In general, small and medium-sized computer rooms do not have access floors for reasons of increased floor height and increased construction cost. Therefore, the air conditioning method used here applies the method of directly blowing the cold air of the air conditioner into the computer room. In this case, the hot/cold air is not separated, and as the hot air is recirculated, it is re-introduced to the front of the server rack, resulting in a problem that the server cooling efficiency is decreased. In addition, in such a computer room structure, it is difficult to configure and install a containment system. In this study, we tried to understand the problem of the formation airflow in the case of using the existing air conditioning method, and to find a method of configuring the air conditioning environment to improve the cooling efficiency. The purpose of this study was to understand the airflow/temperature distribution in the computer room using the CFD simulation method. In addition, the thermal characteristics of various air-conditioning environments such as the location of the CRAC cold air discharge location, the layout between server rack and CRAC and the containment were reviewed.

In this study, heat exchangers used in data center and building air-conditioners were tested according to the type of heat exchangers to select them for commercial use. The experiment was performed three samples, one micro channel heat exchanger, the same volume oval coil and the same performance oval coil. The experiment conducted under actual operation conditions in the data center and building. Micro-channel heat exchanger has lower air side pressure drop and higher capacity per volume than oval coil. It may be advantageous when the installation small space or the little design static pressure in the fan, such as in-row systems or CRAC installed in data center.

Indirect evaporative coolers (IECs) are widely used for cooling of outdoor air in building air-conditioning and for cooling of indoor air in data center air-conditioning. However, for each case, the inlet air temperature and humidity condition to IEC are different, which may yield different cooling efficiency. In this study, tests were conducted at the two air conditions using two IEC samples having different channel pitch (3 mm × 5 mm, 5 mm × 5 mm). Results showed that the efficiencies of the 3 mm × 5 mm sample were 12~32% larger than those of the 5 mm × 5 mm sample due to 25% larger heat transfer area and the usage of smaller diameter channel. The efficiency was 10% larger at the data center condition than at the building condition. The reason may be attributed to a larger absolute humidity difference between the liquid film and the air at the data center condition. At the same air velocity, the pressure drops at the wet channel were 64~128% larger than those at the dry channel due to the presence of liquid film at the wet channel. Comparison of the data with predictions by the analytical model revealed that both the efficiency and the pressure drop were over-predicted. Possible reason may be the simplification of the channel geometry and the assumption of fully developed flow, which may be improved in the future.

목적 : 본 연구는 국가치매관리사업과 관련된 공공데이터를 수집하여 치매안심센터에서 시행되는 작업치료 의 비용편익분석을 통해 미래의 국가치매관리사업의 효율화 방안을 모색하고자 한다. 연구방법 : 2016년 1월부터 12월까지의 국가치매관리사업 관련 공공데이터를 정보공개 창구를 이용하여 수집하였다. 수집된 자료를 토대로 작업치료 비용편익분석을 위한 각종 변수를 정의하고, 빈도분석 및 산술계산으로 변수의 값을 산출했다. 결과 : 우리나라에서 서울은 모든 자치구에서 치매관리사업을 시행하고 있고, 사업수행인원 전원이 전담인력으로 배치되어 있다. 특히 작업치료 전담인력을 치매안심센터의 96.0%에 배치하여 치매안심센터 서비스에서 작업치료를 제공하고 있다. 치매안심센터에서 시행되는 작업치료의 순 편익은 작업치료 전담인력이 배치된 경우 서울에서 약 73억 원으로 산출되었다. 결론 : 서울과 같은 형태로 국가치매관리사업 사업을 확대하고, 작업치료 전담인력을 통한 프로그램 시행으로 치매관리비용을 절감하는 효과가 있을 것으로 기대된다. 치매 국가책임제 추진으로 치매관리사업이 국가 단위의 보건사업으로 발돋움하고 있는 지금 한정된 보건의료자원을 효율적으로 사용하기 위해서는 치매안심센터에서 작업치료의 확대가 필요할 것으로 보인다.

The costs of large computing facilities like data centers were dominated by the costs of the information technology (IT) equipment that they have in 1990s. As the indirect cost of IT has increased, Total Cost of Ownership(TCO) analysis is required to find the lifetime costs of acquiring, operating, and changing IT equipment. Nowadays, electricity-related costs such as the electrical power used by IT equipment and the facility costs associated with powering and cooling IT equipment has sharply grown. Nonetheless, those electricity-related costs have been underestimated up to now. In this paper, we will develop TCO model for a high performance computing data center and perform TCO analysis. We will also show that the trend towards growing electricity-related IT equipment costs continue, direct IT equipment acquisition costs will not be an critical factor of the economics of computing services.