• 한국지진공학회논문집
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• 제23권6호
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• pp.301-309
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• 2019

A methodology to assess seismic fragility of a nuclear power plant (NPP) using a conditional mean spectrum is proposed as an alternative to using a uniform hazard response spectrum. Rather than the single-scenario conditional mean spectrum, which is the conventional conditional mean spectrum based on a single scenario, a multi-scenario conditional mean spectrum is proposed for the case in which no single scenario is dominant. The multi-scenario conditional mean spectrum is defined as the weighted average of different conditional mean spectra, each one of which corresponds to an individual scenario. The weighting factors for scenarios are obtained from a deaggregation of seismic hazards. As a validation example, a seismic fragility assessment of an NPP containment structure is performed using a uniform hazard response spectrum and different single-scenario conditional mean spectra and multi-scenario conditional mean spectra. In the example, the number of scenarios primarily influences the median capacity of the evaluated structure. Meanwhile, the control frequency, a key parameter of a conditional mean spectrum, plays an important role in reducing logarithmic standard deviation of the corresponding fragility curves and corresponding high confidence of low probability of failure (HCLPF) capacity.

• Earthquakes and Structures
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• 제7권2호
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• pp.141-157
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• 2014

The Conditional Mean Spectrum represents a powerful link between the seismic hazard information and the selection of strong ground motion records at a particular site. The scope of the paper is to apply for the city of Bucharest for the first time the method to obtain the Conditional Mean Spectrum (CMS) presented by Baker (2011) and to select, on the basis of the CMS, a suite of strong ground motions for performing elastic and inelastic dynamic analyses of buildings and structures with fundamental periods of vibration in the vicinity of 1.0 s. The major seismic hazard for Bucharest and for most of Southern and Eastern Romania is dominated by the Vrancea subcrustal seismic source. The ground motion prediction equation developed for subduction-type earthquakes and soil conditions by Youngs et al. (1997) is used for the computation of the Uniform Hazard Spectrum (UHS) and the CMS. The disaggregation of seismic hazard is then performed in order to determine the mean causal values of magnitude and source-to-site distance for a particular spectral ordinate (for a spectral period T = 1.0 s in this study). The spectral period of 1.0 s is considered to be representative for the new stock of residential and office reinforced concrete (RC) buildings in Bucharest. The differences between the Uniform Hazard Spectrum (UHS) and the Conditional Mean Spectrum (CMS) are discussed taking into account the scarcity of ground motions recorded in the region of Bucharest and the frequency content characteristics of the recorded data. Moreover, a record selection based on the criteria proposed by Baker and Cornell (2006) and Baker (2011) is performed using a dataset consisting of strong ground motions recorded during seven Vrancea seismic events.

• Journal of the Korean Statistical Society
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• 제29권1호
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• pp.1-8
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• 2000

A spectrum minimizing the frequency-domain Kullback-Leibler information number has been proposed and used to modify a spectrum estimate. Some numerical examples have illustrated the KL spectrum estimate is superior to the initial estimate, i.e., the autocovariances obtained by the inverse Fourier transformation of the KL spectrum estimate are closer to the sample autocovariances of the given observations than those of the initial spectrum estimate. Also, it has been shown that a Gaussian autoregressive process associated with the KL spectrum is the closest in the timedomain Kullback-Leibler sense to a Gaussian white noise process subject to given autocovariance constraints. In this paper a corresponding conditional probability theorem is presented, which gives another rationale to the KL spectrum.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.20-33
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• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1872-1879
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• 2016

The techniques to recycle and reuse plastics attract public attention. These public attraction and needs result in improving the recycling technique. However, the identification technique for black plastic wastes still have big problem that the spectrum extracted from near infrared radiation spectroscopy is not clear and is contaminated by noise. To overcome this problem, we apply Raman spectroscopy to extract a clear spectrum of plastic material. In addition, to improve the classification ability of fuzzy Radial Basis Function Neural Networks, we apply supervised learning based clustering method instead of unsupervised clustering method. The conditional fuzzy C-Means clustering method, which is a kind of supervised learning based clustering algorithms, is used to determine the location of radial basis functions. The conditional fuzzy C-Means clustering analyzes the data distribution over input space under the supervision of auxiliary information. The auxiliary information is defined by using k Nearest Neighbor approach.

• 한국지진공학회논문집
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• 제25권4호
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• pp.179-189
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• 2021

Conditional spectra (CS) are applied to the seismic fragility assessment of a nuclear power plant (NPP) containment building for comparison with a relevant conventional uniform hazard response spectrum (UHRS). Three different control frequencies are considered in developing conditional spectra. The contribution of diverse magnitudes and epicentral distances is identified from deaggregation for the UHRS at a control frequency and incorporated into the conditional spectra. A total of 30 ground motion records are selected and scaled to simulate the probability distribution of each conditional spectra, respectively. A set of lumped mass stick models for the containment building are built considering nonlinear bending and shear deformation and uncertainty in modeling parameters using the Latin hypercube sampling technique. Incremental dynamic analysis is conducted for different seismic input models in order to estimate seismic fragility functions. The seismic fragility functions and high confidence of low probability of failure (HCLPF) are calculated for different seismic input models and analyzed comparatively.

• 대한기계학회논문집
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• 제12권5호
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• pp.1175-1188
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• 1988

본 연구에서는 조건와류를 추출하려면 우선 속도상관관계를 알아야 하는데, 이를 위하여 실험적 데이타와 이론적 모델을 모두 적용하였다. 전자는 Van Atta와 Chen의 그리드 난류에서의 등방성에 가까운 속도상관관계 데이터를 취하여 이용하였으 며, 후자는 Driscoll과 Kennedy의 난류에너지 스펙트럼 모델을 해석하여 적용하였다. 이 이론적 모델은 레이놀즈수를 변화시킬 수 있는 장점이 있으며, 특히 벽면근처에서 의 와동구조해석을 위해서는 레이놀즈수가 작은 조건와류가 필요하다. 조건와류의 반지모양의 와동은 이방성분포인 평균전단유동에 중첩되어 전체 와동장을 구성하는데, 난류유동의 vortex stretching과정에서 중요한 역할을 하는 머리핀 와동(hairpin vor- tex)과 비슷한 구조를 이 전체 와동에서 구할 수 있다. 이는 조건와류의 와동장의 크기와 평균전단에 의한 평균 와동장의 상호크기에 따라 결정되는데, 실제 난류유동장 에서 난류전달과 레이놀즈 응력과 밀접한 관계가 있다.

• Structural Engineering and Mechanics
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• 제5권6호
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• pp.839-851
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• 1997

Closed-form solutions are analytically derived for stochastic properties of earthquake ground motion fields, which are conditioned by an observed time series at certain observation sites and are characterized by spectra with uncertainties. The theoretical framework presented here can estimate not only the expectations of such simulated earthquake ground motions, but also the prediction errors which offer important information for the field of engineering. Before these derivations are made, the theory of conditional random fields is summarized for convenience in this study. Furthermore, a method for stochastic interpolation of power spectra is explained.

• 한국지진공학회논문집
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• 제20권1호
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• pp.55-62
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• 2016

It is important to select an accurate set of ground motions when conducting linear and nonlinear response history analyses of structures. This study proposes a method for selecting ground motions from a ground motion library with response spectra that match the target response spectrum mean, variance and correlation structures. This study also has addressed the determination of an appropriate value for the weight factor of a correlation structure. The proposed method is conceptually simple and straightforward, and does not involve a simulation algorithm. In this method, a desired number of ground motions are sequentially selected from first to last. The proposed method can be also used for selecting ground motions with response spectra that match the conditional spectrum. The accuracy and efficiency of the proposed procedure are verified with numerical examples.

• 대한전자공학회논문지TC
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• 제48권3호
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• pp.50-59
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• 2011

본 논문은 주파수 영역에서 과거와 현재에 센싱된 결과들의 관계를 이용한 스펙트럼 센싱기법을 제안하였다. 기존에 제안된 대부분의 스펙트럼 센싱기법은 해당 시간에 센싱된 우선사용자의 신호만을 다루고 있다. 해당 시간 이전의 우선사용자의 상태는 조건부확률을 사용하여 검출기의 신뢰성을 증가시킬 수 있다. 따라서, 본 논문은 이전 시간과 해당 시간의 스펙트럼 센싱 결과를 사용하는 cross entropy 기반의 스펙트럼 센싱기법을 제안하며 이를 통해 우선사용자 신호 검출 성능을 향상시키고 잡음에 강인한 성능을 가질 수 있다. 이전 시간에 검출된 신호가 잡음인 경우 cross entropy 기반의 스펙트럼 센싱 성능 감소는 기존의 entropy 기반의 센싱기법과 동일하게 된다. 이러한 문제를 해결하기 위해 본 논문에서는 보다 향상된 cross entropy 센싱기법을 제안하였다. 본 논문은 시뮬레이션을 통해 가장 최근에 제안된 주파수 영역에서의 entropy 기반 스펙트럼 센싱기법 보다 제안된 방법이 더 나은 성능을 보이는 것을 보였다.