• Structural Monitoring and Maintenance
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• 제3권1호
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• pp.51-69
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• 2016

Monitoring the performance and estimating the remaining useful life of aging civil infrastructure in the United States has been identified as a major objective in the civil engineering community. Structural health monitoring has emerged as a central tool to fulfill this objective. This paper presents a review of the major structural monitoring programs that have been recently implemented in the United States, focusing on the integrity and performance assessment of large-scale structural systems. Applications where response data from a monitoring program have been used to detect and correct structural deficiencies are highlighted. These applications include (but are not limited to): i) Post-earthquake damage assessment of buildings and bridges; ii) Monitoring of cables vibration in cable-stayed bridges; iii) Evaluation of the effectiveness of technologies for retrofit and seismic protection, such as base isolation systems; and iv) Structural damage assessment of bridges after impact loads resulting from ship collisions. These and many other applications show that a structural health monitoring program is a powerful tool for structural damage and condition assessment, that can be used as part of a comprehensive decision-making process about possible actions that can be undertaken in a large-scale civil infrastructure system after potentially damaging events.

• Structural Engineering and Mechanics
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• 제81권6호
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• pp.781-790
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• 2022

The present paper describes a general procedure of the structural safety assessment for the independent type C tank of LNG bunkering ship. This strength assessment procedure consists of two main scheme, global Finite Element Analysis (FEA) model primarily for hull structure assessment and detailed LNG Tank structures FEA model including the cylindrical tank itself and saddle-support structures. Two kinds of mechanism are used, fixed and slides constraints in fore and rear of the saddle-support structures that result in a variation of the reaction forces. Finite Element (FE) analyses have been performed and verified by the strength acceptance criteria to evaluate the safety adequacy of yielding and buckling of the hull and supporting structures. The detail of FE model for an LNG type C tank and its saddle supports was made, which includes the structural members such as cylindrical tank shell, ring stiffeners, swash bulkhead, and saddle supports. Subsequently, the FE buckling analysis of the Type C tank has been performed under external pressure following International Gas Containment (IGC) code requirements. Meanwhile, the assessment is also performed for yielding and buckling strength evaluation of the cylindrical LNG tank according to the PD 5500 unfired fusion welded pressure vessels code. Finally, a complete procedure for assessing the structural strength of 500 CBM LNG cargo tank, saddle support and hull structures have been provided.

• 전산구조공학
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• 제10권3호
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• pp.15-21
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• 1997

Modern ocean-going vessels are highly dynamically loaded all-welded structures. Traditionally, this fact has been taken into account in the design of ship structures by keeping the overall stress level within permissible limits and by limiting notch effects in the design of local structures. With an improving knowledge of loads and the rapid development of calculation means more detailed calculation-based methods are increasingly introduced. A brief review on fatigue assessment methods used in the design of ship structures has been given during the 1993 IIW International Conference in Glasgow. The rapid development during recent years underlines the importace of the subject and justifies its extended discussion in this paper.

• 한국구조물진단유지관리공학회 논문집
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• 제7권3호
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• pp.167-174
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• 2003

우리나라 군 시설에서 조적조가 차지하는 비중은 매우 크며, 군 시설 현대화사업의 추진 등으로 성능에 대한 정확한 평가가 없이 노후 시설물을 철거하는 경우가 있어서 낭비를 초래하고 있다. 본 연구는 조적조 노후 군시설을 효율적으로 유지보수 하는데 도움을 주기 위해서 시설물의 기울기 및 침하, 내하력, 내구성 등을 조사하여 시설물 전반의 성능을 객관적으로 평가할 수 있는 기준을 제시하였다. 내하력은 조적상태, 줄눈모르터 상태, 긴결철물의 상태, 테두리보 상태, 하중상태 등으로 평가하고, 내구성은 균열, 표면노후화, 진동등의 항목으로 평가하도록 하였다. 평가항목의 중요도는 AHP 기법을 적용하여 산정한 가중치로 결정하였다. 조사대상 조적조 노후 군시설의 성능을 판정할 수 있는 절차도 제시하였으며, 사례연구를 통하여 본 연구에서 제시한 평가기준의 적용성을 확인할 수 있었다.

• Smart Structures and Systems
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• 제24권5호
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• 아동학회지
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• 제22권1호
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• pp.227-240
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• 2001

This review examined trends in research on the assessment of Korean children's story comprehension. Specific areas that were analyzed included types of questions asked in the assessment and variables treated as relevant to the assessment of story comprehension. Literal, inferential, and critical questions were identified. Among the 33 studies reviewed, 20 used all 3 types of questions, the other 13 used only literal questions. The studies using only literal questions interpreted comprehension of a story as "comprehension of letters and/or components of a story." The other studies interpreted it as "comprehension of implied meaning of a story." Other relevant variables were "teaching strategies" (29 studies) and "structural components" (4 studies). None of the studies treated "children's internal variables related to story comprehension."

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.257-271
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• 2016

The Structural SIMilarity (SSIM) index is one of the most widely-used methods for perceptual image quality assessment (IQA). It is based on the principle that the human visual system (HVS) is sensitive to the overall structure of an image. However, it has been reported that indices predicted by SSIM tend to be biased depending on the type of distortion, which increases the deviation from the main regression curve. Consequently, SSIM can result in serious performance degradation. In this study, we investigate the aforementioned phenomenon from a new perspective and review a constant that plays a big role within the SSIM metric but has been overlooked thus far. Through an experimental study on the influence of this constant in evaluating images with SSIM, we are able to propose a new solution that resolves this issue. In the proposed IQA method, we first design a system to classify different types of distortion, and then match an optimal constant to each type. In addition, we supplement the proposed method by adding color perception-based structural information. For a comprehensive assessment, we compare the proposed method with 15 existing IQA methods. The experimental results show that the proposed method is more consistent with the HVS than the other methods.

• Steel and Composite Structures
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• 제14권4호
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• pp.379-395
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• 2013

Aim of this paper is to apply to a steel truss bridge a methodology that takes into account the consequences of extreme loads on structures, focusing on the influence that the loss of primary elements has on the structural load bearing capacity. In this context, the topic of structural robustness, intended as the capacity of a structure to withstand damages without suffering disproportionate response to the triggering causes while maintaining an assigned level of performance, becomes relevant. In the first part of this study, a brief literature review of the topics of structural robustness, collapse resistance and progressive collapse takes place, focusing on steel structures. In the second part, a procedure for the evaluation of the structural response and robustness of skeletal structures under impact loads is presented and tested in simple structures. Following that, an application focuses on a case study bridge, the extensively studied I-35W Minneapolis steel truss bridge. The bridge, which had a structural design particularly sensitive to extreme loads, recently collapsed for a series of other reasons, in part still under investigation. The applied method aims, in addition to the robustness assessment, at increasing the collapse resistance of the structure by testing alternative designs.

• Structural Monitoring and Maintenance
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• 제3권1호
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• pp.91-114
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• 2016

In this paper, recent research trends and activities on structural health monitoring (SHM) of civil infrastructure in Korea are reviewed. Recently, there has been increasing need for adopting smart sensing technologies to SHM, so this review focuses on smart sensing, monitoring, and assessment for civil infrastructure. Firstly, the research activities on smart sensor technology is reviewed including optical fiber sensors, piezoelectric sensors, wireless smart sensors, and vision-based sensing system. Then, a brief overview is given to the recent advances in smart monitoring and assessment techniques such as vibration-based global monitoring techniques, local monitoring with piezoelectric materials, decentralized monitoring techniques for wireless sensors, wireless power supply and energy harvest. Finally, recent joint SHM activities on several test beds in Korea are discussed to share the up-to-date information and to promote the smart sensors and monitoring technologies for applications to civil infrastructure. It includes a Korea-US joint research on test bridges of the Korea Expressway Corporation (KEC), a Korea-US-Japan joint research on Jindo cable-stayed bridge, and a comparative study for cable tension measurement techniques on Hwamyung cable-stayed bridge, and a campaign test for displacement measurement techniques on Sorok suspension bridge.

• 품질경영학회지
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• 제39권1호
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• pp.90-97
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• 2011

The purpose of this study is to analyze various factors comprising a job satisfaction; determine possible factors that affects job satisfaction. Job satisfaction model is designed to evaluate major factors, such as job stress and strength, and to assess relationship between these factors. Partial least squares algorithm is used to develop a job satisfaction measurement model. To evaluate validity of developed model, survey data of health insurance review and assessment service is to applied.