• Computers and Concrete
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• 제28권5호
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• pp.507-519
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• 2021

In this study, a new procedure was proposed in order to predict the crack pattern and failure mode of steel fiber reinforced concrete (SFRC) corbels. Moreover, an experimental study was carried out in order to investigate the effect of several parameters, such as compressive strength, tensile strength, steel fiber ratio, shear span on the mechanical behavior of SFRC corbels in detail. Totally, 24 RC and SFRC corbels were prepared for the experimental study. Experimental results indicate that each investigated parameter has noticeable effect on the load capacity and failure mode of SFRC corbels. Moreover, finite element (FE) model of the tested corbels were prepared and efficiency of FE model was investigated for further studies. Comparison of FE and experimental results show that there is an acceptable fit between them regarding load capacity and crack patterns. Thereafter, parametric study was carried out via FE analyses in order to obtain a methodology for crack pattern and failure mode prediction of SFRC corbels. As a result of parametric studies, a new procedure was proposed as flowcharts in order to predict the failure mode of SFRC corbels for normal and high strength concrete class separately.

• 플랜트 저널
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• 제15권2호
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• pp.56-61
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• 2019

본 연구에서는 500 MW급 초임계압 석탄 화력발전소의 발전보일러용 고압 급수가열기에서 발생한 내부 튜브의 파손 사례 분석을 통해 운전 기록 모니터링에 의한 발전보일러용 고압 급수가열기 내부 튜브의 파손 예측 방안을 모색하고자 하였다. 이 연구를 통해 고압 급수가열기 내부 튜브 파손 시 쉘 측 수위 조절 밸브 개도와 보일러 급수펌프 흡입 유량의 변화로 내부 튜브 파손을 진단할 수 있는 예측 모형을 제안하였고, 제안된 예측 모형은 급수 계통의 불균형이 일어난 추가 사례를 통해 실증하였다. 이에 따라 본 연구와 유사한 특성의 발전보일러용 고압 급수가열기의 경우에도 쉘 측 수위 조절 밸브 개도와 보일러 급수펌프의 흡입 유량의 정상 운전 상태 값 대비 현재 운전 값 비교는 고압 급수가열기 내부 튜브의 파손에 대한 유력한 예측 진단 방안이 될 수 있다고 판단된다.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2011년도 춘계학술발표대회 논문집
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• pp.257-264
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• 2011

In this study, we performed sensitivity study of the $217Plus^{TM}$ system model to various parameters. Specific attention was put to logistics model and its behavior has been examined in terms of non-component failure causes. We first briefly explained the $217Plus^{TM}$ methodology with system level failure rate evaluation. We then applied experimental designs with several failure causes as factors. We used an orthogonal array with three levels of each parameter. Our results indicate that cannot duplicate, induced, and wear-out causes have dominant effects on the system failures and design, parts, and system management have much less but a little strong effects. The results in this study not only figure out the behavior of the predicted failure rate as functions of failure causes but provide meaningful guidelines for practical applications.

• 산업경영시스템학회지
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• 제22권52호
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• pp.171-180
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• 1999

Industrial equipment reliability improvement and maintenance is gaining attention as the next great opportunity for manufacturing productivity improvement. Reactive maintenance is expensive because of extensive unplanned downtime and damage to machinery. To avoid such an unplanned machine downtime, it is needed to use proactive maintenance approach by either using historical maintenance data or by sensing machine conditions. This paper discusses failure diagonosis and prediction based on the condition-based maintenance and reliability technique. Thus, by enabling such a framework, it can bring us more efficient planning and execution of maintenance to reduce costs and/or increase profits.

• 융합정보논문지
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• 제7권1호
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• pp.55-60
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• 2017

사물인터넷 환경에서 인간의 개입 없는 지능화된 서비스를 위해서는 IoT 디바이스에서 생성되는 빅데이터로 부터 정상 패턴을 학습하고 이를 기반으로 불량, 오작동과 같은 이상 징후에 대해 예측하는 과정이 요구된다. 본 연구의 목적은 제품 공정의 다양한 기기에서 발생되는 빅데이터를 분석함으로써 제품 불량을 예측할 수 있는 기계 학습모델을 구현하는 것이다. 기계 학습 모델은 어느 정도 볼륨을 가진 기존 데이터를 기반으로 분석을 해야 하므로 빅데이터 분석도구 R을 사용하였으며, 제품 공정에서 수집된 데이터에는 제품에 대한 불량 여부가 포함되어 있으므로 지도 학습 모델을 활용하였다. 연구의 결과, 제품 불량에 영향을 주는 변수 및 변수 조건을 분류하였고, 의사결정 트리를 기반으로 제품의 불량 여부에 대한 예측 모델을 제시하였다. 또한, ROC Curve를 이용한 모델의 적합성 및 성능평가 분석에서 모델의 예측력은 상당히 높게 나타났다.

• International Journal of Concrete Structures and Materials
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• 제5권1호
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• pp.57-64
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• 2011

An extensive database has been constructed of reinforced concrete (RC) beam-column connection tests subjected to cyclic lateral loading. All cases within the database experienced joint shear failure, either in conjunction with or without yielding of longitudinal beam reinforcement. Using the experimental database, envelope curves of joint shear stress vs. joint shear strain behavior have been created by connecting key points such as cracking, yielding, and peak loading. Various prediction approaches for RC joint shear behavior are discussed using the constructed experimental database. RC joint shear strength and deformation models are first presented using the database in conjunction with a Bayesian parameter estimation method, and then a complete model applicable to the full range of RC joint shear behavior is suggested. An RC joint shear prediction model following a U.S. standard is next summarized and evaluated. Finally, a particular joint shear prediction model using basic joint shear resistance mechanisms is described and for the first time critically assessed.

• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.535-541
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• 2007

The Non-homogeneous Poisson process is probably the most popular model since it can model systems that are deteriorating or improving. The renewal process is a model that is often used to describe the random occurrence of events in time. But both these models are based on too restrictive assumptions on the effect of the repair action. The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose maximum likelihood estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model.

• 한국농공학회논문집
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• 제59권5호
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• pp.101-108
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• 2017

Recently, the occurrence of landslides has been increasing over the years due to the extreme weather event. Developments of landslides monitoring technology that reduce damage caused by landslide are urgently needed. Therefore, in this study, a strain ratio sensor was developed to predict the ground behavior during the slope failure, and the change in surface ground displacement was observed as slope failed on the field model experiment. As a result, in the slope failure, the ground displacement process increases the risk of collapse as the inverse displacement approaches zero. It is closely related to the prediction of precursor. In all cases, increase in displacement and reverse speed of inverse displacement with time was observed during the slope failure, and it is very important event for monitoring collapse phenomenon of risky slopes. In the future, it can be used as disaster prevention technology to contribute in reduction of landslide damage and activation of measurement industry.

• Journal of Mechanical Science and Technology
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• 제16권7호
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• pp.889-895
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• 2002

This paper presents the effect of external corrosion, material properties, operation condition and design thickness in pipeline on failure prediction using a failure probability model. The predicted failure assessment for the simulated corrosion defects discovered in corroded pipeline is compared with that determined by ANSI/ASME B31G code and a modified B31G method. The effects of environmental, operational, and random design variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress and pipe thickness on the failure probability are systematically studied using a failure probability model for the corrosion pipeline.

• 한국정밀공학회지
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• 제21권1호
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• pp.173-180
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• 2004

This paper presents the effect of varying boundary conditions such as ground subsidence, internal pressure and temperature variation for buried pipelines on failure prediction by using a failure probability model. The first order Taylor series expansion of the limit state function incorporating with von-Mises failure criteria is used in order to estimate the probability of failure mainly associated with three cases of ground subsidence. Using stresses on the buried pipelines, we estimate the probability of pipelines with von-Mises failure criterion. The effects of varying random variables such as pipe diameter, internal pressure, temperature, settlement width, load for unit length of pipelines, material yield stress and pipe thickness on the failure probability of the buried pipelines are systematically studied by using a failure probability model for the pipeline crossing ground subsidence regions which have different soil properties.