• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.162-163
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• 2016

This paper presents a mathematical model for optimizing earthwork allocation plan that minimizes earthwork cost. The model takes into account operational constraints in the real-world earthwork such as material-type (i.e., quality level of material) and quantities excavated from cut-sections, required quality of material and quantities for each embankment layer, top-down cutting and bottom-up filling constraints, and allocation orders. These constraints are successfully handled by assuming the rock-earth material as the three dimensional (3D) blocks. The study is of value to project scheduler because the model identifies the optimal earth allocation plan (i.e., haul direction (cut and fill pairs), quantities of soil, type of material, and order of allocations) expeditiously and is developed as an automated system for usability. It is also relevant to estimator in that it computes more realistic earthworks costs estimation. The economic impact and validity of the mathematical model was confirmed by performing test cases.

• Knowledge Management Research
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• v.22 no.3
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• pp.91-106
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• 2021

With the recent rapid development of deep learning technology, the demand for analyzing huge text documents in the national R&D field from various perspectives is rapidly increasing. In particular, interest in the application of a BERT(Bidirectional Encoder Representations from Transformers) language model that has pre-trained a large corpus is growing. However, the terminology used frequently in highly specialized fields such as national R&D are often not sufficiently learned in basic BERT. This is pointed out as a limitation of understanding documents in specialized fields through BERT. Therefore, this study proposes a method to build an R&D KoBERT language model that transfers national R&D field knowledge to basic BERT using further pre-training. In addition, in order to evaluate the performance of the proposed model, we performed classification analysis on about 116,000 R&D reports in the health care and information and communication fields. Experimental results showed that our proposed model showed higher performance in terms of accuracy compared to the pure KoBERT model.

• Wind and Structures
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• v.26 no.6
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• pp.397-413
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• 2018

Excitation mechanism of interference effect between two tall buildings is investigated with wind tunnel experiments. Synchronized building surface pressure and flow field measurements by particle image velocimetry (PIV) are conducted to explore the relationship between the disturbed wind flow field and the consequent wind load modification for twin buildings in tandem. This reveals evident excitation mechanisms for the fluctuating across-wind loads on the buildings. For small distance (X/D < 3) between two buildings, the disturbed flow pattern of impaired vortex shedding is observed and the fluctuating across-wind load on the downstream building decreases. For larger distance ($X/D{\geq}3$), strong correlation between the across-wind load of the downstream building and the oscillation of the wake of the upstream building is found. By further analysis with conditional sampling and phase-averaged techniques, the coherent flow structures in the building gap are clearly observed and the wake oscillation of the upstream building is confirmed to be the reason of the magnified across-wind force on the downstream building. For efficient PIV measurement, the experiments use a square-section high-rise building model with geometry scale smaller than the usual value. Interference factors for all three components of wind loads on the building models being surrounded by another identical building with various configurations are measured and compared with those from previous studies made at large geometry scale. The results support that for interference effect between buildings with sharp corners, the length scale effect plays a minor role provided that the minimum Reynolds number requirement is met.

• Journal of KIBIM
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• v.1 no.2
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• pp.12-18
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• 2011

The BIM techniques which manages information over the life cycle of construction project based on the 3-dimensional model are developing in the direction of integrated construction management including planning, design, analysis, estimation, 3D simulation and so on. The estimation model based on the BIM has different detail level and model information. In this study, the LOD of estimation model is catched for the bridge structures. The library classes are defined with construction information classification system, and the quantities of resources are calculated by class parameter using Microstation API. Finally, the automated estimation system using BIM based library is verified by the integrated model for adjustments of level of detail.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.4 no.2
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• pp.82-95
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• 1992

It has been known that the application of an airflow window system reduces the energy consumption compared with conventional double pane window in a building. But how to analyze thermal load in a building with an airflow window system has not been well known. so two kinds of method (Mode 1 and Mode 2) to analyze time dependent thermal load of the building with an airflow window system are presented in this study. The results of load analysis about the model building(total area : $4521m^2$, 3 floors) by Mode 2 show that the maximum cooling and heating load in a building with an airflow window system are decreased about 12-17% and about 19.5% than with double pane glass window, and yearly energy consumption with an airflow window system is saved about about 20% than with double pane glass window.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.385-392
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• 2010

A LiDAR technique has the merits that survey engineers can get a large number of measurements with high precision quickly. Aerial photos and satellite sensor images are used for generating 3D spatial images which are matched with the map coordinates and elevation data from digital topographic files. Also, those images are used for matching with 3D spatial image contents through perspective view condition composed along to the designated roads until arrival the corresponding location. Recently, 3D aviation image could be generated by various digital data. The advanced geographical methods for guidance of the destination road are experimented under the GIS environments. More information and access designated are guided by the multimedia contents on internet or from the public tour information desk using the simulation images. The height data based on LiDAR is transformed into DEM, and the real time unification of the vector via digital image mapping and raster via extract evaluation are transformed to trace the generated model of 3-dimensional downtown building along to the long distance for 3D tract model generation.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.273-284
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• 2023

This study is centered on the combined use of LiDAR(Light Detection and Ranging) and AR(Augmented Reality) technologies during vertical and horizontal frame measurements in construction projects. The intention is to enhance the quality control procedure, elevate accuracy, and curtail manual labor along with time expenditure. Present methods for accuracy inspection in frame construction often grapple with reliability concerns due to subjective interpretation and the scope for human error. This research recommends the application of LiDAR and AR technologies to counter these issues and augment the efficiency of the inspection process, along with facilitating the dissemination of results. The suggested technique involves the collection of 3D point cloud data of the frame utilizing LiDAR and leveraging this data for checks on construction accuracy. Furthermore, the inspection outcomes are fed into a BIM (Building Information Modeling) model, and the results are visualized via AR. Upon juxtaposing this methodology with the current approach, it is evident that it offers benefits in terms of objective inspection, speed, precise result sharing, and potential enhancements to the overall quality and productivity of construction projects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.419-424
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• 2009

This paper show about the possibility of practical application after building VR(virtual reality) data based on Airborne LiDAR data which determines complicated topography quickly for the 3D-GIS construction. In this paper, we collected Airborne LiDAR data, digital map, serial photo and a basic design. The results are expected some effective determination by 3D-GIS construction based on LiDAR data. Hereafter, because the research will be able to be given quickly topography information on ubiquitous environment the field of construction and GIS will be able to be helped.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.565-572
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• 2014

A systematically structured 3D information model can be effectively utilized in many application fields. This study presents the methodology of generation and application of the city information model, which is suited for the management of the flood damage information. To ensure the interoperability and re-usability of the information, this study develops application methodology to utilize the information attributes included in the CityGML as an open standard data schema and extension methodology for additional information attributes. Also, an effective combining method for topography and building model was proposed. Using the data extracted from the combined information model based on a real flood damage case, it was shown that the numbers of casualties and isolation during a flood can be predicted and as a result, the applicability of the data model on flood damage estimation is naturally verified.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.