• 제목/요약/키워드: probabilistic characteristics

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CFRP 적층복합재료의 층간분리 평가 (An Analysis for Delaminations in CFRP Laminates)

  • 강기원;김정규
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2000년도 춘계학술대회논문집A
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    • pp.132-137
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    • 2000
  • In this study, model for arrest toughness is proposed in consideration of fracture behavior of composite materials. Also, the probabilistic model is proposed to describe the variability of arrest toughness due to the nonhomogeneity of material. For these models. experiments were conducted on the Carbon/Epoxy composite plates with various thickness using the impact hammer. The elastic work fatter used in J-Integral is applicable to the evaluation of energy release rate. The fracture behavior call be described by crack arrest concept and the arrest toughness is independent of the delamination size. Additionally, a probabilistic characteristics of arrest toughness is well described by the Weibull distribution function. An increasing of thickness raises a variation of arrest toughness.

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확률 신경망에 의한 해저 저질의 식별 (Classifying Seafloor Sediments Using a Probabilistic Neural Network)

  • 이대재
    • 한국수산과학회지
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    • 제51권3호
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    • pp.321-327
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    • 2018
  • To classify seafloor sediments using a probabilistic neural network (PNN), the frequency-dependent characteristics of broadband acoustic scattering, which make it possible to qualitatively categorize seabed type, were collected from three different geographical areas in Korea. The echo data samples from three types of seafloor sediment were measured using a chirp sonar system operating over a frequency range of 20-220 kHz. The spectrum amplitudes for frequency responses of 35-75 kHz were fed into the PNN as input feature parameters. The PNN algorithm could successfully identify three seabed types: mud, mud/shell and concrete sediments. The percentage probabilities of the three seabed types being correctly classified were 86% for mud, 66% for mud/shell and 72% for concrete sediment.

Cross-Validation Probabilistic Neural Network Based Face Identification

  • Lotfi, Abdelhadi;Benyettou, Abdelkader
    • Journal of Information Processing Systems
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    • 제14권5호
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    • pp.1075-1086
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    • 2018
  • In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer's size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

각 지역별 확률론적 신뢰도 평가에 관한 연구 (A Study on Nodal Probabilistic Reliability Evaluation at Load Points)

  • 김홍식;문승필;최재석;차준민
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 A
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    • pp.206-209
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    • 2001
  • This paper illustrates a new method for reliability evaluation at load points in a composite power system. The algorithm includes uncertainties of generators and transmission lines as well as main transformers at substations. The CMELDC based on the new effective load model at HLII has been developed also. The CMELDC can be obtain from convolution integral processing of the outage capacity probabilistic distribution function of the fictitious generator and the original load duration curve given at the load point. The CMELDC based on the new model at HLII will extend the application areas of nodal probabilistic production cost simulation, outage cost assessment and reliability evaluation etc. at load points. The characteristics and effectiveness of this new model are illustrated by a case study of a small test system.

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ISSUES IN PROBABILISTIC SEISMIC HAZARD ANALYSIS FOR NUCLEAR FACILITIES IN THE US

  • Mcguire, Robin K.
    • Nuclear Engineering and Technology
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    • 제41권10호
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    • pp.1235-1242
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    • 2009
  • Probabilistic seismic hazard analysis (PSHA) is routinely conducted in the US for nuclear plants, for the determination of appropriate seismic design levels. These analyses incorporate uncertainties in earthquake characteristics in stable continental regions (where direct observations of large earthquakes are rare), in estimates of rock motions, in site effects on strong shaking, and in the damage potential of seismic shaking for engineered facilities. Performance goals related to the inelastic deformation of individual components, and related to overall seismic core damage frequency, are used to determine design levels. PSHA has the ability to quantify and document the important uncertainties that affect seismic design levels, and future work can be guided toward reducing those uncertainties.

케이슨 방파제의 확률론적 지진재해도 평가 (Probabilistic Seismic Hazard Analysis of Caisson-Type Breakwaters)

  • 김상훈;김두기
    • 한국해양공학회지
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    • 제19권1호
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    • pp.26-32
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    • 2005
  • Recent earthquakes, measuring over a magnitude of 5.0, on the eastern coast of Korea, have aroused interest in earthquake analyses and the seismic design of caisson-type breakwaters. Most earthquake analysis methods, such as equivalent static analysis, response spectrum analysis, nonlinear analysis, and capacity analysis, are deterministic and have been used for seismic design and performance evaluation of coastal structures. However, deterministic methods are difficult for reflecting on one of the most important characteristics of earthquakes, i.e. the uncertainty of earthquakes. This paper presents results of probabilistic seismic hazard assessment(PSHA) of an actual caisson-type breakwater, considering uncertainties of earthquake occurrences and soil properties. First, the seismic vulnerability of a structure and the seismic hazard of the site are evaluated, using earthquake sets and a seismic hazard map; then, the seismic risk of the structure is assessed.

국내 연구용원자로 PSA 수행을 위한 초기사건 선정 및 빈도 분석 (Initiating Event Selection and Analysis for Probabilistic Safety Assessment of Korea Research Reactor)

  • 이윤환
    • 한국안전학회지
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    • 제36권2호
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    • pp.101-110
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    • 2021
  • This paper presents the results of an initiating event analysis as part of a Level 1 probabilistic safety assessment (PSA) for at-power internal events for the Korea Research Reactor (KRR). The PSA methodology is widely used to quantitatively assess the safety of research reactors (RRs) in the domestic nuclear industry. Initiating event frequencies are required to conduct a PSA, and they considerably affect the PSA results. Because there is no domestic database for domestic trip events, the safety of RRs is usually assessed using foreign databases. In this paper, operating experience data from the KRR for trip events were collected and analyzed in order to determine the frequency of specific initiating events. These frequencies were calculated using two approaches according to the event characteristics and data availability: (1) based on KRR operating experience or (2) using generic data.

Probabilistic analysis of structural pounding considering soil-structure interaction

  • Naeej, Mojtaba;Amiri, Javad Vaseghi
    • Earthquakes and Structures
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    • 제22권3호
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    • pp.289-304
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    • 2022
  • During strong ground motions, adjacent structures with insufficient separation distances collide with each other causing considerable architectural and structural damage or collapse of the whole structure. Generally, existing design procedures for determining the separation distance between adjacent buildings subjected to structural pounding are based on approximations of the buildings' peak relative displacement. These procedures are based on unknown safety levels. This paper attempts to evaluate the influence of foundation flexibility on the structural seismic response by considering the variability in the system and uncertainties in the ground motion characteristics through comprehensive numerical simulations. Actually, the aim of this study is to evaluate the influence of foundation flexibility on probabilistic evaluation of structural pounding. A Hertz-damp pounding force model has been considered in order to effectively capture impact forces during collisions. In total, 5.25 million time-history analyses were performed over the adopted models using an ensemble of 25 ground motions as seismic input within OpenSees software. The results of the study indicate that the soil-structure interaction significantly influences the pounding-involved responses of adjacent structures during earthquakes and generally increases the pounding probability.

Probabilistic seismic risk assessment of a masonry tower considering local site effects

  • Ozden Saygili
    • Earthquakes and Structures
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    • 제26권3호
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    • pp.191-201
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    • 2024
  • A comprehensive probabilistic seismic hazard analysis was carried out in Istanbul to examine the seismotectonic features of the region. The results showed that earthquakes can trigger one another, resulting in the grouping of earthquakes in both time and space. The hazard analysis utilized the Poisson model and a conventional integration technique to generate the hazard curve, which shows the likelihood of ground motion surpassing specific values over a given period. Additionally, the study evaluated the impact of seismic hazard on the structural integrity of an existing masonry tower by simulating its seismic response under different ground motion intensities. The study's results emphasize the importance of considering the seismotectonic characteristics of an area when assessing seismic hazard and the structural performance of buildings in seismic-prone regions.

Closed-form fragility analysis of the steel moment resisting frames

  • Kia, M.;Banazadeh, M.
    • Steel and Composite Structures
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    • 제21권1호
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    • pp.93-107
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    • 2016
  • Seismic fragility analysis is a probabilistic decision-making framework which is widely implemented for evaluating vulnerability of a building under earthquake loading. It requires ingredient named probabilistic model and commonly developed using statistics requiring collecting data in large quantities. Preparation of such a data-base is often costly and time-consuming. Therefore, in this paper, by developing generic seismic drift demand model for regular-multi-story steel moment resisting frames is tried to present a novel application of the probabilistic decision-making analysis to practical purposes. To this end, a demand model which is a linear function of intensity measure in logarithmic space is developed to predict overall maximum inter-story drift. Next, the model is coupled with a set of regression-based equations which are capable of directly estimating unknown statistical characteristics of the model parameters.To explicitly address uncertainties arise from randomness and lack of knowledge, the Bayesian regression inference is employed, when these relations are developed. The developed demand model is then employed in a Seismic Fragility Analysis (SFA) for two designed building. The accuracy of the results is also assessed by comparison with the results directly obtained from Incremental Dynamic analysis.