• 한국BIM학회 논문집
• /
• 제4권2호
• /
• pp.25-32
• /
• 2014

Today, there is a growing need of environment-friendly buildings, so-called 'green', facilities, and energy saving buildings to decrease environmental pollutants released into cities by construction activities. Green-Building Information Modeling (Green-BIM) is a purpose-built solution which supports to forecast energy consumption of 3-D model of a building by augmenting its primary 3-D measurements (width, height and depth) with many more dimensions (e.g. time, costs, social impacts and environmental consequences) throughout a series of sequential phases in the lifecycle of a building. The current study was carried out in order to integrate vegetation systems (particularly green roof and green wall systems) and investigate thermal performance of the new Sainsbury's building which will be built on Melton road, Leicester, United Kingdom. Within this scope, a 3-D building model of the news Sainsbury's building was first developed in $Autodesk^{(R)}$ $Revit^{(R)}$ and this model was then simulated in $Autodesk^{(R)}$ $Ecotect^{(R)}$once weather data of the construction site was obtained from $Autodesk^{(R)}$ Green Building $Studio^{(R)}$. This study primarily analyzed data from (1) solar radiation, (2) heat gains and losses, and (3) heating and cooling loads simulation to evaluate thermal performance of the building integrated with vegetation system or conventionally available envelops. The results showed that building integrated vegetation system can potentially reduce internal solar gains on the building rooftops by creating a 'bioshade'. Heat gains and losses through roofs and walls were markedly diminished by offering greater insulation on the building. Annual energy loads for heating and cooling were significantly reduced by vegetation more significantly through the green roof system in comparison to green wall system.

• 한국태양에너지학회 논문집
• /
• 제33권2호
• /
• pp.28-34
• /
• 2013

It is essential to reduce building energy consumption in office building because government enact policy which encourages building energy certification from 2013. Office building has high cooling energy demand due to large glazed area of facade in these days. Shading devices can be an alternative of reducing high cooling energy demand. So, this study simulated a variety of exterior venetian blinds to know how much building energy be affected by orientation and reflectance of slat. The results of this study are based on Seoul weather data. The following is a summary of this study. 1) As a slat of venetian blinds has the lower reflectance, the more building energy reduced. Reflectance is usually affected by color and material of slat. In case reflectance is 0.2 reduce 4% of building energy than reflectance is 0.8. 2) Horizontal exterior venetian blinds are more effective than vertical exterior venetian blinds in all of orientation. Horizontal shape is average 16% more effective in shading effect than vertical shape. 3) In this case study, the most effective shading device is low reflectance horizontal exterior venetian blinds that result about 18% building energy reduction than no shade model. The results of this research can be used to plan shading devices for energy conservative office building.

• 한국태양에너지학회 논문집
• /
• 제32권spc3호
• /
• pp.185-193
• /
• 2012

Recently rapid urbanization facilitates development of high-rise building complex including apartment and office building in urban area. Many problems related with high -rise building are reported. Especially, unpleasant strong winds in pedestrian area are frequently encountered around the high-rise building. CFD simulation methods are used to analyze the wind environment of pedestrian level in high-rise building block. However, the results show differences between CFD and measurement. This difference is attributed to improper use of CFD. Conventional CFD simulation for wind environment around high-rise building does not describe the effect of trees, shrubs and plants near ground which affect the wind environment of pedestrian level. Canopy model can be used to reproduce the aerodynamic effects of trees, shrubs and plants near ground. In this paper, CFD simulation methods coupled with the tree canopy model to predict wind environment of pedestrian level in high-rise residential building block were suggested and the validity was analyzed by comparison between measurement and CFD results.

• KIEAE Journal
• /
• 제11권2호
• /
• pp.113-122
• /
• 2011

About 30% of the total annual energy consumption on the earth is used in the architectural activities, including construction, maintenance management, and demonstration of a building. Also, 40% of the natural resource consumption, 50% of $CO_2$ emissions, and 20%~50% of industrial waste emissions are produced from a building. Unfortunately, the percentage of its energy consumption is staidly increasing year by year, about 8% every year, and it recently causes a sustainable architectural concept to come to the fore globally. Indeed, the importance of the sustainable architecture is increasingly becoming a worldwide trend. BIM(Building Information Modeling) is considered a new paradigm and a powerful method in building design, construction and maintenance. BIM has characteristics similar to a building's systems. All of the components in a model have a parametric relationship to each other. Understanding and capitalizing on these interrelationships typically takes numerous iterations that span multiple projects. Optimizing the integrated strategies and technologies for a high-performance, sustainable design requires a continual look at understanding how they work together to deliver the best potential. Throughout all of these concepts, we are going to be using a variety of tools that revolve around a BIM model. Some of the tools will require a heavier use of BIM than others, but all of them will utilize the model geometry you've created as part of your design. This study presents importance and validity of energy performance analyzation in the pre-design phase for the sustainable architecture with the support of Building Information Modeling (BIM) technology.

• 한국신재생에너지학회:학술대회논문집
• /
• 한국신재생에너지학회 2011년도 추계학술대회 초록집
• /
• pp.39.2-39.2
• /
• 2011

The new and renewable energy today has a great interest in all countries around the world. In special it has need more limit of the fossil fuel that needs of low carbon emission among the social necessary conditions. Recently, the high-rise building demand the structural safety, the economic feasibility and the functional design. The high-rise building spends enormous energy and it satisfied the design in solving energy requirements. The requirements of energy for the building depends on the partly form wind energy due to the cladding of the building that came from the surroundings of the high-rise building. In this study of the wind energy, the cladding of the building was assessed a tentative study. The wind energy obtains from several small wind powers that came from the building or the surrounding of the building. In making a cladding the wind energy forms with wind pressure by means of energy transformation methods. The assessment for the building cladding was surrounded of wind speed and wind pressure that was carried out as a result of numerical simulation of wind environment and wind pressure which is coefficient around the high-rise building with the computational fluid dynamics. In case of the obtained wind energy from the pressure of the building cladding was estimated by the simulation of CFD of the building. The wind energy at this case was calculated by energy transform methods: the wind pressure coefficients were obtained from the simulated model for wind environment using CFD as follow. The concept for the factor of $E_f$ was suggested in this study. $$C_p=\frac{P_{surface}}{0.5{\rho}V^{2ref}}$$ $$E_c=C_p{\cdot}E_f$$ Where $C_p$ is wind pressure coefficient from CFD, $E_f$ means energy transformation parameter from the principle of the conservation of energy and $E_c$ means energy from the building cladding. The other wind energy that is $E_p$ was assessed by wind power on the building or building surroundings. In this case the small wind power system was carried out for wind energy on the place with the building and it was simulated by computational fluid dynamics. Therefore the total wind energy in the building was calculated as the follows. $$E=E_c+E_p$$ The energy transformation, which is $E_f$ will need more research and estimation for various wind situation of the building. It is necessary for the assessment to make a comparative study about the wind tunnel test or full scale test.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.723-727
• /
• 2015

Building energy use estimation relies on building characteristics, its energy systems, occupants, and weather. Energy estimation of new buildings is considerably an easy task when compared to modeling existing buildings as they require calibration with actual data. Particularly, when energy estimation of existing building stock is warranted at a city-scale, the problem is exacerbated owing to lack of construction drawings and other engineering specifications. However, as collection of buildings and other infrastructure constitute cities, such predictions are a necessary component of developing and maintaining sustainable cities. This paper uses Artificial Neural Network techniques to predict electricity consumption for residential buildings situated in the City of Gainesville, Florida. With the use of 32,813 samples of data vectors that comprise of building floor area, built year, number of stories, and range of monthly energy consumption, this paper extends the prediction to environmental impact assessment of electricity usage at the urban-scale. Among others, one of the applications of the proposed model discussed in this paper is the study of urban scale Life Cycle Assessment, and other decisions related to creating sustainable cities.

• 대한건축학회논문집:구조계
• /
• 제35권2호
• /
• pp.45-52
• /
• 2019

BEMS(Building Energy Management Systems) have been applied to office buildings and collect relevant building energy data, e.g. temperatures, mass flow rates and energy consumptions of building mechanical systems and indoor spaces. The aforementioned measured data can be beneficially utilized for developing data-driven machine learning models which can be then used as part of MPC(Model Predictive Control) and/or optimal control strategies. In this study, the authors developed ANN(Artificial Neural Network) models of an AHU (Air Handling Unit) and a chiller for a real-life office building using BEMS data. Based on the ANN models, the authors developed optimal control strategies, e.g. daily operation schedule with regard to optimal start and stop of the AHU and the chiller (500 RT). It was found that due to the optimal start and stop of the AHU and the chiller, 4.5% and 16.4% of operation hours of the AHU and the chiller could be saved, compared to an existing operation.

• 한국GIS학회:학술대회논문집
• /
• 한국GIS학회 2010년도 추계학술대회
• /
• pp.291-291
• /
• 2010

Emerging global economic growth and increasing demand for energy supply and demand imbalance and the excessive use of fossil fuels existing the rapidly increasing greenhouse gas emissions and resource depletion of global energy crisis is deepening. Accordingly, improvement of living conditions around and through the natural ecological preservation and the need for a comfortable life for the meeting the importance of energy management and consumption are emerging. Many in the field of architecture for energy-saving measures and conducts research and analysis from the early stages to verify the energy performance of BIM (Building Information Model) technology development and commercialization through the building's energy performance to an objective technology forecasts Analysis of the existing building energy performance in waste management also possible that "BIM-based green building process, the possibility of" suggested. In this study, BIM through the analysis of information using the structures for the management of waste, energy and physical data collected by Mapping it can effectively plan resources for recycling were analyzed.

• 설비공학논문집
• /
• 제19권2호
• /
• pp.183-190
• /
• 2007

Controlling superheat of indoor units associated with a multi-type heat pump is one of difficult tasks to be addressed. This study suggests a dynamic model of an evaporator based on heat and mass balance. Thermodynamic properties are calculated by a commercial software, Refprop. The model is programmed in MFC Visual C++ for controller interface in real-time mode. The simulation results shows that PI control works for a narrow range of superheat. Beyond the range, the temperature behavior of the refrigerant is quite nonlinear mainly due to phase change. Thus, it is concluded that PI control of superheat has to be supplemented by nonlinear control ideas to avoid saturation and excessive superheat.

• Journal of Construction Engineering and Project Management
• /
• 제5권4호
• /
• pp.16-22
• /
• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. Several case studies were conducted to experimentally evaluate their impact on BIM-based energy analysis to calculate energy load. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.