• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.3
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• pp.585-592
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• 2017

Most sewer lines buried in the city are likely to be collapsed due to serious aging. Also, due to the high concentration of development and high population density and traffic, the collapse of the sewer will cause enormous social and economic damage. Therefore, proactive maintenance is required to prevent accidents caused by deteriorated sewer pipe. In order to utilize limited budget effectively, risk-based prioritization methods should be proposed that simultaneously consider the consequence of failure and the probability of failure. In this study, the method of risk-based prioritization of sewer was examined by reviewing various cases of overseas studies and applied to the urban sub-catchment. First, the impact factors that can be secured through the sewer GIS DB in Seoul were derived, and the weight, sub-criteria, and impact score of each impact factor were determined and the consequence of failure was calculated by weight sum method. In addition, the probability of failure was calculated by dividing the service life by the estimated useful life, and the consequence of failure and the probability of failure were classified into five grades by the Jenks natural breaks classification method. The prioritization method was applied to sub-catchment in the Seoul to derive a risk matrix and a risk grade. As a result, 26% of all subjects were selected as the inspection priority subjects with 4-5 risk grade. Therefore, using the risk-based CCTV prioritization methodology, it will be possible to systematically determine the objects that need investigation first.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.12 no.1
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• pp.17-22
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• 2016

Alloy 600 widely used in nuclear power plant is susceptible to primary water stress corrosion cracking (PWSCC). It is important to prioritize the inspection of Alloy 600 components using PWSCC susceptibility index. Plant-specific model for the susceptibility index was reviewed. The normalized PWSCC susceptibility index to a reference value is suggested and applied. The result was found to be reasonable.

• Journal of Applied Reliability
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• v.10 no.2
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• pp.123-135
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• 2010

Failure mode and effects analysis (FMEA) is a widely used technique to assess or to improve reliability of products or processes at early stage of development. Traditionally, the prioritization of failures for corrective actions is performed by evaluating risk priority numbers (RPN). In practice, due to insufficient evaluation criteria specific to related products and processes, RPN is not always evaluated properly. This paper reestablishes an effective methodology for prioritization of failure modes in FMEA procedure. Revised evaluation criteria of RPN are devised and a refined FMEA sheet is introduced. To verify the proposed methodology, it is applied to inspection processes of PCB products.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.598-603
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• 2003

During the last ten years, the need has been increased for reducing maintenance cost for aged equipments and ensuring safety, efficiency and profitability of petrochemical and refinery plants. RBI (Risk Based Inspection) methodology is one of the most promising technologies satisfying the need in the field of integrity management. In this study, a user-friendly software, realRBI for RBI based on the API 581 code was developed and a quantitative analysis was performed for over 500 equipments in a domestic plant whose operating time reaches about 13 years. Current risks for each equipment parts were evaluated and risk based prioritization were determined as a conclusion.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2B
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• pp.187-195
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• 2006

A bridge scour management system is developed to evaluate the vulnerability of bridge piers to scour and to help establish effective disaster measures, taking into account the locality and scour characteristics in Korea. This system is programmed using the techniques of the geographical information system(GIS) for the storage, retrieval, and display of information regarding to bridge scour. The system functions are basically divided into two parts; prioritization and maintenance. Bridges are initially screened and prioritized for bridge scour inspection and evaluation using the basic information which is obtained from the office review. The bridge scour evaluation including site investigation is performed and the vulnerability of bridge piers is categorized into six groups taking into account the local scour depth, foundation bearing capacity, foundation type, foundation depth, and present scour condition. The system tabulates and plots all the data and the results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.3
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• pp.416-423
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• 2003

During the last ten years, the need has been increased for reducing maintenance cost for aged equipments and ensuring safety, efficiency and profitability of petrochemical and refinery plants. RBI (Risk Based Inspection) methodology is one of the most promising technologies satisfying the need in the field of integrity management. In this study, a user-friendly software, realRBl for RBI based on the API 581 code was developed. This software has modules for evaluating qualitative and semi-quantitative risk level, analyzing quantitative risks using the potential consequences of a failure of the pressure boundary, and assessing the likelihood of failure. A quantitative analysis was performed for 16 columns in a domestic NCC (Naphtha Cracking Center) plant whose operating time reaches about 12 years. Each column was considered as two equipment parts by dividing into top and bottom. Generic column failure frequencies were adjusted based on likelihood data. After determining release rate, release duration and release mass for each failure scenario, flammable/explosive and toxic consequences were assessed. Current risks for 32 equipment parts were evaluated and risk based prioritization were determined as a final result.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.1-14
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• 2017

Recently, the automobile industry is rapidly changing due to autonomous vehicles based on advanced ICT technology. As a result, studies related to autonomous vehicles have also been actively conducted. However, most studies are focusing on the autonomous driving technology so that the prediction of changes in road traffic safety and associated legal system due to the introduction of autonomous vehicles are lacking. The purpose of this study is to suggest improvement methods and priorities of road traffic safety projects according to the introduction of autonomous vehicles. As a result of the AHP analysis using the results of the questionnaire surveyed for autonomous driving car experts, it was analyzed that revision of the traffic safety inspection law and development of education system for autonomous driving motor drivers and operators should be given top priority.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.843-852
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• 2022

Despite continuous safety management, the death rate of construction workers is not decreasing every year. Accordingly, various studies are in progress to prevent construction site accidents. In this paper, we developed an AI-based priority inspection target selection model that preferentially selects sites are expected to cause construction accidents among construction sites with construction costs of less than 5 billion won (KRW). In particular, Random Forest (90.48 % of accident prediction AUC-ROC) showed the best performance among applied AI algorithms (Classification analysis). The main factors causing construction accidents were construction costs, total number of construction days and the number of construction performance evaluations. In this study an ROI (return of investment) of about 917.7 % can be predicted over 8 years as a result of better efficiency of manual inspections human resource and a preemptive response to construction accidents.

• Corrosion Science and Technology
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• v.14 no.1
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• pp.1-11
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• 2015

Local wall thinning and integrity degradation caused by several mechanisms, such as flow accelerated corrosion (FAC), cavitation, flashing and/or liquid drop impingements, are a main concern in carbon steel piping systems of nuclear power plant in terms of safety and operability. Thinned pipe management program (TPMP) had been developed and optimized to reduce the possibility of unplanned shutdown and/or power reduction due to pipe failure caused by wall thinning in the secondary side piping system. This program also consists of several technical elements such as prediction of wear rate for each component, prioritization of components for inspection, thickness measurement, calculation of actual wear and wear rate for each component. Decision making is associated with replacement or continuous service for thinned pipe components. Establishment of long-term strategy based on diagnosis of plant condition regarding overall wall thinning is also essential part of the program. Prediction models of wall thinning caused by FAC had been established for 24 operating nuclear plants. Long term strategies to manage the thinned pipe component were prepared and applied to each unit, which was reflecting plant specific design, operation, and inspection history, so that the structural integrity of piping system can be maintained. An alternative integrity assessment criterion and a computer program for thinned piping items were developed for the first time in the world, which was directly applicable to the secondary piping system of nuclear power plant. The thinned pipe management program is applied to all domestic nuclear power plants as a standard procedure form so that it contributes to preventing an accident caused by FAC.