Scholarlink

<p>Heat exchangers play a crucial role in improving energy efficiency by transferring heat between fluids, reducing energy consumption, and minimizing environmental impact. Their optimization is essential for lowering operational costs and supporting sustainability in industries such as heating, ventilation, and air conditioning (HVAC) systems. This study aims to assess the comparative heat transfer performance of a heat exchanger when varying three key parameters: refrigerant type (R410A, R407C, and R134A), heat transfer area (0.745, 0.764, and 0.785&#xa0;m²), and mass flow rate of cooling water (0.085, 0.090, and 0.095&#xa0;kg/s), each tested at three levels. The objective is to optimize these design and process parameters to enhance heat exchanger performance for practical applications. This study investigates the optimization of heat transfer rate (Qavg) through a comprehensive analysis utilizing the Taguchi Technique based on an L9 orthogonal array and Multifactor Regression Analysis (MRA). The independent variables considered were refrigerant (REF), condenser area (AREA), and mass flow rate (MFR), while the dependent output was the average heat transfer rate (Qavg). Analysis of the factors contributing to Qavg revealed that refrigerant type was the most influential factor, contributing 44.3%, followed by condenser area at 32.8%, while mass flow rate had the least impact with a contribution of 22.9%. The study also compared two methods for result analysis: the Taguchi-ANOVA technique, which demonstrated applicability with a 95% confidence level, and MRA, which showed poor correlation (R² = 0.32, Adj. R² = 0.096) and was deemed unsuitable. The uncertainty in the experimental results was found to be 3.2%, indicating a high confidence level of approximately 97%. The findings suggest that significant enhancement in heat transfer rate (up to 15%) can be achieved through careful selection of refrigerant, heat exchanger type, and operational conditions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Taguchi-Based Experimentation Technique in Combination with Multifactor Regression for Optimization of Refrigerants, Design and Process Parameters to Maximize Heat Transfer in Heat Pumps

  • 期刊论文

  • 发表日期：

    2025年4月17日

查看全文
  • S. Yogendra Kumar,
  • H. B. Bhaskar,
  • M. Nagamadhu,
  • R. Chandrashekar,
  • N. Lohith

摘要

Heat exchangers play a crucial role in improving energy efficiency by transferring heat between fluids, reducing energy consumption, and minimizing environmental impact. Their optimization is essential for lowering operational costs and supporting sustainability in industries such as heating, ventilation, and air conditioning (HVAC) systems. This study aims to assess the comparative heat transfer performance of a heat exchanger when varying three key parameters: refrigerant type (R410A, R407C, and R134A), heat transfer area (0.745, 0.764, and 0.785 m²), and mass flow rate of cooling water (0.085, 0.090, and 0.095 kg/s), each tested at three levels. The objective is to optimize these design and process parameters to enhance heat exchanger performance for practical applications. This study investigates the optimization of heat transfer rate (Qavg) through a comprehensive analysis utilizing the Taguchi Technique based on an L9 orthogonal array and Multifactor Regression Analysis (MRA). The independent variables considered were refrigerant (REF), condenser area (AREA), and mass flow rate (MFR), while the dependent output was the average heat transfer rate (Qavg). Analysis of the factors contributing to Qavg revealed that refrigerant type was the most influential factor, contributing 44.3%, followed by condenser area at 32.8%, while mass flow rate had the least impact with a contribution of 22.9%. The study also compared two methods for result analysis: the Taguchi-ANOVA technique, which demonstrated applicability with a 95% confidence level, and MRA, which showed poor correlation (R² = 0.32, Adj. R² = 0.096) and was deemed unsuitable. The uncertainty in the experimental results was found to be 3.2%, indicating a high confidence level of approximately 97%. The findings suggest that significant enhancement in heat transfer rate (up to 15%) can be achieved through careful selection of refrigerant, heat exchanger type, and operational conditions.