• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1050-1056
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• 2008

Many cut slopes are situated on national highways. In this study, we chose rock slopes of moderated weathering grade to analyze general strength parameters of cut slopes. We analyzed the strength parameters of selected rock slopes by the experience method. Also, we arranged the strength parameters by area and rock types.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.179-184
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• 2005

Shear strength parameters obtained from filed survey are important factors in the analysis of slope stability. In this study, sensitivity analysis was performed to evaluate the effect of input parameters on the analysis of slope stability. The input parameters selected for sensitivity analysis were slope angle, cohesion, and friction angle. Monte-Carlo Simulation method was used for calculating input parameters and the factor of safety was computed by means of limit equilibrium method. A rock slope, which has failed in the field, was used for the sensitivity analysis in the analysis of slope stability. The result of analysis shows that the factor of safety of the rock slope was a little low. From partial correlation coefficient(PPC) of input parameters determined from the sensitivity analysis, slope stability was dependant on cohesion and slope angle. The effect of friction angle was lower than that of cohesion and slope angle on slope stability.

• Journal of Construction Engineering and Project Management
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• v.4 no.4
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• pp.9-16
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• 2014

The purpose of this paper is to develop a model for forecasting early design construction cost of building projects using Artificial Neural Network (ANN). Eighty questionnaires distributed among construction organizations were utilized to identify significant parameters for the building project costs. 169 case studies of building projects were collected from the construction industry in Gaza Strip. The case studies were used to develop ANN model. Eleven significant parameters were considered as independent input variables affected on "project cost". The neural network model reasonably succeeded in estimating building projects cost without the need for more detailed drawings. The average percentage error of tested dataset for the adapted model was largely acceptable (less than 6%). Sensitivity analysis showed that the area of typical floor and number of floors are the most influential parameters in building cost.

• Computers and Concrete
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• v.33 no.5
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• pp.535-544
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• 2024

In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.1-10
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• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• Proceedings of the Korean Geotechical Society Conference
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• 1994.09a
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• pp.209-216
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• 1994

Rock mass classifications have played an indispensable role in underground construction for several decades. An important issue in rock mass classifications is the selection of the parameters of greatest significance. There appears to be no single parameter that can fully describe a jointed rock mass for underground construction design. In this paper. We find some problems shen applied rock mass classification for underground construction in domestic, analyze the most significant parameters and parameters correlation influencing the behavior of a rock mass, and suggest the Simplied Rock Mass Rating system based on RMR method for effective underground supports.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.596-601
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• 2013

In the current pavement construction practice, the state agencies traditionally determine the quality of the as-constructed pavement mix based on individual mixture material parameters (e.g., air voids, cement or asphalt content, aggregate gradation, etc.) and consider these parameters as key variables to influence payment schedule to the contractors and the present and future quality of the as-constructed mixture. A set of empirically pre-determined pay adjustment schedule for each parameter that was differently developed and being used by the individual agencies is then applied to a given project, in order to judge whether each parameter conforms to the designated specifications and consequently the contractor may either be rewarded or penalized in accordance with the payment schedule. With an improved quality assurance system, the Performance Related Specification, the individual parameters are not utilized as a direct judgment factor; rather, they become independent variables within a performance prediction function which is directly used to predict the performance. The quantified performance based on the prediction model is then applied to evaluate the pavement quality. This paper presents the brief history of the quality assurance in asphalt pavement construction including the Performance Related Specifications, statistical performance models in terms of fatigue and rutting distresses, as an example of the performance prediction models, and envisions the possibilities as to how this Performance Related Specification could be utilized in other infrastructures construction quality assurance.

• Journal of the Korean Geotechnical Society
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• v.21 no.5
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• pp.75-82
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• 2005

Shear strength parameters obtained from field tests are important factors in the analysis of slope stability. In this paper, sensitivity analysis was performed to evaluate the effect of input parameters on the analysis of slope stability. The input parameters selected for sensitivity analysis were slope angle, cohesion, and friction angle. Monte-Carlo Simulation method was to estimate input parameters for sensitivity analysis in slope stability, and the limit equilibrium method was used to calculate the factor of safety of slope stability. A rock slope, failed in the field, was used for the sensitivity analysis of input parameters in the analysis of slope stability. The result of analysis shows that the factor of safety of the rock slope was a little low. From partial correlation coefficient (PCC) of input parameters from the sensitivity analysis, slope stability was dependant mainly on cohesion and slope angle. The effect of friction angle was smaller than those of cohesion and slope angle on slope stability.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.184-191
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• 2003

In this paper, a mathematical framework based on a homogenisation technique to simulate 'umbrella arch reinforcement system' (UARS) and its implementation into a 3D Finite Element program that can consider stage construction situations are presented. The constitutive model developed allows considering the main design parameters of the problem and only requires geometrical and mechanical properties of the constituents. Additionally, the use of a homogenisation approach implies that the generation of the Finite Element mesh can be easily produced and that re-meshing is not required as basic geometrical parameters such as the orientation of the pipes are changed. The model developed is used to simulate tunnelling with the UARS. From the analyses, the effects of the main design parameters on the elastic and the elastoplastic analyses are considered.

• Steel and Composite Structures
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• v.12 no.2
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• pp.167-181
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• 2012

Ultra high performance cementitious composite material is applied to the design of multifunctional permanent form for bridge pier in this paper. The basic properties and calculating constitutive model of ultra high performance cementitious composite are introduced briefly. According to momental theory of thin-walled shell, the analytical solutions of structural behavior parameters including circumferential stress, longitudinal stress and shear stress are derived for UHPCC thin-walled circular tube. Based on relevant code of construction loads (MHURD of PPC 2008), the calculating parameter expression of construction loads for UHPCC thin-walled circular tube is presented. With geometrical dimensions of typical pier, the structural behavior parameters of UHPCC tube under construction loads are calculated. The effects of geometrical parameters of UHPCC tube on structural behavior are analyzed and the design advices for UHPCC tube are proposed. This paper shall provide a scientific reference for UHPCC permanent form design and UHPCC hybrid structure application.