봄철 치유의 숲 이용객의 열쾌적성 예측을 위한 에너지 수지 모델링
Energy Budget Modeling for Prediction of Thermal Comfort of Healing Forest Visitors in Spring
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초록
본 연구는 COMFA모델을 사용하여 봄철인 4, 5월 대전 치유의 숲 이용객의 열스트레스를 정량화하고 치유의 숲 열쾌적성 예측에 활용하고자 수행되었다. 이 연구는 크게 4단계로 진행하였다. 첫째, 치유의 숲의 이용빈도가 높은 일곱 지점의 열 환경을 측정하였다. 둘째, 직접 측정한 열환경 요소를 COMFA에 적용하여 치유의 숲 이용객의 맑은 날, 부분적으로 흐린 날, 흐린 날의 에너지수지(Energy Budget)를 예측하였다. 셋째, 치유의 숲의 열부하가 높은 장소와 시간을 확인하였다. 넷째, 이용객의 열부하를 완화하는 방안을 제시하였다. 예측 모델 구축 결과, 예측된 세 가지 시나리오 중 화창한 날, 4월의 경우, 13시~18시에 세 지점이 온열질환에 주의해야 한다고 평가되었으며, 화창한 날, 5월의 경우, 11시~17시에 모든 지점이 온열질환에 주의해야 한다고 평가되었다. 치유의 숲 열쾌적성 예측모델을 통해 에너지수지(Energy Budget) 정보를 제공함으로써 치유의 숲 이용객과 공간관리 측면에서 열환경 개선 방안을 제시하였다. 이용객 측면에서, 열쾌적성 예측은 미리 열 스트레스를 대비 함으로써 온열질환을 예방할 수 있다. 또한, 운영 측면에서, 치유의 숲의 계획단계에 열쾌적성을 증진 시킬 수 있는 방안을 사전에 수립할 수 있으므로 공간의 목적에 따라 주 이용공간을 파악하고 해당 공간의 열쾌적성을 증진시켜 치유의 숲의 만족도를 높이고 이용 활성화 향상에 기여할 수 있을 것으로 사료된다.
Abstract
This study was conducted to quantify the heat stress of Daejeon Healing Forest visitors in April and May in spring using the COMFA model and to use it to predict the thermal comfort of the healing forest. This study was largely conducted in four stages. First, the thermal environment at seven points where the frequency of use of the healing forest is high was measured. Second, by applying the thermal environmental elements measured directly to COMFA, the energy budget of healing forest visitors on sunny, partly cloudy, and complete overcast days was predicted. Third, the place and time where the heat load of the healing forest was high were confirmed. Fourth, a plan to alleviate the heat load of users was proposed. As a result of the establishment of the predictive model, among the three predicted scenarios, The three places were evaluated to be careful of thermal diseases on sunny days, April, from 13:00 to 18:00, and The all places were evaluated to be careful of thermal diseases on sunny days, May, from 11:00 to 17:00. By providing energy budget information through the healing forest thermal comfort prediction model, a plan to improve the thermal comfort in terms of healing forest users and space management was proposed. In terms of users, thermal comfort prediction can prevent thermal diseases by preparing for heat stress in advance. In addition, since it is possible to establish a plan in advance to improve the thermal comfort o the healing forest, it is believed that the main use space can be identified according to the purpose of the space and the thermal comfort of the healing forest can be improved.
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