• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.42-51
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• 2017

Due to the high degree of mechanization and the good environmental benefits, the prefabricated buildings are being promoted in China. The construction site layout of the prefabricated buildings has important influence on its safety benefit. However, few scholars have studied the safety problem on it. Firstly, in order to give a follow-up study foreshadowing the characteristics of prefabricated buildings are analyzed, the research assumptions are given and three types of safety buffers are established. And then a mult-objective model for the prefabricated buildings site layout is presented: taking into account the limits of noise, the coverage of the tower crane and the possibility of exceeding boundaries and overlapping, the constraints are and designed established respectively; Based on the improved System Layout Planning (SLP) method, the efficiency\cost\safety interaction matrices among the facilities are also founded for objective function. For the sake of convenience, a hypothetical facility layout case of the prefabricated building is used, the optimal solution of that is obtained in MATLAB with particle swarm algorithm (PSO), which proves the effectiveness of the model presented in this paper.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.287-288
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• 2023

The inspection work at construction sites is one of the important supervisory tasks, which involves verifying that the building is being constructed by the numerical values specified in the design drawings. The conventional measuring method for inspection involves using tools or equipment such as rulers directly by the personnel at the site, and it is usually confirmed by vision. Therefore, this study proposes an model to measure numerical values on images of the construction site. Through the case study to measure the installation interval of jack supports, the proposed algorithm was verified the effiect and validity. The results of this study suggest that it can support inspection work even in the office, which may have been overlooked by on-site inspectors, and contribute to the digitization of inspection work at construction sites.

• 한국건축시공학회지
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• 제15권3호
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• pp.329-337
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• 2015

건설도면은 프로젝트에서 발생하는 다양한 정보를 담은 지식의 집성체이다. 도면에 포함된 지식의 재활용은 건설 프로젝트의 성공에 있어 중요한 부분이다. 마감상세도는 실별, 부위별 마감 및 공법을 선택하고 설계하면서 생성되는 도면으로, 기존 사례 도면의 재활용이 가장 많은 도면중 하나이다. 그러나 여러 도면이 한꺼번에 작성되는 마감상세도의 특징 때문에 기존 도면관리시스템에서는 활용이 어렵다. 본 연구에서는 개별적인 마감상세도의 활용을 위하여 도면 블록화 알고리즘을 제안하였고, 이를 바탕으로 마감상세도 블록화 모듈을 개발하였다. 개발된 모듈을 기반으로 마감상세도 관리 시스템을 구축한다면 개별적인 마감상세도에 대한 관리가 가능할 것이다. 개별적인 마감상세도의 관리는 기존 마감상세도 검색에 소요되는 시간을 단축시켜 마감상세도 설계 작업의 생산성을 높일 수 있을 것이다. 또한, 마감상세도 내 지식의 재활용성이 증대됨에 따라 설계된 도면의 품질 향상에도 기여할 수 있을 것이다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.219-220
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• 2021

It is considered that the construction industry is one of the pivotal players in the national economy in terms of Gross Domestic Production (GDP) and employment. Behind the positive role of this industrial sector to the national economy, the construction industry generates approximately 50 % of the total waste generation from all the industrial sectors. There are several measures to mitigate the adverse impacts of the construction waste such as reduce, reuse and recycle. Recycling would be one of the effective strategies for waste minimisation, which would be able to reduce the demand upon new resources as well as enhance reusing the construction materials on sites. The automated construction waste classification system would make it possible not only to reduce the amount of labour input but also mitigate the possibility of errors during the manual classification process. In this study, we proposed an automated waste segmentation and classification system for recycling the construction and demolition waste in the real construction site context. Since the practical application to the real-world construction sites was one of the significant factors to develop the system, a YOLACT (You Only Look At CoefficienTs) algorithm was chosen to conduct the study. In this study, it is expected that the proposed system would make it possible to enhance the productivity as well as the cost efficiency by reducing the manpower for the construction and demolition waste management at the construction site.

• Smart Structures and Systems
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• 제13권2호
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• pp.305-318
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• 2014

This paper numerically investigates the feasibility of an active mass damper (AMD) system using the time delay control (TDC) algorithm, which is one of the robust and adaptive control algorithms, for effectively suppressing the excessive vibration of a building structure under wind loading. Because of its several attractive features such as the simplicity and the excellent robustness to unknown system dynamics and disturbance, the TDC algorithm has the potential to be an effective control system for mitigating the vibration of civil engineering structures such as buildings and bridges. However, it has not been used for structural response reduction yet. In this study, therefore, the active control method combining an AMD system with the TDC algorithm is first proposed in order to reduce the wind-induced vibration of a building structure and its effectiveness is numerically examined. To this end, its stability analysis is first performed; and then, a series of numerical simulations are conducted. It is demonstrated that the proposed active structural control system can effectively reduce the acceleration response of the building structure.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2012년도 추계 학술논문 발표대회
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• pp.253-254
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• 2012

The purpose of this study is to suggest and verify high-strength concrete mix design model applying neural network theory, in order to minimize effort and time wasted by using trial and error method utill now. There are 7 input and 2 output to predict mix design. 40 data of mix design were learned with back-propagation algorithm. Then they are repeatedly learned back-propagation in neural network theory. Also, to verify predicted model, we analyzed and compared value predicted from 60MPa mix design with value measured by actual compressive strength test.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2014년도 춘계 학술논문 발표대회
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• pp.4-5
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• 2014

Planning earthmoving haul-route must be preceded for appropriate equipment fleet assignment. However, traditional haul-route planning methods have limitations relative to practical usage because multiple variables (e.g., grade/rolling resistance, length, equipment's weight etc.) should be considered at a time. Genetic algorithm(GA) was introduced to improve these traditional methods. However, GA based haul-route planning method still remains in inefficiency relative to computation performance. This study presents a new haul-route searching method that computes an optimal haul-route using GA. The system prototype is developed by using MATLAB(ver. 2008b). The system identifies an optimal haul-route by considering equipment type, soil type, and soil condition.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2011년도 추계 학술논문 발표대회
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• pp.101-103
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• 2011

Various desired performances of concrete cannot be always obtained by current conventional mix proportion methods for recycled aggregate concrete (RAC). This paper suggests a new design method of mix proportion for RAC to reduce the number of trial mixes using genetic algorithm (GA) which has been an optimization technique to solve the multi-object problem. In mix design method by GA, several fitness functions for the required properties of concrete, i.e., slump, strength, price, and carbonation speed coefficient were considered based on conventional data or fitness function. As a result, various optimum mix proportions for RAC that meet required performances were obtained and the risk evaluation was also conducted for selected mixtures.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 춘계 학술논문 발표대회
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• pp.130-131
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• 2018

The compressive strength of concrete is determined by various influencing factors. However, the conventional method for estimating the compressive strength of concrete has been suggested by considering only 1 to 3 specific influential factors as variables. In this study, nine influential factors (W/B ratio, Water, Cement, Aggregate(Coarse, Fine), Fly ash, Blast furnace slag, Curing temperature, and humidity) of papers opened for 10 years were collected at 4 conferences in order to know the various correlations among data and the tendency of data. The selected mixture and compressive strength data were learned using the Deep Learning Algorithm to derive an estimated function model. The purpose of this study is to investigate the effect of the number of hidden layers on the prediction performance in the process of estimating the compressive strength for an arbitrary combination.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2019년도 춘계 학술논문 발표대회
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• pp.30-31
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• 2019

Carbonation of the root concrete reduces the durability of the reinforced concrete, and it is important to check the carbonation resistance of the concrete to ensure the durability of the reinforced concrete structure. In this study, a basic study on the prediction of carbonation progress was conducted by considering the mixing conditions of concrete using deep learning algorithm during the theory of artificial neural network theory. The data used in the experiment used values that converted the carbonation velocity coefficient obtained from the mixing conditions of concrete and the accelerated carbonation experiment into the actual environment. The analysis shows that the error rate of the deep learning model according to the Hidden Layer is the best for the model using five layers, and based on the five Hidden layers, we want to verify the predicted performance of the carbonation speed coefficient of the carbonation test specimen in which the exposure experiment took place in the real environment.