• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.107-115
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• 2018

To ensure the structural integrity of nuclear power plants, it is essential to predict the lifetime of Alloy 182 weld, which is used for welding in nuclear reactors. The lifetime of Alloy 182 weld is directly related to the crack initiation time. Owing to the large time scatter in most crack initiation tests, a probabilistic model, such as the Weibull distribution, has mainly been adopted for prediction. However, since statistically more advanced methods than current typical methods may be applied, we suggest a statistical procedure for parameter estimation of the crack initiation time of Alloy 182 weld, considering right-censored data and the covariate effect. Furthermore, we suggest a procedure for uncertainty evaluation of the estimators based on the bootstrap method. The suggested statistical procedure can be applied not only to Alloy 182 weld but also to any material degradation data set including right-censored data with covariate effect.

• Journal of Ship and Ocean Technology
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• v.2 no.1
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• pp.58-70
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• 1998

Many bulk carrier losses have been reported of late, and one of the possible causes of such casualties is thought to be the structural failure of aging hulls in rough weather. Clearly, in such cases, vessels that start out belong adequate somehow become marginal later in life. Fatigue and corrosion related potential problems may be the most important factors affecting such age related vessel damage. With respect to fatigue, extensive studies have been done worldwide both experimentally and theoretically, and the results have been applied to some extent. However, in the case of corrosion effects, additional research is still needed to better understand, clarify and address the various strength uncertainties and their effects on structural behavior. This paper develops a probabilistic corrosion rate estimation model for the longitudinal strength members of bulk carriers. The model is based on available statistical data for corrosion of existing bulk carriers. The corrosion data collected are documented for future use.

• Computers and Concrete
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• v.15 no.4
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• pp.485-501
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• 2015

Cooling by the flow of water through an embedded cooling pipe has become a common and effective artificial thermal control measure for massive concrete structures. However, an extreme thermal gradient induces significant thermal stress, resulting in thermal cracking. Using a mesoscopic finite-element (FE) mesh, three-phase composites of concrete namely aggregate, mortar matrix and interfacial transition zone (ITZ) are modeled. An equivalent probabilistic model is presented for failure study of concrete by assuming that the material properties conform to the Weibull distribution law. Meanwhile, the correlation coefficient introduced by the statistical method is incorporated into the Weibull distribution formula. Subsequently, a series of numerical analyses are used for investigating the influence of the correlation coefficient on tensile strength and the failure process of concrete based on the equivalent probabilistic model. Finally, as an engineering application, damage and failure behavior of concrete cracks induced by a water-cooling pipe are analyzed in-depth by the presented model. Results show that the random distribution of concrete mechanical parameters and the temperature gradient near water-cooling pipe have a significant influence on the pattern and failure progress of temperature-induced micro-cracking in concrete.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.102-110
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• 2009

The cost for maintenance of bridge structures such as repair or reinforcement is increasing. In addition, the efforts for inspection of bridge structures is becoming more important since the proper repair or reinforcement should be performed to save the maintenance cost and ensure the safety for public infrastructure. Therefore, it is studied on this paper to estimate the repair or reinforcement cycles using probabilistic approach for the steel-box girders of bridge superstructure. In addition, a computer simulation program is uniquely developed based on probabilistic approach to calculate the cycles derived from the function of age of bridge and performance rating curve which were previously studied. In order to ensure the reliability of results and appropriateness of the model, statistical analyses were performed. Also, the results were compared and proved to be similar with ones from previous statistical data related to the repair or reinforcement cycles. The results from this study is expected to be useful for the determination of proper time to repair or reinforce the bridge structure and raise the safetyness of bridge structure in advance.

• The Journal of Engineering Geology
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• v.14 no.2
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• pp.211-222
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• 2004

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The seven landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The seven factors consist of two topographic factors and five geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 90.74% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

• Tunnel and Underground Space
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• v.12 no.1
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• pp.19-30
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• 2002

Rock joint orientation is one of important geometric attributes that have an influence on the stability of rock structures such as rock slopes and tunnels. Especially, statistical models of the geometric attributes of rock joints can provide a probabilistic approach of rock engineering problems. The result from probabilistic modeling relies on the choice of statistical model. Therefore, it is critical to define a representative statistical model for joint orientation data as well as joint size and intensity and build up a series of modeling procedure including analytical validation. In this paper, we have examined a theoretical methodology for the statistical estimate and hypothesis analysis based upon Fisher distribution and bivariate normal distribution. In addition, we have proposed the algorithms of random number generator which is applied to the simulation of rock joint networks and risk analysis.

• Smart Structures and Systems
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• v.15 no.3
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• pp.699-715
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• 2015

A modal parameter based damage sensitive feature (DSF) is defined to mimic the relative change in any diagonal element of the stiffness matrix of a model of a structure. The damage assessment is performed in a statistical pattern recognition framework using empirical complementary cumulative distribution functions (ECCDFs) of the DSFs extracted from measured operational vibration response data. Methods are discussed to perform probabilistic structural health assessment with respect to the following questions: (a) "Is there a change in the current state of the structure compared to the baseline state?", (b) "Does the change indicate a localized stiffness reduction or increase?", with the latter representing a situation of retrofitting operations, and (c) "What is the severity of the change in a probabilistic sense?". To identify a range of normal structural variations due to environmental and operational conditions, lower and upper bound ECCDFs are used to define the baseline structural state. Such an approach attempts to decouple "non-damage" related variations from damage induced changes, and account for the unknown environmental/operational conditions of the current state. The damage assessment procedure is discussed using numerical simulations of ambient vibration testing of a bridge deck system, as well as shake table experimental data from a 4-story steel frame.

• Journal of Korean Society on Water Environment
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• v.24 no.3
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• pp.345-353
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• 2008

In order to design storage-based non-point source management facilities, the aspect of statistical features of the entire precipitation time series should be considered since non-point source pollutions are delivered by continuous rainfall runoffs. The 3-parameter mixed exponential probability density function instead of traditional single-parameter exponential probability density function is applied to represent the probabilistic features of long-term precipitation time series and model urban stormwater runoff. Finally, probability density functions of water quality control basin overflow are derived under two extreme intial conditions. The 31-year continuous precipitation time series recorded in Busan are analyzed to show that the 3-parameter mixed exponential probability density function gives better resolution.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4179-4188
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• 2021

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R²), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

• Earthquakes and Structures
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• v.13 no.3
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• pp.221-230
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• 2017

One of the important phases of probabilistic performance-based methodology is establishing appropriate probabilistic seismic demand models (PSDMs). These demand models relate ground motion intensity measures (IMs) to demand measures (DMs). The objective of this paper is selection of the optimal IMs in probabilistic seismic demand analysis (PSDA) of the RC high-rise buildings. In selection process features such as: efficiency, practically, proficiency and sufficiency are considered. RC high-rise buildings with core wall structural system are selected as a case study building class with the three characteristic heights: 20-storey, 30-storey and 40-storey. In order to determine the most optimal IMs, 720 nonlinear time-history analyses are conducted for 60 ground motion records with a wide range of magnitudes and distances to source, and for various soil types, thus taking into account uncertainties during ground motion selection. The non-linear 3D models of the case study buildings are constructed. A detailed regression analysis and statistical processing of results are performed and appropriate PSDMs for the RC high-rise building are derived. Analyzing a large number of results it are adopted conclusions on the optimality of individual ground motion IMs for the RC high-rise building.