Automation in Advanced Fluid Flow Analysis: Revolutionizing Thermal Management Solutions in Engineering
DOI:
https://doi.org/10.18034/abcjar.v13i1.786Keywords:
Automation, Fluid Flow Analysis, Thermal Management, Artificial Intelligence (AI), Machine Learning (ML), Computational Fluid Dynamics (CFD), Design OptimizationAbstract
This paper examines how automation in advanced fluid flow analysis has transformed engineering thermal management systems. The primary goal is to study how AI, ML, and HPC may improve fluid dynamics simulation accuracy, efficiency, and scalability to match the rising complexity of current thermal systems. A thorough literature review synthesizes AI-driven predictive modeling, real-time monitoring, design optimization, and multiscale analytical advances. AI can increase predictive skills, expedite design processes, and offer adaptive, real-time thermal system management. Automation also integrates multiphysics and multiscale issues, enabling energy-efficient aerospace, automotive, and data center solutions. Data availability, model interpretability, and automation integration with engineering processes remain issues. Standardized frameworks, more cooperation between academics, businesses, and regulators, and investments in accessible, sustainable technology may help foster wider adoption. By tackling these difficulties, fluid flow analysis automation may enhance thermal management, minimize energy consumption, and help build sustainable engineering solutions.
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Copyright (c) 2024 Deekshith Narsina; Arjun Kamisetty; Christopher Ryan Thompson; Krishna Devarapu
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