• 한국산학기술학회논문지
• /
• 제18권11호
• /
• pp.770-777
• /
• 2017

BIM(Building Information Modeling)은 2000년대 들어서면서 기존의 CAD를 대신하여 통합정보모델로서의 관심과 기대를 받아왔다. 건설산업 전체 중에서 건축분야에서 먼저 활용되기 시작한 BIM기술은 토목분야에서는 상대적으로 늦게 도입이 되기 시작하였다. 그러나 정부에서 2020년부터 모든 SOC사업의 20%를 적용계획을 발표하는 등 토목사업에서의 도입은 가속화 될 것으로 예상된다. BIM을 성공적으로 도입하기 위해서는 통합적 설계정보에 대한 체계적인 구조와 이를 구현하는 기술이 뒷받침되어야 한다. 또한 건설사업에서 정보화는 많은 복잡한 요소들이 얽혀 있어 정보체계간의 관계 정립이 무엇보다 중요하다. 본 연구에서는 토목사업에 BIM을 도입하기 위한 정보관계를 규명하여 통합정보를 구성하기 위한 프레임워크를 제시하고 이를 교량사업에 적용하여 그 효용성을 확인한다. 본 연구는앞으로 토목분야에서 WBS(Work Breakdown Structure)를 BIM에 도입하여 공정 및 공사비 관리를 통합적으로 수행하는데 활용될 수 있다. 또한 BIM을 도입하기 위한 정보체계의 표준화에 대한 방향제시를 통하여 앞으로 토목의 각 분야에서 BIM을 도입하는데 도움이 될 것이다.

• 국제학술발표논문집
• /
• The 3th International Conference on Construction Engineering and Project Management
• /
• pp.257-262
• /
• 2009

Image processing has been utilized for assessment of infrastructure surface coating conditions for years. However, there is no robust method to overcome the non-uniform illumination problem to date. Therefore, this paper aims to deal with non-uniform illumination problems for bridge coating assessment and to achieve automated rust intensity recognition. This paper starts with selection of the best color configuration for non-uniformly illuminated rust image segmentation. The adaptive-network-based fuzzy inference system (ANFIS) is adopted as the framework to develop the new model, the box-and-ellipse-based neuro-fuzzy approach (BENFA). Finally, the performance of BENFA is compared to the Fuzzy C-Means (FCM) method, which is often used in image recognition, to show the advantage and robustness of BENFA.

• 국제강구조저널
• /
• 제18권4호
• /
• pp.1177-1190
• /
• 2018

This study presents an analytical framework for estimating the thermo-mechanical behavior of a composite beam exposed to fire. The framework involves: a fire simulation from which the evolution of temperature on the structure surface is obtained; data transfer by an interface model, whereby the surface temperature is assigned to the finite element model of the structure for thermo-mechanical analysis; and nonlinear thermo-mechanical analysis for predicting the structural response under high temperatures. We use a plastic-damage model for calculating the response of concrete slabs, and propose a method to determine the stiffness degradation parameter of the plastic-damage model by a nonlinear regression of concrete cylinder test data. To validate simulation results, structural fire experiments have been performed on a real-scale steel-concrete composite beam using the fire load prescribed by ASTM E119 standard fire curve. The calculated evolution of deflection at the center of the beam shows good agreement with experimental results. The local test results as well as the effective plastic strain distribution and section rotation of the composite beam at elevated temperatures are also investigated.

• Journal of Construction Engineering and Project Management
• /
• 제5권1호
• /
• pp.11-19
• /
• 2015

This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.

• Steel and Composite Structures
• /
• 제24권2호
• /
• pp.265-276
• /
• 2017

Structures are designed in such a way that they behave in a nonlinear manner when subject to strong ground motions. Energy concepts have been widely used to evaluate the structural performance for the last few decades. Energy based design can be expressed as the balance of energy input and the energy dissipation capacity of the structure. New research is needed for multi degree of freedom systems (MDOFs)-real structures- within the framework of the energy based design methodology. In this paper, energy parameters are evaluated for low-, medium- and high-rise steel special concentrically braced frames (SCBFs) in terms of total energy input and hysteretic energy. Nonlinear dynamic time history analyses are carried out to assess the variation of energy terms along the height of the frames. A seismic energy demand spectrum is developed and hysteretic energy distributions within the frames are presented.

• 국제강구조저널
• /
• 제18권5호
• /
• pp.1560-1576
• /
• 2018

With the aim to provide an efficient platform for the elastic-plastic analysis of steel structures, reinforced concrete (RC) structures and steel-concrete composite structures, a program iFiberLUT based on the fiber model was developed within the framework of ABAQUS. This program contains an ABAQUS Fiber Generator which can automatically divide the beam and column cross sections into fiber sections, and a material library which includes several concrete and steel uniaxial material models. The range of applications of iFiberLUT is introduced and its feasibility is verified through previously reported test data of individual structural members as well as planar steel frames, RC frames and composite frames subjected to various loadings. The simulation results indicate that the developed program is able to achieve high calculation accuracy and favorable convergence within a wide range of applications.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2008년도 춘계 학술발표회 초청강연 및 논문집
• /
• pp.494-504
• /
• 2008

Successful design, construction and maintenance of NATM tunnel demands prediction, control, stability estimation and monitoring of surface settlement, gradient and ground displacement with high accuracy. Back analysis using measured data and forward analysis have been and are indispensable tools to achieve this goal. Sakurai provided the hazard warning levels for assessing the stability of tunnels using the relation of critical strain and apparent Young's modulus. This paper performed the estimation of tunnel stability on construction. Firstly, the apparent Young's modulus concept and back analysis method is introduced for the assessment of tunnel safety during excavation a brief framework. Secondly, this paper deals with case study using "Apparent Young's modulus" and "Back analysis" for the purpose of estimating the stability of NATM tunnel in Korea. Finally, a general method that can be estimated the tunnel stability discussed by a flow chart.

• Computers and Concrete
• /
• 제25권2호
• /
• pp.167-179
• /
• 2020

Optimal design of structures against earthquake loads is often limited to reduce initial construction costs, while the cost induced to structures during their useful life may be several times greater than the initial costs. Therefore, it is necessary to consider the indirect costs due to earthquakes in the design process. In this research, an integrated methodology for calculating life cycle cost (LCC) of moment-resisting concrete frames is presented. Increasing seismic safety of structures and reducing human casualties can play an important role in determining the optimal design. Costs incurred for structures are added to the costs of construction, including the costs of reconstruction, financial losses due to the time spent on reconstruction, interruption in building functionality, the value of people's life or disability, and content loss are a major part of the future costs. In this research, fifty years of useful life of structures from the beginning of the construction is considered as the life cycle. These costs should be considered as factors of calculating indirect costs of a structure. The results of this work represent the life cycle cost of a 4 story, 7 story, and 10 story moment-resisting concrete frame by details. This methodology is developed based on the economic conditions of Iran in 2016 and for the case of Tehran city.

• 대한토목학회논문집
• /
• 제43권6호
• /
• pp.801-809
• /
• 2023

대규모로 진행되는 도로건설사업에서 비용 초과와 공기 지연이 지속적으로 발생하고 있지만 이를 사전에 관리하고 대비할 수 있는 성과평가 체계 연구는 미흡한 실정이다. 또한 긴 공기를 가진 도로건설사업은 시공과정에서 많은 요인들에 영향을 받기 때문에 도로만의 특성을 고려한 성과 평가를 실시하고, 추후 유사한 사업에 대비할 필요가 있다. 따라서 본 연구는 도로건설사업의 시공단계 성과평가 프레임워크를 개발하여 도로건설사업의 성과관리 방안을 제시하고자 한다. 본 연구는 각종 유관기관에서 도로건설사업 시공단계의 정보를 수집하고 속성정보에 따라 데이터베이스를 구축하였다. 또한 사업의 착공·준공시점 간 시간차에 대해 비용 표준화를 실시하였고, 성과평가를 위한 지표를 도출하여 분석을 실시하였다. 본 연구는 도로건설사업 시공과정의 절대적, 상대적 비용·일정 성과를 정량적으로 분석함으로써 성과평가 연구의 고도화 가능성과 신규 도로건설사업 계획 시 활용방안을 보여준다.

• 한국건설관리학회논문집
• /
• 제8권4호
• /
• pp.203-213
• /
• 2007

In the past, several construction projects have exceeded their schedule resulting in financial losses to the owners; at present there are very few methods available to accurately forecast the completion date of a project. These nay be because of unforeseen outcomes that cannot be accounted for earlier and because of deficiency of proper tools to forecast completion date of said project. To overcome these difficulties, project managers may need a tool to predict the completion date at the early stage of project development. Bayesian Inference introduced in this paper is one such tool that can be employed to forecast project progress at all construction stages. Using this inference, project managers can combine an initially planned project progress (growth curve) with reported information from ongoing projects during the development, and in addition, dynamically revise this initial plan and quantify the uncertainty of completion date. This study introduces a theoretical model and proposes a mathematically information-based framework to forecast a project completion date that corresponds with the actual progress data and to monitor the modified uncertainties using Bayesian Inference.