• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.370-374
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• 2022

Construction is a labor-intensive industry that heavily relies on skilled construction workers. However, the aging of the workforce is rapidly growing, and the shortage of skilled workers is intensifying. The application of construction robotics technology can solve the problem of workforce shortage and guarantee construction productivity, safety, and quality improvement. This study presents a framework of the functional analysis for construction processes and work tasks that classifies and analyzes processes and work tasks for construction robotics design. The framework presents the functional analysis process, which analyzes workers' attributes and identifies functions of construction robotics.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.203-204
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• 2023

The construction industry is a hazardous environment in which many field workers work. Therefore, there is a limit to the safety manager's grasp of all situations. In order to solve these problems, the application of automatic control technology in connection with AI and CCTV is being introduced, and the development of intelligent CCTV to reduce the safety accident rate is actively progressing. This study seeks to present future directions by identifying the current status of intelligent CCTV developed to reduce the safety accident rate at construction sites and analyzing its limitations. Through this, the range of accident prevention types of the safety control system at the construction site will be confirmed and the need for future intelligent CCTV function development will be suggested.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.405-406
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• 2023

In the era of AI, intelligent construction safety technologies are being introduced to the construction safety environment, but the application of AI has limitations due to the lack of accident images to learn in complex construction sites. In order to overcome this, we will introduce an intelligent risk detection system that dramatically improves risk detection accuracy by combining AI with digital twin technology, and introduce various cases.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.669-670
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• 2015

Efficient management of the construction heavy equipment is required to reduce the rate of carbon emissions and on-site accidents. The intelligent excavation system (IES) will improve the construction quality and productivity through information technologies and efficient equipment operation, especially in large earthwork projects. Three-dimensional digitized ground data should be required for identifying the path of heavy equipment and work-site environment. Rapid development of terrain laser scanners (TLS) is more readily to acquire the digital data. This study suggests the '3D ground terrain processing platform (3DGTPP)' including data manipulating module and analyzing module of the scanned data for intelligent earthmoving equipment operation. The processing platform consists of six modules, including scanning, registering, manipulating, analyzing, transmitting, and storing. 3D ground terrain processing platform presented in this study will provide fundamental information for intelligent excavation system (IES), which will increase the efficiency of earthworks and safety of workers in significant.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2008년도 정기학술발표대회 논문집
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• pp.305-310
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• 2008

건설프로젝트가 점차 대형화, 고층화 되어감에 따라 프로젝트의 관리방식에 많은 변화가 요구되고 있다. 특히, RFID/USN과 같은 유비쿼터스 기술적용이 활발히 진행되고 있는 건설물류관리 분야를 중심으로 이를 효율화하기 위한 다양한 관점의 방안이 제시되고 있다. 이에 최근 건설현장을 지능화하기 위한 목적으로 개발되고 있는 지능형 장비의 도입은 건설현장에서의 건설물류관리에 새로운 프로세스 모델개발이 요구되고 있다. 따라서 본 연구에서는 바코드 및 RFID/USN 기반의 개별 자재 형태로 제안되고 있는 기존 건설물류프로세스의 한계를 극복하고, 지능형 장비와 같은 건설물류관리의 변화요인들을 반영하여 건설공사에 사용되는 수많은 자재들이 이러한 변화된 프로세스에 쉽게 적용될 수 있는 가이드를 제공하기 위하여 지능형 건설물류관리 프로세스 레퍼런스 모델을 개발하였다.

• Geomechanics and Engineering
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• 제37권1호
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• pp.9-19
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• 2024

This study presents an energy analysis for large-strain cavity expansion problem based on the general strength criterion and energy theory. This study focuses on the energy dissipation problem during the cavity expansion process, dividing the soil mass around the cavity into an elastic region and a plastic region. Assuming compliance with the small deformation theory in the elastic region and the large deformation theory in the plastic region, combined with the general strength criterion of soil mass and energy theory, the energy dissipation solution for cavity expansion problem is derived. Firstly, from an energy perspective, the process of cavity expansion in soil mass is described as an energy conversion process. The energy dissipation mechanism is introduced into the traditional analysis of cavity expansion, and a general analytical solution for cavity expansion related to energy is derived. Subsequently, based on this general analytical solution of cavity expansion, the influence of different strength criterion, large-strain, expansion radius, cavity shape and characteristics of soil mass on the stress distribution, displacement field and energy evolution around the cavity is studied. Finally, the effectiveness and reliability of theoretical solution is verified by comparing the results of typical pressure-expansion curves with existing literature algorithms. The results indicate that different strength criterion have a relatively small impact on the displacement and strain field around the cavity, but a significant impact on the stress distribution and energy evolution around the cavity.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.242-249
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• 2009

High-rise construction sites, especially those situated in spatially constrained urban areas, have difficulties in timely delivery of materials. Modern techniques such as Just-in-time delivery, and use of information technology such as Project Management Information System (PMIS), are targeted to improve the efficiency of the logistics. Such IT-driven management techniques can be further benefited from state-of-the-art devices such as Radio Frequency Identification (RFID) tags and Ubiquitous Sensor Networks (USN), which has resulted in notable achievements in automated logistics management at the construction sites. Based on those achievements, this research develops USN hardware toolkits for construction lifts, which aims to be automated the vertical material delivery by sensing the material information and routing it automatically to the right place. The gathered information from the sensors can also be used for monitoring the overall status. The developed system will be tested in the actual high-rise construction sites to assess the system's feasibility. The proposed system is being implemented using Zigbee communication modules and RFID sensor networks which will communicate with the intelligent palette system (previously developed by the authors). To support the system, a lift-mountable intelligent toolkit is under development. Its feasibility test will be conducted by applying the implemented system to a test bed and then analyzing efficiency of the system and the toolkit. The collected test data will be provided as a basis of autonomous vertical transport equipment development. From this research, efficient management of the material lift is expected with increased accuracy, as well as better management of overall construction schedule benefited from the system. Further research will be expected to develop a smart construction lift, which will eliminate the need for human supervision, thus enabling a real 'autonomous' operation of the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3970-3990
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• 2021

In view of the problems of insufficient data collection and processing capability of multi-source heterogeneous equipment, and low visibility of equipment status at the ship block construction site. A data collection method for ship block construction equipment based on wireless sensor network (WSN) technology and a data processing method based on edge computing were proposed. Based on the Browser/Server (B/S) architecture and the OneNET platform, an online monitoring system for ship block construction equipment was designed and developed, which realized the visual online monitoring and management of the ship block construction equipment status. Not only that, the feasibility and reliability of the monitoring system were verified by using the intelligent tire frame system as the application object. The research of this project can lay the foundation for the ship block construction equipment management and the ship block intelligent construction, and ultimately improve the quality and efficiency of ship block construction.

• Geomechanics and Engineering
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• 제34권3호
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• pp.303-316
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• 2023

With the development and utilization of urban underground space, the artificial ground freezing technology has been widely used in the construction of underground engineering in soft soil areas. The mechanical properties of soft clay changed greatly after freezing and thawing, which affected the seismic performance of underground structures. In this paper, a series of triaxial tests were carried out to study the dynamic response of the freezing-thawing clay under the seismic load considering different dynamic stress amplitudes and different confining pressures. The reduction factor of dynamic shear stress was determined to correct the amplitude of the seismic load. The deformation development mode, the stress-strain relationship and the energy dissipation behavior of the soft clay under the seismic load were analyzed. An empirical model for predicting accumulative plastic strain was proposed and validated considering the loading times, the confining pressures and the dynamic stress amplitudes. The relevant research results can provide a theoretical reference to the seismic design of underground structures in soft clay areas.

• 드라이브 ㆍ 컨트롤
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• 제20권4호
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• pp.133-139
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• 2023

A weighing system calculates the bucket's excavation amount of an excavator. Usually, the excavation amount is computed by the excavator's motion equations with sensing data. But these motion equations have computing errors that are induced by assumptions to the linear systems and identification of the equation's parameters. To reduce computing errors, some commercial weighing system incorporates particular motion into the excavation process. This study introduces a linear regression model on an artificial neural network that has fewer predicted errors and doesn't need a particular pose during an excavation. Time serial data were gathered from a 30tons excavator's loading test. Then these data were preprocessed to be adjusted by MPL (Multi Layer Perceptron) or CNN (Convolutional Neural Network) based linear regression models. Each model was trained by changing hyperparameter such as layer or node numbers, drop-out rate, and kernel size. Finally ID-CNN-based linear regression model was selected.