• Smart Structures and Systems
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• 제6권5_6호
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• pp.561-578
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• 2010

This study proposes a multi-level damage localization strategy to achieve an effective damage detection system for civil infrastructure systems based on wireless sensors. The proposed system is designed for use of distributed computation in a wireless sensor network (WSN). Modal identification is achieved using the frequency-domain decomposition (FDD) method and the peak-picking technique. The ASH (angle-between-string-and-horizon) and AS (axial strain) flexibility-based methods are employed for identifying and localizing damage. Fundamentally, the multi-level damage localization strategy does not activate all of the sensor nodes in the network at once. Instead, relatively few sensors are used to perform coarse-grained damage localization; if damage is detected, only those sensors in the potentially damaged regions are incrementally added to the network to perform finer-grained damage localization. In this way, many nodes are able to remain asleep for part or all of the multi-level interrogations, and thus the total energy cost is reduced considerably. In addition, a novel distributed computing strategy is also proposed to reduce the energy consumed in a sensor node, which distributes modal identification and damage detection tasks across a WSN and only allows small amount of useful intermediate results to be transmitted wirelessly. Computations are first performed on each leaf node independently, and the aggregated information is transmitted to one cluster head in each cluster. A second stage of computations are performed on each cluster head, and the identified operational deflection shapes and natural frequencies are transmitted to the base station of the WSN. The damage indicators are extracted at the base station. The proposed strategy yields a WSN-based SHM system which can effectively and automatically identify and localize damage, and is efficient in energy usage. The proposed strategy is validated using two illustrative numerical simulations and experimental validation is performed using a cantilevered beam.

• 한국항해학회지
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• 제25권4호
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• pp.417-422
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• 2001

Every ship might be exposed to collision, grounding and/or various accidents. They may make some underwater holes on the hull. An underwater damage would cause her loss of buoyancy, trim, and inclination. Although a ship has some provisions against these accidents, if the circumstance is serious, she would be sunk or upsetted. Because of varieties of type of accidents, one could not prepare all of them. Many subdivision could prevent them, but it is difficult to realize it due to rising costs. This paper deals with physical phenomena of sinkage and an application on box type ship, and some results are earned as follows； 1. sinkage speed up to the level of the damage hole is increased proportionally, and is decreased proportionally after filling the level. 2. the curve of draft shows cup type of second order polynomial up to the damage hole level, and shows cap type of second order polynomial after filling the level. 3. if damage occurs beneath half of the draft, changes of head and displacement, and sinking speed follow almost straight lines. 4. by careful observation, sinkage speed could be predicted.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.85-88
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• 2008

Damage from typhoon disaster can be mitigated by grasping and dealing with the damage promptly for the regions in typhoon track. What is this work, a technique to analyzed dangerousness of typhoon should be presupposed. This study estimated 10m level wind speed using 700hPa wind by typhoon, referring to GPS dropwindsonde study of Franklin(2003). For 700hPa wind, 30km resolution data of Regional Data Assimilation Prediction System(RDAPS) were used. For roughness length in estimating wind of 10m level, landuse data of USGS are employed. For 10m level wind speed of Typhoon Rusa in 2002, we sampled AWS point of $7.4\sim30km$ distant from typhoon center and compare them with observational data. The results show that the 10m level wind speed is the estimation of maximum wind speed which can appear in surface by typhoon and it cannot be compared with general hourly observational data. Wind load on domestic buildings relies on probability distributions of extreme wind speed. Hence, calculated 10m level wind speed is useful for estimating the damage structure from typhoon.

• 시큐리티연구
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• 제14호
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• pp.261-283
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• 2007

범죄두려움의 원인을 설명하기 위한 최근의 연구들에서는 성, 연령, 경제수준, 범죄 피해경험 등의 미시적인 개인수준과 거시적인 지역수준과의 연계를 시도하는 연구에 관심과 노력을 보이고 있다. 하지만 이 연구에서는 이러한 지역수준의 특성에 대한 개인의 관심과 해석은 개인의 특성으로서 과거의 범죄피해경험, 범죄피해의 취약성 정도, 범죄관련 정보에 대한 관심에 따라 다를 수 있다고 보며, 미시적인 수준과 거시적인 수준의 연계를 시도하기에 앞서 개인적인 수준에서 개인의 특성과 범죄두려움의 관계에 대해서 실증적인 분석을 실시하였다. 따라서 이 연구의 목적은 범죄두려움이 과연 개인의 특성에 따라서 어떻게 느끼게 되며 또한 얼마나 많은 영향을 받게 되는지를 실증적으로 검증하는 데에 그 목적이 있다. 이 연구의 조사결과 우선 범죄피해경험이 집단간의 차이가 통계적으로 유의미한 인구통계학적 특성은 연령, 결혼상태, 최종학력, 거주하는 장소였으며, 범죄피해의 취약성 정도는 성별과 결혼상태, 범죄관련 정보에 대한 관심은 성별, 연령, 최종학력, 가족 수입, 거주장소 위치에 따라서 집단 간의 통계적으로 유의미한 차이가 있는 것으로 나타났다. 둘째, 개인적 특성 요인과 범죄두려움의 상관관계 분석을 실시한 결과 독립변수 세요인 모두 범죄두려움과 통계적으로 유의미한 상관관계를 나타내고 있었으며, 특히 범죄피해에 대한 취약성 요인이 범죄두려움과 가장 상관관계가 높게 나타났다. 마지막으로 개인의 특성으로서 범죄피해의 취약성, 범죄정보에 대한 관심, 범죄피해경험은 범죄두려움에 영향을 미쳤으며, 특히 이러한 개인적 특성 요인 중 자신이 범죄피해에 대해 취약하다고 생각 하는 범죄피해의 취약성이 범죄두려움에 가장 많은 영향을 미치는 요인으로 나타났다.

• Composites Research
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• 제12권2호
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• pp.62-69
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• 1999

복합재료가 피로하중을 받으면 재료 내부에 손상이 누적되며, 이는 재료의 물성 변화로 나타난다. 본 연구에서는 손상을 나타내는 인자로 피로계수를 사용하였다. 피로계수와 참고계수로 정의되는 손상함수로부터 복합재료의 피로수명 예측을 이론적으로 연구하였다. 제안된 모델들은 인가 응력 수준, 피로주기 및 피로수명의 함수로 유도하였다. 예측 결과는 유리섬유/에폭시 복합재료와 유리섬유/폴리에스터 복합재료를 사용한 다중응력 피로 실험 데이터를 이용하여 검증하였다.

• 대한기계학회논문집A
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• 제25권7호
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• pp.1089-1096
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• 2001

This paper presents the fatigue behavior of composite materials with impact-induced damage under 2 level block loading. For this purpose, the 2 level block loading fatigue tests were performed on the impacted composite laminate. The fatigue life of the laminate under the block loading is greatly influenced by the impact damage; the effect of impact damage can be characterized by the present impact damage parameter. Based on this parameter, the model is developed to predict the fatigue life under block loading and the results by this model agree well with experimental results regardless of applied impact energy. Also, stochastic model is established to describe the variation of cumulative damage behavior and fatigue life due to the material nonhomogeneity.

• Wind and Structures
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• 제15권5호
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• pp.369-383
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• 2012

Researchers have recently begun using high spatial resolution remote-sensing data, which are automatically captured and georeferenced, to assess damage following natural and man-made disasters, in addition to, or instead of employing the older methods of walking house-to-house for surveys, or photographing individual buildings from an airplane. This research establishes quantitative relationships between the damage states observed at ground-level, and those observed from space using high spatial resolution remote-sensing data, for windstorms, for individual site-built one- or two-family residences (FR12). "Degrees of Damage" (DOD) from the Enhanced Fujita (EF) Scale were determined for ground-based damage states; damage states were also assigned for remote-sensing imagery, using a modified version of Womble's Remote-Sensing (RS) Damage Scale. The preliminary developed model can be used to predict the ground-level damage state using remote-sensing imagery, which could significantly lessen the time and expense required to assess the damage following a windstorm.

• 방사성폐기물학회지
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• 제19권2호
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• pp.197-204
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• 2021

In this study, the well-known non-destructive acoustic emission (AE) and electrical resistivity methods were employed to predict quantitative damage in the silo structure of the Wolsong Low and Intermediate Level Radioactive Waste Disposal Center (WLDC), Gyeongju, South Korea. Brazilian tensile test was conducted with a fully saturated specimen with a composition identical to that of the WLDC silo concrete. Bi-axial strain gauges, AE sensors, and electrodes were attached to the surface of the specimen to monitor changes. Both the AE hit and electrical resistance values helped in the anticipation of imminent specimen failure, which was further confirmed using a strain gauge. The quantitative damage (or damage variable) was defined according to the AE hits and electrical resistance and analyzed with stress ratio variations. Approximately 75% of the damage occurred when the stress ratio exceeded 0.5. Quantitative damage from AE hits and electrical resistance showed a good correlation (R = 0.988, RMSE = 0.044). This implies that AE and electrical resistivity can be complementarily used for damage assessment of the structure. In future, damage to dry and heated specimens will be examined using AE hits and electrical resistance, and the results will be compared with those from this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.786-799
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• 2021

Road damage detection is important for road maintenance. With the development of deep learning, more and more road damage detection methods have been proposed, such as Fast R-CNN, Faster R-CNN, Mask R-CNN and RetinaNet. However, because shallow and deep layers cannot be extracted at the same time, the existing methods do not perform well in detecting objects with fewer samples. In addition, these methods cannot obtain a highly accurate detecting bounding box. This paper presents a Multi-level Feature Pyramids method based on M2det. Because the feature layer has multi-scale and multi-level architecture, the feature layer containing more information and obvious features can be extracted. Moreover, an attention mechanism is used to improve the accuracy of local boundary boxes in the dataset. Experimental results show that the proposed method is better than the current state-of-the-art methods.

• Journal of the Korean Statistical Society
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• 제28권2호
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• pp.235-251
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• 1999

In this paper we examine extremal behavior of a $textsc{k}$th-order stationary Markov chain {X\ulcorner} by considering excesses over a high level which typically appear in clusters. Excesses over a high level within a cluster define a cluster damage, i.e., a normalized sum of all excesses within a cluster, and all excesses define a damage point process. Under some distributional assumptions for {X\ulcorner}, we prove convergence in distribution of the cluster damage and obtain a representation for the limiting cluster damage distribution which is well suited for simulation. We also derive formulas for the mean and the variance of the limiting cluster damage distribution. These results guarantee a compound Poisson limit for the damage point process, provided that it is strongly mixing.