인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Purpose: For economic reasons, several temporary buildings have been planned and built in urban areas. Therefore, in addition to the consideration for material properties and recycling issues, it is time to investigate the sustainable method for improving the thermal comfort of users and the performance of energy use. Method: By utilizing the characteristics of temporary buildings commonly used in industry, this study aims to develop a control model that can maintain the quality of indoor thermal comfort and suppress the increase in excessive energy use. The improved control patterns are calculated by combining a conventional thermostat model with an adaptive process that analyzes the changes in human factors. By learning the control patterns as input variables, a predictive model is developed and its control performance is analyzed. Results: As compared to the conventional thermostat model, the performance of the learning predictive model is improved by about 63% for the consistency of thermal comfort and by about 8% for the reduction of energy use, respectively. The result confirms the possibility that significant energy savings can be achieved while maintaining the usability of temporary buildings where the operational economy is prioritized.
본문·목차
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UCI(KEPA) : I410-151-26-02-094568611
