An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid

An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid

Optimising heat transfer in biomedical systems, especially in blood-mediated liquids, is essential for precise medication administration and thermal ablation treatments. However, conventional methods for modelling and optimizing these frameworks frequently encounter challenges owing to their intrica...

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Bibliographic Details
Main Authors: Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
Artificial intelligence
machine learning
neural network
blood-integrated nano-fluid
modified finite difference method
computational fluid dynamics
Online Access:https://www.tandfonline.com/doi/10.1080/19942060.2025.2459664
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https://www.tandfonline.com/doi/10.1080/19942060.2025.2459664

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