• Structural Engineering and Mechanics
• /
• 제41권4호
• /
• pp.539-558
• /
• 2012

The diagnosis of bridge serviceability is carried out by a combination of in-situ visual inspection, static and dynamic loading tests and analyses. Structural health monitoring (SHM) using information technology and sensors is increasingly being used for providing a better estimate of structural performance characteristics rather than above traditional methods. Because the mechanical behavior of bridges with various kinds of damage can not be made clear, it is very difficult to estimate both the damage mode and degree of damage of existing bridges. In this paper, the sensitivity of both static and dynamic behaviors of bridges are studied as a measure of damage assessment through experiments on model bridges induced with some specified artificial damages. And, a method of damage assessment of bridges based on those behaviors is discussed in detail. Finally, based on the results, a possible application for structural health monitoring systems for existing bridges is also discussed.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2002년도 가을 학술발표회 논문집
• /
• pp.311-318
• /
• 2002

A GIS-based tunnelling risk management system (GIS-TURIMS) has been developed in this study, The developed system uses ArcView 8.2 as a basic platform and the built-in interface (VBA) has been used to perform first-order simplified analyses for prediction of tunnelling-induced ground movements and building damage assessment. The main emphasis in this study was to develop a working framework that can be used in the perspective of tunnelling risk management. The developed system is capable of carrying out computationally intensive analyses for ground movement prediction as well as building/utilities damage assessment with fully taking advantage of the GIS technologies. This paper describes the concept and details of the GIS-TURIMS development and implementation

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2004년도 춘계학술대회
• /
• pp.479-484
• /
• 2004

For the rational design of welded joint, it is needed to assess repeatedly the fatigue life of the joint with various dimensions and welding conditions. In this paper, an automation of repeated process of fatigue life assessment for welded cruciform joint was studied. The process is related to stress analysis in vicinity of weld-toe and fatigue life assessment based on analyzed stress distribution. With the change of design condition including dimensions and/or welding heat input, the above two works have to be performed. Using the commercial tool for system integration, ModelCenter, an automation of the repeated process for welded cruciform joint based on 2D modeling was achieved. In this automation system, data exchanges between programs regardless of commercial or in-house one work well, and parametric studies for optimal design can be performed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권5호
• /
• pp.2414-2428
• /
• 2018

In order to solve the problem that the current network security situation assessment methods just focus on the attack behaviors, this paper proposes a kind of network security situation assessment method based on Markov Decision Process and Game theory. The method takes the Markov Game model as the core, and uses the 4 levels data fusion to realize the evaluation of the network security situation. In this process, the Nash equilibrium point of the game is used to determine the impact on the network security. Experiments show that the results of this method are basically consistent with the expert evaluation data. As the method takes full account of the interaction between the attackers and defenders, it is closer to reality, and can accurately assess network security situation.

• 한국멀티미디어학회논문지
• /
• 제23권12호
• /
• pp.1447-1453
• /
• 2020

In this paper, we propose a method for no-reference quality assessment of sports videos using 3D shearlet transform and deep residual neural networks. In the proposed method, 3D shearlet transform-based spatiotemporal features are extracted from the overlapped video blocks and applied to logistic regression concatenated with a deep residual neural network based on a conditional video block-wise constraint to learn the spatiotemporal correlation and predict the quality score. Our evaluation reveals that the proposed method predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권8호
• /
• pp.3602-3620
• /
• 2016

Dynamic topology is one of the main influence factors on network performability. However, it was always ignored by the traditional network performability assessment methods when analyzing large-scale mobile ad hoc networks (MANETs) because of the state explosion problem. In this paper, we address this problem from the perspective of complex network. A two-layer hierarchical modeling approach is proposed for MANETs performability assessment, which can take both the dynamic topology and multi-state nodes into consideration. The lower level is described by Markov reward chains (MRC) to capture the multiple states of the nodes. The upper level is modeled as a small-world network to capture the characteristic path length based on different mobility and propagation models. The hierarchical model can promote the MRC of nodes into a state matrix of the whole network, which can avoid the state explosion in large-scale networks assessment from the perspective of complex network. Through the contrast experiments with OPNET simulation based on specific cases, the method proposed in this paper shows satisfactory performance on accuracy and efficiency.

• 한국지반신소재학회논문집
• /
• 제18권4호
• /
• pp.39-52
• /
• 2019

In this paper the development and implementation of an artificial intelligence (AI)-based Tunnelling Impact prediction and assessment program (SKKU-iTunnel) is presented. Program predicts tunnelling induced surface settlement and groundwater drawdown by utilizing well trained ANNs and uses these predicted values to perform the damage assessment likely to occur in nearby structures and pipelines/utilities for a given tunnel problem. Generalised artificial neural networks (ANNs) were trained, to predict the induced parameters, through databases generated by combining real field data and numerical analysis for cases that represented real field conditions. It is shown that program equipped with carefully trained ANN can predict tunnel impact assessments and perform damage assessments quiet efficiently and comparable accuracy to that of numerical analysis. This paper describes the idea and implementation details of the SKKU-iTunnel with an example for demonstration.

• Journal of Electrical Engineering and Technology
• /
• 제1권4호
• /
• pp.414-422
• /
• 2006

Deterministic techniques have been applied in power system planning for many years and there is a growing interest in combining these techniques with probabilistic considerations to assess the increased system stress due to the restructured electricity environment. The overall reliability framework proposed in this paper incorporates the deterministic N-1 criterion in a probabilistic framework, and results in the joint inclusion of both adequacy and security considerations in system planning. The combined framework is achieved using system well-being analysis and traditional adequacy assessment. System well-being analysis is used to quantify the degree of N-1 security and N-1 insecurity in terms of probabilities and frequencies. Traditional adequacy assessment is Incorporated to quantify the magnitude of the severity and consequences associated with system failure. The concepts are illustrated by application to two test systems. The results based on the overall reliability analysis framework indicate that adequacy indices are adversely affected by a generation deficient environment and security indices are adversely affected by a transmission deficient environment. The combined adequacy and security framework presented in this paper can assist system planners to realize the overall benefits associated with system modifications based on the degree of adequacy and security, and therefore facilitate the decision making process.

• 대한기계학회논문집A
• /
• 제37권10호
• /
• pp.1291-1296
• /
• 2013

위험도 평가 기술은 주로 플랜트의 많은 운영설비 중 대형사고나 피해를 유발할 수 있는 위험설비를 선별하는 목적으로 개발되었다. 설비의 위험도를 평가하여 위험도의 크기에 따라 순위를 정하고 이 순위를 기준으로 정비자원을 투입하는 순서나 정비작업의 시급성을 판단한다. 위험도란 고장이 발생할 확률과 고장이 발생할 경우에 수반되는 파손피해의 곱으로 정의된다. 위험도 평가방법으로는 간단한 손상 및 고장 평가기법을 이용하여 기본적인 고장확률 데이터를 확보하고 정성적인 문진을 통해 이를 보완하는 준 정량적 방법이 많이 사용되고 있다. 본 논문에서는 준 정략적 평가를 이용하여 석탄화력발전소의 보일러설비에 대한 위험도 평가를 수행하고 이를 기반으로 설비 별차기 정비주기를 선정하였다.

• 공학교육연구
• /
• 제13권6호
• /
• pp.143-151
• /
• 2010

본 논문은 서울과학기술대학교(구 서울산업대학교) 기계설계자동화공학부에서 16년간의 캡스톤디자인 운영경험과 개선을 바탕으로 캡스톤디자인 교과목 기반의 프로그램 학습성과의 평가 사례에 대해 서술하였다. 우선, 캡스톤디자인 교과목과 관련된 프로그램 학습성과를 소개하였고, 평가 방법 및 항목에 대해서 설명하였다. 이를 바탕으로 하여 2008년도의 학습성과 평가 결과를 도출하였고, 이를 분석한 후 개선 전략을 수립하였다. 전략으로서 학생들에게 심사 기준과 모범사례를 온라인상에 미리 공개하였고, 그 결과 2009년도에는 전반적으로 약 3.3% 개선된 학습성과 평가 결과를 얻을 수 있었다. 마지막으로 코스 임베디드 평가 개념 측면에서 캡스톤디자인 교과목을 이용한 프로그램 학습성과 평가의 타당성, 효율성, 내실성, 그리고 지속가능성에 대해서도 논의하였다.