MARATTO

article · Journal of Energy Research and Reviews

Material and Parametric Design Optimization of Improved Heat Transfer Rate of AC Condenser

Abstract

Air conditioner system is made up of a condenser that removes unwanted heat in an enclosure through the refrigerant and transfers the heat outside. Improving the heat transfer of air conditioning condenser is still a difficult task because of the broader set of materials and various parametric designs involved. Due to this high cost, the experimental set-up cost cannot be modified, instead, simulation analysis was introduced in the optimization process in order to achieve a near-optimal solution. The aim of this research is to improve the heat transfer rate for air conditioning condenser by material and parametric design optimization. The system was designed based on one basic parameter optimization: varying the condenser tube diameter. This variable was changed in order to improve the heat transfer of the condenser. Simulations using Computational Fluid Dynamic (CFD) analysis and thermal analysis were carried out to have a better understanding and distinct visualization of the fluid flow and materials used, and to compare the results. The materials that were used for CFD analysis are R32 and R290, and for thermal analysis are copper (C12200) and aluminum. The analysis was done using Analysis System (ANSYS) software. Different parameters were calculated from the results that were obtained and graphs were plotted between various parameters such as heat flux, static pressure, velocity, mass flow rate and total heat transfer. From the CFD analysis, the result shows that R32 has more static pressure, velocity, mass flow rate and total heat transfer than R290 at a condenser tube diameter of 7mm. In thermal analysis, the heat flux is more for copper (C12200) material at a condenser tube diameter of 7mm than aluminum.

Research topics

  • Advanced Sensor and Control Systems
  • Engineering Applied Research

Sustainable Development Goals

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.9734/jenrr/2024/v16i10373

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.