ผลกระทบของการเปลี่ยนแปลงอัตราการระบายอากาศตาม ข้อมูลความหนาแน่นของบุคคลในอาคารสำนักงานเพื่อ ป้องกันการแพร่กระจายเชื้อโรคโควิด-19

• 主要作者: พิชชาพร ประพิณศรี
• 其他作者: สรัล ศาลากิจ
• 格式: Theses and Dissertations
• 語言: Thai
• 出版: จุฬาลงกรณ์มหาวิทยาลัย 2022
• 主題: โควิด-19 (โรค); การระบายอากาศ; อาคาร > อากาศพลศาสตร์; COVID-19 (Disease); Ventilation; Buildings > Aerodynamics
• 在線閱讀: https://digiverse.chula.ac.th/Info/item/dc:84441
• 機構: Chulalongkorn University

The airborne transmission of pathogens through the respiratory system has been a challenge that humans have faced since the past. Controlling the environment can reduce the quantity of disease-causing agents and the probability of infection for individual. A risk assessment model in conjunction with a social distancing index and the effectiveness of protective devices is developed. The model has an average deviation of only 10.78 percent from actual airborne transmission data in a total of 11 situations. The model analyzes the relationship between occupancy density and ventilation rates to determine preventive measures against contagious diseases. These measures include setting appropriate occupancy density, time limits, and mandating face mask usage. This study analyzes the appropriate occupancy density and air ventilation rates in areas with limited ventilation rates, following ASHRAE 62.1 standards. Sample areas such as office spaces, restaurants, and bars are considered. The results show that wearing face masks increases occupancy density by 51.52-800 percent compared to not wearing masks. Allowing for higher probability of infection values would enable higher occupancy rates. Adjusting ventilation rates based on occupancy density helps maintain infection probability below 0.02 for a 3-hour stay. Wearing masks reduces ventilation rates but they remain higher than standards. Standard rates may not be enough to keep infection probability low. The predicted ventilation rates lead to higher energy consumption and electricity costs, exceeding the standards for both the case of not wearing a mask and wearing a mask, with percentages of 1,351 – 1,802 and 169 – 269, respectively.