Advances in Thermofluid Simulation for Heat Transfer Optimization in Compact Mechanical Devices

• Author(s): Musa Adekunle Adewoyin ; Enoch Oluwadunmininu Ogunnowo ; Joyce Efekpogua Fiemotongha ; Thompson Odion Igunma ; Adeniyi K. Adeleke
• Paper ID: 1708641
• Page: 116-133
• Published Date: 31-12-2020
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 4 Issue 6 December-2020

Abstract

The increasing demand for high-performance, energy-efficient, and space-saving mechanical systems has driven significant advances in thermofluid simulation for heat transfer optimization, particularly within compact mechanical devices. This paper explores the state-of-the-art developments in computational fluid dynamics (CFD), multiphysics modeling, and artificial intelligence-enhanced simulation techniques used to understand and improve thermal-fluid interactions in miniaturized components. These devices—ranging from micro heat exchangers to compact electronic cooling systems—operate under extreme constraints of size, thermal load, and fluid dynamics, requiring precise simulation for optimal performance. Recent progress in high-resolution meshing, turbulence modeling, and transient heat transfer analysis has enabled engineers to predict and mitigate thermal hotspots, improve flow distribution, and enhance heat dissipation mechanisms. Innovations such as lattice Boltzmann methods, hybrid turbulence models, and conjugate heat transfer (CHT) simulations have refined the accuracy of numerical results, even under complex boundary and operating conditions. Additionally, the integration of machine learning algorithms into the simulation pipeline has accelerated design optimization by enabling real-time parametric studies and predictive analytics. Additive manufacturing has also expanded the design possibilities for compact thermal systems, which in turn necessitates simulation tools capable of handling irregular geometries and non-standard materials. The use of nanofluids and phase change materials (PCMs) is also modeled in modern thermofluid simulation to evaluate their impact on enhancing thermal conductivity and specific heat capacity. This study highlights how simulation-led design can significantly reduce prototyping costs and time-to-market while ensuring reliability and performance in space-constrained applications such as aerospace, automotive electronics, and biomedical devices. The paper concludes with future perspectives on digital twin technology, AI-driven design automation, and the need for further experimental validation to support continued progress in this field.

Keywords

Thermofluid Simulation, Heat Transfer Optimization, Compact Mechanical Devices, CFD, Conjugate Heat Transfer, Nanofluids, Digital Twin, Artificial Intelligence, Micro Heat Exchangers, Additive Manufacturing.

Citations

IRE Journals:
Musa Adekunle Adewoyin , Enoch Oluwadunmininu Ogunnowo , Joyce Efekpogua Fiemotongha , Thompson Odion Igunma , Adeniyi K. Adeleke "Advances in Thermofluid Simulation for Heat Transfer Optimization in Compact Mechanical Devices" Iconic Research And Engineering Journals Volume 4 Issue 6 2020 Page 116-133

IEEE:
Musa Adekunle Adewoyin , Enoch Oluwadunmininu Ogunnowo , Joyce Efekpogua Fiemotongha , Thompson Odion Igunma , Adeniyi K. Adeleke "Advances in Thermofluid Simulation for Heat Transfer Optimization in Compact Mechanical Devices" Iconic Research And Engineering Journals, 4(6)