine learning
Rehan Zubair Khalid, Atta Ullah, Asifullah Khan, et al.
International Journal of Heat and Mass Transfer (2024) Vol. 225, pp. 125441-125441
Closed Access | Times Cited: 6
Machine learning algorithms to study the relative roles of jet convection and natural convection in the presence of surface roughness elements on enhancement of jet impingement heat transfer
K. Nagesha
International Journal of Thermal Sciences (2024) Vol. 198, pp. 108847-108847
Closed Access | Times Cited: 5
Selection of oxygen carrier for chemical looping combustion of natural gas and syngas fuels – A machine learning approach
Bilal Ahmed, Atta Ullah, Rehan Zubair Khalid, et al.
Energy Conversion and Management (2025) Vol. 332, pp. 119745-119745
Closed Access
Use of Artificial Neural Networks and Decision Tree for Defaulters’ Prediction
Willard S. Ribeiro, Ana L. M. Siqueira, Fábio Sartori Piran, et al.
Springer proceedings in mathematics & statistics (2025), pp. 13-25
Closed Access
Re-examining the input-parameters and AI strategies for Critical Heat Flux prediction
Kai Wang, Da Wang, Xiaoxing Liu, et al.
Energy (2025), pp. 134606-134606
Open Access
Exploring Turbulence and micro-scale mixing mechanisms for enhancing jet impingement heat transfer using micro-roughness elements: A data-driven and numerical analysis
K. Nagesha
International Communications in Heat and Mass Transfer (2025) Vol. 162, pp. 108646-108646
Closed Access
Routing attacks detection in MANET using trust management enabled hybrid machine learning
G. Arulselvan, A. Rajaram
Wireless Networks (2024)
Closed Access | Times Cited: 2
Fault Prediction and Awareness for Power Distribution in Grid Connected RES Using Hybrid Machine Learning
Rajanish Kumar Kaushal, K Raveendra, N. Nagabhooshanam, et al.
Electric Power Components and Systems (2024), pp. 1-22
Closed Access | Times Cited: 1
Improved Heat Transfer Capabilities of Nanofluids—An Assessment Through CFD Analysis
Rehan Zubair Khalid, Mehmood Iqbal, Aitazaz Hassan, et al.
Chemical Engineering & Technology (2024)
Open Access | Times Cited: 1
Prediction of Condensation Heat Transfer of Passive Cooling Systems in Nuclear Power Plants through Machine Learning
Rehan Zubair Khalid, Tauseeq Hussain, Atta Ullah, et al.
(2024), pp. 1-7
Closed Access
An Optimized Stacking Ensemble Learning Model Using 3-Pyramids Technique for the 2006 CHF Groeneveld Look Table Prediction
Messaoud Djeddou, Jehad Al Dallal, Aouatef Hellal, et al.
(2023), pp. 95-99
Closed Access
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