• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.366-375
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• 2007

Although the STEP modularization is the major development methodology for STEP Application Protocol, there have been few studies on the STEP Modularization in Korea. The necessity of STEP Modularization research has been raised continuously. In addition, the importance became larger and larger because most of newly developing APs, including AP241, are developed using modularization approach. The object of this study is to investigate the basic structure and contents of AEC facilities related Application Modules using STEP Modularization. This study examines 1) the technical analysis regarding STEP Modularization, 2) application modules development regarding civil engineering elements of AP241; Aec_faciliteis_classification", "Aec_civil_item", and "Aec_civil_componet", 3) the developed application modules verification, and 4) the implementation methodology suggestion for application modules and modular AP.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.433-436
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• 2013

This study suggests IFC-based bridge information modeling methods and its application model in BIM environment. Data model extension for bridge structure was achieved using user-defined property sets based on IFC framework. First, identification information was added. Bridge members are identified through physical and spatial semantic information added as property sets. Instances for semantic information were assigned according to standardized rules. Second, CO2 related factors were added for application information model. It can play a role to calculate and manage the quantity of CO2 emission. Third, properties for temporary structure to estimate and manage the construction cost were added. Finally, we investigated proposed methods through implementing the application information model of bridges.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.61-62
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• 2005

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1201-1208
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• 2009

A making a decision of construction cost has important meaning and function for both contractor and owner in construction projects. Especially, it should be premised that estimating the construction cost in efficient and rational way in public construction, which is invested by government funds, for efficient execution of the budget and investment as a side of government. The systematic methodology for estimating construction cost approximately of a river facility construction project has not yet been established because of its unique characteristics including its relatively small project size in terms of cost. On this study, It collect and analyze a river facility construction historical cost data for develop an approximate cost estimating model for river applied by typical embankment section method and rate application of the others activity type. And it verify suitability of model through a that result of application of real river facility construction statement at developed model. By this study, it is expected to reasonable and systematic estimating construction cost through application of developed model.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2008.10a
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• pp.43-51
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• 2008

Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.

• Structural Engineering and Mechanics
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• v.11 no.4
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• pp.443-460
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• 2001

This paper presents an effective application of a variable-node axisymmetric solid element designated as AQV (Axisymmetric Quadrilateral Variable-node element). The variable-node element with physical midside nodes helps to overcome some problems in connecting the different layer patterns on a quadrilateral mesh in the adaptive h-refinement. This element alleviates the necessity of imposing displacement constraints on irregular (hanging) nodes in order to enforce the inter-element compatibility. Therefore, the elements with variable mid-side nodes can be used effectively in the local mesh refinement for the axisymmetric structures which have stress concentrations. A modified Gaussian quadrature should be adopted to evaluate the stiffness matrices of the variable-node elements mainly because of the slope discontinuity of assumed displacement within the elements. Some numerical examples show the usefulness of variable-node axisymmetric elements in the practical application.

• Structural Engineering and Mechanics
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• v.50 no.4
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• pp.541-561
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• 2014

This paper approaches the issue of seismic vulnerability assessment strategies for facade walls of traditional masonry buildings through the development of a methodology and its subsequent application to over 600 building facades from the old building stock of the historic city centre of Coimbra. Using the post-earthquake damage assessment of masonry buildings in L'Aquila, Italy, an analytical function was developed and calibrated to estimate the mean damage grade for masonry facade walls. Having defined the vulnerability function for facade walls, damage scenarios were calculated and subsequently used in the development of an emergency planning tool and in the elaboration of an access route proposal for the case study of the historic city centre of Coimbra. Finally, the methodology was pre-validated through the comparison of a set of results obtained from its application and also resourcing to a widely accepted mechanical method on the description of the out-of-plane behaviour of facade walls.

• Computers and Concrete
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• v.11 no.3
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• pp.237-252
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• 2013

This paper presents the application of artificial neural network (ANN) to predict deep beam deflection using experimental data from eight high-strength-self-compacting-concrete (HSSCC) deep beams. The optimized network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of ten and four neurons in first and second hidden layers using TRAINLM training function predicted highly accurate and more precise load-deflection diagrams compared to classical linear regression (LR). The ANN's MSE values are 40 times smaller than the LR's. The test data R value from ANN is 0.9931; thus indicating a high confidence level.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.200-201
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• 2005

• Proceedings of the Korean Geotechical Society Conference
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• 1995.10a
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• pp.15.3-24
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• 1995