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남부지역 주거건물의 외피단열변화에 따른 에너지소비량 예측
문진우,한승훈,오세규,Moon, Jin-Woo,Han, Seung-Hoon,Oh, Sai-Gyu 한국주거학회 2011 한국주거학회 논문집 Vol.22 No.1
This study aimed at quantifying the impact of envelope insulation on energy consumption for thermal controls in residential buildings in southern part of Korea. A series of parametric simulations for a range of R-values of walls, roof, floor, and windows were computationally conducted for a prototypical Korean detached house. Analysis revealed that the total amount of heat gain was larger than that of heat loss, while the amount of energy for cooling was smaller than that for heating due to the difference of system efficiency; the envelope heat transfer was more significant for the heat loss, thus, the increase of the envelope insulation was more effective to reduce heating load; and there were certain levels of envelope insulation after which the energy saving effect was not significant. These findings are expected to be a fundamental database for the decision of proper insulation level in Korean residential buildings.
소총발사 거리 및 각도에 따른 전투복 관통흔 파열형태의 분석
문진우,윤영욱,박종혁,이동민,정찬일,최미정 한국과학수사학회 2021 과학수사학회지 Vol.15 No.3
K-2 소총사격 거리(근사(近射); 약 20 cm 및 원사(遠射); 약 25 m)와 각도(90o~15o)가 관통흔에 미치는 영향을 확인하였다. 가로 길이는 근사와 원사 모두에서 측정 수치가 불규칙하여 사격 거리와 각도의 상관관계를 확인할 수 없었으나 세로 길이와 원형판별지수(CDI)에서는 75o 에서 가장 낮고 15o 에서 가장 높았다. 또한, 그래프 상에서 90o 에서 75o 로 갈수록 수치가 감소하고 60o 에서부터 증가하는 형태가 나타났다. 망울, 융단, 인장, 팽창 4종류의 용융흔을 확인하였고 팽창은 근사에서만 보였다. 오물륜은 전투복의 배경색과 원단의 특성으로 인하여 일부 시료(근사; 45o ~15o 및 원사; 60o ~15o )에서만가시적으로 관찰된다. 백화현상은 근사 시료에서만 보였으며, 격발 시 발생하는 고온의 가스와 소염기의 구조적인 영향(11~3시 방향에 존재)으로 발생하는 것으로 추정된다. 전투복 손상 분석 요소 중 용융흔, 백화현상으로는 사격 거리를 추정(근사)할 수 있는 요소로 판단되며, 각도를 추정할 수 있는 요소로는 관통흔의 세로 길이와 CDI 측정이 유용함을 확인할 수 있었다.
Energy Consumption Pattern by Morphological Building Change
문진우,백용규,이광호,김수영 한국생활환경학회 2013 한국생활환경학회지 Vol.20 No.6
This study was conducted to quantify the impact of building space configuration on the heating and cooling energy consumption of buildings. Employing the eQuest simulation tool, a series of parametric simulations was performed to calculate the energy consumption of diverse buildings’ floor areas, space volumes, and numbers of floors. A typical two-story single-family residential building in the two climate zones - the cold and hot/humid regions - in the U.S. was modeled using the simulation tool. The analysis of the simulation results revealed that the heating energy in the coldclimate region was the most significantly used energy component. Thus, the application of an energy-efficient heating system is required. In addition, the building’s floor area, volume of space, and number of floors were proportional to the amount of heating and cooling energy consumed. Therefore, the optimal planning of a building in terms of energy saving is required for improving the building’s energy efficiency.
문진우,Moon, Jin Woo 한국토지주택공사 토지주택연구원 2019 LHI journal of land, housing, and urban affairs Vol.10 No.3
This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.
인공지능망과 뉴로퍼지 모델을 이용한 주거건물 냉난방 시스템 조절 로직 및 예비 성능 시험
문진우,Moon, Jin-Woo 한국주거학회 2011 한국주거학회 논문집 Vol.22 No.3
This study aimed to develop AI- (Artificial Intelligence) based thermal control logics and test their performance for identifying the optimal thermal control method in buildings. For this objective, a conventional Two-Position On/Off logic and two AI-based variable logics, which applied ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System), have developed. Performance of each logic was tested in a typical two-story residential building in U.S.A. using the computer simulation incorporating MATLAB and IBPT (International Building Physics Toolbox). In the analysis of the test results, AI-based control logic presented the advanced thermal comfort with stability compared to the conventional logic while they did not show significant energy saving effects. In conclusion, the predictive and adaptive AI-based control logics have a potential to maintain interior air temperature more comfortably, and the findings in this study could be a solid foundation for identifying the optimal thermal control method in buildings.