HEAT EXCHANGER DESIGN USING COMPUTATIONAL OPTIMIZATION
DOI:
https://doi.org/10.66238/jaeee1Keywords:
Heat Exchanger Design, Computational Optimization, Genetic Algorithm, Thermal PerformanceAbstract
Heat exchangers are critical components in industrial and HVAC applications for efficient thermal energy transfer. The design of heat exchangers involves multiple complex variables and constraints, often making traditional design methods inefficient. This paper presents a comprehensive study on the design of heat exchangers utilizing computational optimization techniques such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN). The integration of these methods helps achieve improved thermal performance, reduced pressure drop, and minimized manufacturing costs. Results indicate that computational optimization significantly enhances design efficiency and operational reliability. Case studies on shell-and-tube and plate heat exchangers demonstrate the practical application and optimization potential in the context of Pakistan’s industrial sectors.
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Copyright (c) 2025 Asif Mehmood, Bilal Khan
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