This study investigated design recommendations to reduce airborne infection risk in an emergency department by using airflow network simulation. The main design concepts include isolating the source of the airborne pathogen and increasing the ventilation rate. A conventional emergency department is selected as a base model, and influenza is selected as the airborne pathogen examined in the study. The Wells-Riley equation is used to model airborne infection risk in a zone. The simulation results indicate that airborne infection risk exists when a patient releases an influenza pathogen in the emergency department with a ventilation rate of 3 ACH according to the Korean building code. The findings reveal that isolating the airborne pathogen source and increasing the ventilation rate are good methods to prevent airborne infection risk. However, the isolation method can increase the infection risk in a zone with an airborne pathogen source. Thus, it is necessary to simultaneously increase the ventilation in a zone with an airborne pathogen source. Additionally, airborne infection risk continuously increases the cumulative exposure time, and it is desirable to increase the ventilation rate required for a zone based on the residing time of a patient releasing airborne pathogens in a target zone.
If a data center experiences a system outage or fault conditions, it becomes difficult to provide a stable and continuous information technology (IT) service. Therefore, it is critical to design and implement a backup system so that stability can be maintained even in emergency (unforeseen) situations. In this study, an actual 20 MW data center project was analyzed to evaluate the thermal performance of an IT server room during a cooling system outage under six fault conditions. In addition, a method of organizing and systematically managing operational stability and energy efficiency verification was identified for data center construction in accordance with the commissioning process. Up to a chilled water supply temperature of 17 • C and a computer room air handling unit air supply temperature of 24 • C, the temperature of the air flowing into the IT server room fell into the allowable range specified by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers standard (18-27 • C). It was possible to perform allowable operations for approximately 320 s after cooling system outage. Starting at a chilled water supply temperature of 18 • C and an air supply temperature of 25 • C, a rapid temperature increase occurred, which is a serious cause of IT equipment failure. Due to the use of cold aisle containment and designs with relatively high chilled water and air supply temperatures, there is a high possibility that a rapid temperature increase inside an IT server room will occur during a cooling system outage. Thus, the backup system must be activated within 300 s. It is essential to understand the operational characteristics of data centers and design optimal cooling systems to ensure the reliability of high-density data centers. In particular, it is necessary to consider these physical results and to perform an integrated review of the time required for emergency cooling equipment to operate as well as the backup system availability time.As shown in Figure 1, considerable technological infrastructure is required in data centers to meet even the minimum requirements for Tier 1 system availability (96.671% uptime per year), which is the basic level. In specialized colocation data centers for business purposes, enormous system construction costs are required for uninterrupted system operation to ensure Tier 3-4 high availability (95.995-99.982% uptime) [3]. On the other hand, interest in environmental problems such as global warming and the demand for low-energy and high-efficiency buildings is increasing, so the use of excessive facilities in the pursuit of reliability alone must be avoided. Considering these facts, ensuring stable and efficient performance is an important aspect of data center design and implementation. Conventional construction methods are focused on tangible results such as the construction period and financial costs (not quality) necessary to set up the data center infrastructure according to the design plans, which can make it difficult to verify whether non-IT equipment ...
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