In the nuclear fuel cycle (NFC) facilities, the failure of Heating Ventilation and Air Conditioning (HVAC) system starts with minor component failures and can escalate to affecting the entire system, ultimately resulting in radiological consequences to workers. In the field of air-conditioning and refrigerating engineering, the fault detection and diagnosis (FDD) of HVAC systems have been studied since faults occurring in improper routine operations and poor preventive maintenance of HVAC systems result in excessive energy consumption. This paper aims to provide a systematic review of existing FDD methods for HVAC systems therefore explore its potential application in nuclear field. For this goal, typical faults and FDD methods are investigated. The commonly occurring faults of HVAC are identified through various literature including publications from International Energy Agency (IEA) and American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). However, most literature does not explicitly addresses anomalies related to pressure, even though in nuclear facilities, abnormal pressure condition need to be carefully managed, particularly for maintaining radiological contamination differently within each zone. To build simulation model for FDD, the whole-building energy system modeling is needed because HVAC systems are major contributors to the whole building’s energy and thermal comfort, keeping the desired environment for occupants and other purposes. The whole-building energy modeling can be grouped into three categories: physics-based modeling (i.e., white-box models), hybrid modeling (i.e., grey-box models), and data-driven modeling (i.e., black-box models). To create a white-box FDD model, specialized tools such as EnergyPlus for modeling can be used. The EnergyPlus is open source program developed by US-DOE, and features heat balance calculation, enabling the dynamic simulation in transient state by heat balance calculation. The physics based modeling has the advantage of explaining clear cause-and-effect relationships between inputs and outputs based on heat and mass transfer equations, while creating accurate models requires time and effort. Creating a black-box FDD model requires a sufficient quantity and diverse types of operational data for machine learning. Since operation data for HVAC systems in existing nuclear cycle facilities are not fully available, so efforts to establish a monitoring system enabling the collection, storage, and management of sensor data indicating the status of HVAC systems and buildings should be prioritized. Once operational data are available, well-known machine learning methods such as linear regression, support vector machines, random forests, artificial neural networks, and recurrent neural networks (RNNs) can be used to classify and diagnose failures. The challenge with black-box models is the lack of access to failure data from operating facilities. To address this, one can consider developing black-box models using reference failure data provided by IEA or ASHRAE. Given the unavailability of operation data from the operating NFC facilities, there is a need for a short to medium-term plan for the development of a physics-based FDD model. Additionally, the development of a monitoring system to gather useful operation data is essential, which could serve both as a means to validate the physics-based model and as a potential foundation for building data-driven model in the long term.

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.

To ensure the safety and functionality of a railroad bridge, maintaining the integrity of the bridge via continuous structural health monitoring is important. However, most structural integrity monitoring methods proposed to date are based on modal responses which require the extracting process and have limited availability. In this paper, the applicability of the existing damage identification method based on free-vibration reponses to time-domain deflection shapes due to moving train load is investigated. Since the proposed method directly utilizes the time-domain responses of the structure due to the moving vehicles, the extracting process for modal responses can be avoided, and the applicability of structural health evaluation can be enhanced. The feasibility of the presented method is verified via a numerical example of a simple plate girder bridge.

This study investigated the odor-associated bacterial community in automobile HVAC systems. Through a metagenome analysis, it was found that; Massilia (42.426%), Sphingomonas (28.200%), (10.780%), and Methylobacterium (5.756%) were abundant in the HVAC systems. Massilia can cause the biodegradation of polycyclic aromatic hydrocarbons (PAHs) producing odor in automobiles. Sphingomonas produces volatile halogenated compounds or degrades organic pollutants. Rhodococcus is reported to produce sulfur compounds which give off an odor similar to rotting eggs and cabbages. Methylobacterium is one of the most representative bacteria that causes odor in automobile HVAC systems. The evaporator is considered as the appropriate habitat for microorganisms in automobiles because of its high humidity and organic adsorption. Massilia, Sphingomonas, Rhodococcus, Methylobacterium, Bacillus, Staphylococcus, Arthrobacter, Micrococcus, and Pseudomonas, listed in order from most to least present, were isolated as abundant bacteria in the evaporator of the HVAC systems.

In this study, by comparing the heating performance when operating the air conditioning system that is installed directly air-cooled(heater) air conditioning central air conditioning system of the ship, with improved performance, through the actual measurement study of thermal environment of the cabin, Ship's air conditioning in the future it is intended to be used as a basic data experience of design and planning.

In this study, to develop high-efficiency environmental improvement system that can be combined with hot and cold potable water supply to poultry air conditioning for the summer increase heat stress relief and winter feed efficiency through optimal design hwihan The aim of this study was to provide basic data. As a cage the size of the system installed is 100m2 test capacity 20RT district heating and cooling of air-to-water heat pump and the control was composed of electric hot water boilers. First of cage sizes for heating load design, materials, heat pump capacity, air capacity, storage tank, drinking water tank capacity, etc. were determined. The capacity of the heat pump was set to 20RT cage captive birds are erected as vertically and horizontally × height × (13 × 21 × 4.5m). Storage tank 3 tons and capacity of 10 tons potable water tank was designed. In the future, the size of the cage, designed according to the best breeding two numbers are needed.

It is important to understand psychological and physiological responses of occupants who seated in a chair in order to shape a comfortable indoor official environment. So it is needed to find out optimal seated conditions. The purpose of this study was to explore optimal condition of seat air conditioning control based on psychological or subjective responses (perceived temperature and comfort sensation) and physiological responses (heartrate variability; HRV). To do this, experimental conditions were designed by the difference of indoor temperature and seat air conditioning temperature. In the experiment 1, seven experimental conditions were designed with one control condition which was not used seat air conditioning system, and six experimental conditions which the difference of indoor temperature and seat air conditioning temperature (-1℃～-6℃). In the experiment 2, four experimental conditions were designed with one control condition and three experimental conditions (-3℃～-5℃). In addition, participants’ psychological or subjective response was measured by CSV (comfort sensation vote) and PTS (perceived temperature sensitivity) as a psychological or subjective response, and heartrate variability was measured as a physiological response. As a result, in the experiment 1, it was reported that the optimal conditions of seat air conditioning control based on participants’ psychological or subjective comfort were from -3℃ to -5℃ experimental conditions. In addition, in the experiment 2, it was reported that the optimal condition of seat air conditioning control based on participants’ physiological comfort was -4℃ experimental condition. These results suggested that seat air conditioning could affected to comfort sensation of occupants in an appropriate range, rather than unconditionally.

본 연구에서는 목포해양대학교의 실습선 새누리호를 대상으로 선박의 중앙집중 공조시스템에 공랭식 에어컨을 직접 설치하여 성능을 개선시킨 공기조화시스템으로 운전하였을 경우의 냉방 성능을 비교하고, 선실의 온열환경에 대한 실측조사를 통해서 향후 선박용 공기조화 설계 및 계획에 경험적 기초참고자료로 활용하고자 하는 것이다. 연구결과 동일한 외기조건에서 기존의 중앙집중방식 공조시스템과 개선된 공조시스템으로 운전하였을 경우, 모든 선실의 온도는 24~28 ℃, 습도는 55~75 %로 쾌적한 조건임을 알 수 있었고, 발전기 부하를 측정결과 공기조화시스템의 성능개선에 따라 평균 부하 48 KW, 전부하시 부하율 약 8 %정도 감소하여 1일 연료소모량 FOC는 하루 평균 222[L/day]의 기름이 절약됨을 알 수 있었다. 또한 학생 선실(Cadet No. 21)은 기관실의 전열로 인해서 온도가 높게 나타났는데, 이것은 공기조화 설계 시 취출구 개수 및 전열부하를 고려하지 못한 결과로 판단된다.

본 연구에서는 선박의 중앙집중 공조시스템에 공랭식 에어컨(전기히터 내장형)을 직접 설치하여 성능을 개선시킨 공기조화시스템으로 운전하였을 경우의 난방 성능을 비교하고, 선실의 온열환경에 대한 실측조사를 통해서 향후 선박용 공기조화 설계 및 계획에 경험적 기초참고자료로 활용하고자 하는 것이다. 연구결과 동일한 외기조건에서 기존의 중앙집중 방식 공조시스템과 개선된 공조시스템으로 운전하였을 경우..

본 연구는 냉 난방공조 조건에서 예상 온열감 반응(predicted mean vote; PMV)의 변화에 따른 심리 생리적 감성반응의 변화를 살펴보고자 하였다. 이를 위해 기존 공조 시스템의 냉 난방 가동에 따라 PMV의 변화를 유도하고, 쾌/불쾌 및 각성/이완 정도를 심리적 감성반응으로, 심박률(heart rate; HR)을 생리적 감성반응으로 활용하여 PMV 변화에 따른 심리 생리적 감성반응을 측정하였다. 그 결과, 동일한 PMV 변화 범위 내에서 재실자의 심리적 쾌/불쾌 및 긴장/이완 반응과 생리적 반응이 공조 조건이 달라짐에 따라 변화하는 것으로 나타났다. 이러한 결과는 난방과 냉방의 공조조건에 따라 재실자의 실내 온열환경에 대한 감성반응이 서로 다를 뿐 아니라 각 공조 조건에 민감한 감성반응이 존재하는 것으로 해석할 수 있다. 이는 실내 온열조건을 재실자에게 가장 적합하도록 조절하고자 할 때, 인간의 심리 및 생리적 감성반응을 모두 고려해야 할 필요가 있음을 시사한다.

여름철 에너지 절약, 온실가스 줄이기, 직장인의 건강증진 등을 위한 쿨맵시 캠페인에 대하여 범국민 인식 및 실천의 필요를 바탕으로, 본 연구는 착의실험을 통해 클맵시 권장복장 착용시의 생리적 반응 및 주관적 감각에 대해 분석하였다. 1차 실험은 두 복장, 즉 일반복장, 쿨맵시 권장복장에 대한 생리적 반응의 측정으로서, 두 환경기온 25℃와 27℃, 상대습도 50%R.H.에서 20대 성인남성 4명을 대상으로 실험을 행하였다. 일반복장은 긴팔 셔츠 정장바지 차림이었고 쿨맵시 권장복장은 넥타이 없이 반팔셔츠에 정장바지 차림이었다. 피험자는 30분간의 안정기를 가진 후 60분 동안 실험을 실시하였는데 사무실 작업과 유사한 컴퓨터 워드작업을 행하였고, 피부온, 직장온, 의복하 습도, 발한량, 온열감, 습윤감, 쾌적감 등을 측정하였다. 대부분의 반응에서 25℃ 일반복장의 경우와 27℃ 쿨맵시복장의 경우가 유사한 결과를 나타내고 우수한 것으로 나타났다. 25℃ 쿨맵시복장의 경우에는 저강도 작업이 지속되면 직장온의 저하가 우려되었으며 27℃ 일반복장에서는 고 평균 피부온, 고 발한량, 높은 온열감 등을 보였다. 2차 실험은 일반복장을 착용한 채 환경온도를 점진적으로 하강시키면서 권장 여름철 냉방온인 27℃에서 쿨맵시 권장복장을 착용한 경우의 피부온도를 발현시키는 실내 환경온도를 찾는 것이었다. 그 결과 권장복장 경우의 피부온을 나타내려면 일반복장의 경우에는 환경온을 2℃를 더 낮추어야만 하였다. 여름철 실내 환경온을 27℃로 높이고 쿨맵시 권장복장을 착용하는 것이 사무실의 장시간 저강도 작업 하에서는 피부온, 주관적 온열감이 우수하였다.

This study was carried out to investigate the presence of L. pneumophila in indoor air and water collected from 692 air conditioning cooling towers at different public facilities. For these 4 years (2001～2004) of investigation, water samples were collected in high air conditioner operating month (from July to September) at department stores, hotels, offices, hospitals, discount stores, and public agencies. It was found that L. pneumophila was present in water samples from 47 air conditioning cooling towers. The detection rate of L. pneumophila was 7.6% in 2001, 10.7% in 2002, and 9.5% in 2003, respectively. When we compared the 4 air conditioner operating months, the highest rate of L. pneumophila detection was obtained in the water samples of July. The detection rate of L. pneumophila differed among different facilities. The highest detection rate of 17.9% was found in samples from department stores. L. pneumophila was detected similarly in water samples from hospitals (8.3%) and offices (8.2%). pH, temperature, and turbidity in the 47 L. pneumophila positive water samples ranged from pH 7 to 9, from 25℃ to 38℃, and from 1.0 to 3.5, respectively.