• 한국산업융합학회 논문집
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• 제25권1호
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• pp.71-78
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• 2022

With the advent of cutting-edge technology, renewable energy is significantly considered as alternative resources to supply electric power. However, many barriers such as energy intermittency, high initial installation cost, and low-efficiency generation challenged building new infrastructure with clean energy. Efforts reducing greenhouse gas emissions and reliance on fossil fuels resulted in the decentralization of power generation like distributed energy resource (DER). This paper is to introduce and evaluate the feasibility of building-integrated photovoltaics (BIPV) in a high-rise building in Ulsan. To optimize BIPV, a variety of methods to minimize efficiency decrease and maximize electric power generation after installing BIPV on the building's facade are suggested. The variables causing power losses are analyzed. By utilizing System Advisor Model (SAM), actual power generated from solar panels is measured by Thin-film PV, Mono-crystalline PV, and Poly-crystalline PV.

• KIEAE Journal
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• 제13권6호
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• pp.83-91
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• 2013

Cool roofs are currently being emerged as one of important mechanism to save energy in relation to the building. It is specifically proposed that the changing trends of rooftop surface temperature in the flat roof building model could be used effectively as an indicator to reduced cooling load reduced by cool roof since it can present stable temperature record, that is not influenced according to the nearby physical as well as human variables. The temperature of cool roof in summer was lower around $20^{\circ}C$, compared to the general roofs. Such a seasonal or daily comparative study for rooftop temperature in the building model will highlight that the cool roof efficiency could be calculated in much area-wide context according to rooftop color distribution in urban residential area. It is anticipated that this research output could be used as a valuable reference in identifying energy saving by cool roof since an objective monitoring has been proposed based on the rooftop temperature in the building model, fully quantitative performance of thermal infrared image.

• Computers and Concrete
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• 제21권4호
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• pp.441-449
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• 2018

FE models for complex or large-scaled structures that need detailed modeling of structural components are usually constructed using commercial analysis softwares. Updating of such FE model by conventional sensitivity-based methods is difficult since repeated computation for perturbed parameters and manual calculations are needed to obtain sensitivity matrix in each iteration. In this study, an FE model updating procedure avoiding such difficulties by using response surface (RS) method and a Pareto-based multiobjective optimization (MOO) was formulated and applied to FE models constructed with a commercial analysis package. The test building is a low-rise reinforced concrete building that has been seismically retrofitted. Dynamic properties of the building were extracted from vibration tests performed before and after the seismic retrofits, respectively. The elastic modulus of concrete and masonry, and spring constants for the expansion joint were updated. Two RS functions representing the errors in the natural frequencies and mode shape, respectively, were obtained and used as the objective functions for MOO. Among the Pareto solutions, the best compromise solution was determined using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) procedure. A similar task was performed for retrofitted building by taking the updating parameters as the stiffness of modified or added members. Obtained parameters of the existing building were reasonably comparable with the current code provisions. However, the stiffness of added concrete shear walls and steel section jacketed members were considerably lower than expectation. Such low values are seemingly because the bond between new and existing concrete was not as good as the monolithically casted members, even though they were connected by the anchoring bars.

• 한국농촌건축학회논문집
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• 제9권3호
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• pp.33-45
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• 2007

Recently, large scale disasters have been occurred in rural areas. Most people suffering from the disaster live in the temporary containers. These could not provide the fundamental occupancy performances such as thermal insulation, ventilation and heating system. It is very important to rebuild the residence for sufferers quickly and safely. Because modular building system has some advantages such as short construction time, mobility, light-weight structure, modularity, flexibility and economical efficiency, it is expected that it could be easily applied to the disaster restoration. So, this research aims at developing the design model of modular building system for disaster restorations in fishing and agrarian villages. For this purpose, current counterplan for restoration was firstly investigated. Also the basic guideline was established through the investigation of current status of residence in fishing and agrarian villages. Finally, 2 types of design model such as single story residence and temporary accommodation facility were proposed. We could see that we could make the flexible building plan when applying the modular building system to the temporary housing for the sufferers.

• KIEAE Journal
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• 제9권1호
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• pp.107-113
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• 2009

The energy cost is resulted from the energy use. Its sources are divided into some types and depended on the building use or energy-use type. The energy cost should be affected by the amount of the energy use. The cost could be calculated to consider various factors such as the insulation, heating type, building shape and others. But it can not consider all of the affect factors to the energy cost and need to categorize the factors to the condition for estimating the cost. In this paper, it aimed at providing the estimation model in linear equation and multiple linear regression, utilizing the building exterior condition and management characteristics in apartment housing. Its survey are conducted in two parts of management characteristics and building exterior condition. The correlation analysis is conducted to get rid of the multicolinearity among the inputted factors. The number of linear equation model is 11 and includes the 1st, 2nd and 3rd equation function, power function and others. Among these, it suggested the 2nd and 3rd function and power function in terms of the statistics. In multiple linear regression model, the building volume and management area are inputted to the estimation.

• 대한건축학회논문집:구조계
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• 제33권12호
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• pp.11-18
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• 2017

The safety inspection cost of the construction work was based on commercial facilities classified as a single building. Therefore, it is not possible to fully reflect the characteristics of the multi-building construction project such as apartment houses. Therefore, this study suggests a reasonable estimation model that can fully reflect the characteristics of the multi-building construction project. The safety inspection cost estimation model proposed two models such as construction cost ratio method and cost plus fixed fee method. And these models were simulated by the apartment construction work and compared with the current standard. As a result, the current construction cost ratio method has shown that the safety inspection cost tends to be overestimated as the construction size increases. Therefore, the proposed model has reflected characteristics of the multi-building construction project, so that it can reasonably estimate the safety inspection cost more than the current standard.

• 국제초고층학회논문집
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• 제9권4호
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• pp.351-360
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• 2020

Monitoring civil structures periodically is necessary for ensuring the fitness of the structures. Cracks on inner and outer surfaces of the building plays a vital role in indicating the health of the building. Conventionally, human visual inspection techniques were carried up to human reachable altitudes. Monitoring of high rise infrastructures cannot be done using this primitive method. Also, there is a necessity for more accurate prediction of cracks on building surfaces for ensuring the health and safety of the building. The proposed research focused on developing an efficient crack classification model using Transfer Learning enabled EfficientNet (TL-EN) architecture. Though many other pre-trained models were available for crack classification, they rely on more number of training parameters for better accuracy. The TL-EN model attained an accuracy of 0.99 with less number of parameters on large dataset. A bench marked METU dataset with 40000 images were used to test and validate the proposed model. The surfaces of high rise buildings were investigated using vision enabled Unmanned Arial Vehicles (UAV). These UAV is fabricated with TL-EN model schema for capturing and analyzing the real time streaming video of building surfaces.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.273-274
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• 2023

Although there are many old school buildings that is more than 40 years in Korea, it is difficult to rebuild all of them due to limitations in budget management. Therefore, objective feasibility evaluation criteria are necessary to determine which school buildings should be rebuilt preferentially among the numerous old school buildings. One of the rebuilding feasibility evaluation items, economic evaluation generally requires documents such as construction statements and facility drawings. However, because most buildings older than 40 years do not have these documents, an economic analysis model that requires only basic building information should be developed. In this study, the economic analysis model that can be used for evaluating the rebuilding feasibility only with the number of years, total floor area, and structural information of school buildings was established. This model can contribute to the objective feasibility evaluation of old school buildings because it can evaluate numerous buildings on the same criteria based on basic building information.

• Wind and Structures
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• 제14권3호
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• pp.253-283
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• 2011

This paper presents the field measurement results of wind effects on a super-tall building (CITIC Plaza, 391 m high) located in Guangzhou. The field data such as wind speed, wind direction and acceleration responses were simultaneously and continuously recorded from the tall building by a wind and vibration monitoring system during two typhoons. The typhoon-generated wind characteristics including turbulence intensity, gust factor, peak factor, turbulence integral length scale and power spectral density of fluctuating wind speed were presented and discussed. The dynamic characteristics of the tall building were determined based on the field measurements and compared with those calculated from a 3D finite element model of the building. The measured natural frequencies of the two fundamental sway modes of the building were found to be larger than those calculated. The damping ratios of the building were evaluated by the random decrement technique, which demonstrated amplitude-dependent characteristics. The field measured acceleration responses were compared with wind tunnel test results, which were found to be consistent with the model test data. Finally, the serviceability performance of the super-tall building was assessed based on the field measurement results.

• KIEAE Journal
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• 제17권5호
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• pp.69-76
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• 2017

Purpose: This study aimed at developing an Artificial Neural Network (ANN) model for predicting the amount of cooling energy consumption of the variable refrigerant flow (VRF) cooling system by the different set-points of the control variables, such as supply air temperature of air handling unit (AHU), condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. Applying the predicted results for the different set-points, the control algorithm, which embedded the ANN model, will determine the most energy efficient control strategy. Method: The ANN model was developed and tested its prediction accuracy by using matrix laboratory (MATLAB) and its neural network toolbox. The field data sets were collected for the model training and performance evaluation. For completing the prediction model, three major steps were conducted - i) initial model development including input variable selection, ii) model optimization, and iii) performance evaluation. Result: Eight meaningful input variables were selected in the initial model development such as outdoor temperature, outdoor humidity, indoor temperature, cooling load of the previous cycle, supply air temperature of AHU, condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. The initial model was optimized to have 2 hidden layers with 15 hidden neurons each, 0.3 learning rate, and 0.3 momentum. The optimized model proved its prediction accuracy with stable prediction results.