Moses Adondua Abah¹
, Micheal Abimbola Oladosu¹
, Abdulshakur Adamsand²
and Ochuele Dominic Agida¹![]()
¹ResearchHub Nexus Institute, Nigeria
²Department of Chemical Engineering, Faculty of Engineering, Lagos State University, Lagos State, Nigeria
(✉) Corresponding Author: m.abah@fuwukari.edu.ng
Received: May 19, 2025/ Revised: June 22, 2025/Accepted: June 24, 2025
Modeling and simulation are crucial in chemical process industries, enabling optimization, prediction, and decision-making. Computational Fluid Dynamics (CFD), Machine Learning (ML), and other digital tools have revolutionized process simulation. This review examines the current state of modeling and simulation techniques, highlighting recent advances and applications. It covers the basics of CFD and ML, and their integration in chemical process simulation. CFD has been widely applied to simulate complex fluid flow, heat transfer, and mass transport phenomena in chemical processes. ML algorithms, such as neural networks and deep learning, are increasingly used for process modeling, optimization, and fault detection. Hybrid approaches combining CFD and ML show promise for simulating complex systems. Digital tools, like process simulation software and data analytics platforms, facilitate process design, operation, and optimization. Case studies demonstrate successful applications in chemical reactors, separation processes, and energy systems. These tools enable predictive modeling, allowing for improved process performance and reduced operational costs. Modeling and simulation are essential for chemical process development and optimization. CFD, ML, and digital tools have transformed process simulation, enabling predictive modeling and decision-making. Future research should focus on integrating emerging technologies to address complex process challenges and improve sustainability, driving innovation in the chemical industry.
Keywords: Modeling, Simulation, Optimization, Computational fluid dynamics, and Machine learning
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How to cite this article
Abah, M. A., Oladosu, M. A., Adamsand, A., & Agida, O. (2025). Modeling and simulation of chemical processes: A review of computational fluid dynamics, machine learning and other digital tools. Chemical and Environmental Science Archives, 5(2), 9–21. https://doi.org/10.47587/CESA.2025.5201
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