• Babita Kumari
• Rahul Sharma

The integration of combined cooling and heating functions in HVAC systems enhances efficiency in terms of time, space, and energy utilization, ultimately leading to cost savings. These systems ensure optimal indoor air quality by providing proper ventilation, filtration, and thermal comfort. Energy efficiency is further improved through the use of non-chlorine-based coolants, driven by advancements in engineering technology. The evolution of HVAC systems from basic ventilation and cooling units to sophisticated solutions has been instrumental in combating airborne illnesses. Tools like Carrier’s Hourly Analysis Program (HAP) facilitate risk mitigation through precise calculations, enabling engineers to tailor HVAC systems for commercial buildings. By leveraging machine learning algorithms, HVAC systems can simulate building energy usage and calculate costs effectively. The proposed work aims to utilize machine learning and HAP software to design HVAC systems, employing Excel for precise thermal load calculations and manual assessments to validate results. A solid understanding of heat, ventilation, thermodynamics fundamentals, and AutoCAD interpretation is essential for designing comprehensive and efficient HVAC systems.

The integration of combined cooling and heating functions in HVAC systems enhances efficiency in terms of time, space, and energy utilization, ultimately leading to cost savings. These systems ensure optimal indoor air quality by providing proper ventilation, filtration, and thermal comfort. Energy efficiency is further improved through the use of non-chlorine-based coolants, driven by advancements in engineering technology. The evolution of HVAC systems from basic ventilation and cooling units to sophisticated solutions has been instrumental in combating airborne illnesses. Tools like Carrier’s Hourly Analysis Program (HAP) facilitate risk mitigation through precise calculations, enabling engineers to tailor HVAC systems for commercial buildings. By leveraging machine learning algorithms, HVAC systems can simulate building energy usage and calculate costs effectively. The proposed work aims to utilize machine learning and HAP software to design HVAC systems, employing Excel for precise thermal load calculations and manual assessments to validate results. A solid understanding of heat, ventilation, thermodynamics fundamentals, and AutoCAD interpretation is essential for designing comprehensive and efficient HVAC systems.

"Enhancing HVAC System Efficiency and Design Through Advanced Engineering Tools and Thermodynamic Principles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.d702-d708, February-2024, Available :http://www.jetir.org/papers/JETIR2402384.pdf

"Enhancing HVAC System Efficiency and Design Through Advanced Engineering Tools and Thermodynamic Principles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppd702-d708, February-2024, Available at : http://www.jetir.org/papers/JETIR2402384.pdf