• Title/Summary/Keyword: Probabilistic Models

Search Result 462, Processing Time 0.023 seconds

Seismic probabilistic risk assessment of weir structures considering the earthquake hazard in the Korean Peninsula

  • Alam, Jahangir;Kim, Dookie;Choi, Byounghan
    • Earthquakes and Structures
    • /
    • v.13 no.4
    • /
    • pp.421-427
    • /
    • 2017
  • Seismic safety evaluation of weir structure is significant considering the catastrophic economical consequence of operational disruption. In recent years, the seismic probabilistic risk assessment (SPRA) has been issued as a key area of research for the hydraulic system to mitigate and manage the risk. The aim of this paper is to assess the seismic probabilistic risk of weir structures employing the seismic hazard and the structural fragility in Korea. At the first stage, probabilistic seismic hazard analysis (PSHA) approach is performed to extract the hazard curve at the weir site using the seismic and geological data. Thereafter, the seismic fragility that defines the probability of structural collapse is evaluated by using the incremental dynamic analysis (IDA) method in accordance with the four different design limit states as failure identification criteria. Consequently, by combining the seismic hazard and fragility results, the seismic risk curves are developed that contain helpful information for risk management of hydraulic structures. The tensile stress of the mass concrete is found to be more vulnerable than other design criteria. The hazard deaggregation illustrates that moderate size and far source earthquakes are the most likely scenario for the site. In addition, the annual loss curves for two different hazard source models corresponding to design limit states are extracted.

Probabilistic analysis of RC beams according to IS456:2000 in limit state of collapse

  • Kulkarni, Anadee M.;Dattaa, Debarati
    • Structural Engineering and Mechanics
    • /
    • v.71 no.2
    • /
    • pp.165-173
    • /
    • 2019
  • This paper investigates the probability of failure of reinforced concrete beams for limit state of collapse for flexure and shear. The influence of randomness of the variables on the failure probability is also examined. The Indian standard code for plain and reinforced concrete IS456:2000 is used for the design of beams. Probabilistic models are developed for flexure and shear according to IS456:2000. The loads considered acting on the beam are live load and dead load only. Random variables associated with the limit state equation such as grade of concrete, grade of steel, live load and dead load are identified. Probability of failure is evaluated based on the limit state equation using First Order Reliability Method (FORM). Importance of the random variables on the limit state equations are observed and the variables are accordingly reduced. The effect of the reduced parameters is checked on the probability of failure. The results show the role of each parameter on the design of beam. Thus, the Indian standard guidelines for plain and reinforced concrete IS456:2000 is investigated with the probabilistic and risk-based analysis and design for a simple beam. The results obtained are also compared with the literature and accordingly some suggestions are made.

Case studies on the probabilistic characteristics of ultimate strength of stiffened panels with uniform and non-uniform localized corrosion subjected to uniaxial and biaxial thrust

  • Cui, Jinju;Wang, Deyu;Ma, Ning
    • International Journal of Naval Architecture and Ocean Engineering
    • /
    • v.11 no.1
    • /
    • pp.97-118
    • /
    • 2019
  • Based on Nonlinear Finite Element Analysis (NFEA), this paper focuses on the bi-axial ultimate strength of typical bottom structures under corrosion. On one hand, uniform and not simultaneous corrosion across different structures is introduced, and surrogate models by Gaussian Process (GP) are built for both longitudinal and transverse cases individually, and corresponding probabilistic characteristics are investigated; meanwhile, corrosion effects on interaction between bi-axial stresses at ultimate state are studied. On the other hand, non-uniform localized pitting corrosion of normally distributed circular shapes is introduced, and different pitting corrosion densities are considered; structural bi-axial ultimate strengths under pitting corrosion are studied, and the results are compared with that from equivalent uniform corrosion; the probabilistic characteristics of structural ultimate strength in life cycle are studied; finally, the ultimate strength under randomly distributed pitting corrosion is compared with results from normally distributed pitting and uniform corrosion under various boundary conditions.

Probability subtraction method for accurate quantification of seismic multi-unit probabilistic safety assessment

  • Park, Seong Kyu;Jung, Woo Sik
    • Nuclear Engineering and Technology
    • /
    • v.53 no.4
    • /
    • pp.1146-1156
    • /
    • 2021
  • Single-unit probabilistic safety assessment (SUPSA) has complex Boolean logic equations for accident sequences. Multi-unit probabilistic safety assessment (MUPSA) model is developed by revising and combining SUPSA models in order to reflect plant state combinations (PSCs). These PSCs represent combinations of core damage and non-core damage states of nuclear power plants (NPPs). Since all these Boolean logic equations have complemented gates (not gates), it is not easy to generate exact Boolean solutions. Delete-term approximation method (DTAM) has been widely applied for generating approximate minimal cut sets (MCSs) from the complex Boolean logic equations with complemented gates. By applying DTAM, approximate conditional core damage probability (CCDP) has been calculated in SUPSA and MUPSA. It was found that CCDP calculated by DTAM was overestimated when complemented gates have non-rare events. Especially, the CCDP overestimation drastically increases if seismic SUPSA or MUPSA has complemented gates with many non-rare events. The objective of this study is to suggest a new quantification method named probability subtraction method (PSM) that replaces DTAM. The PSM calculates accurate CCDP even when SUPSA or MUPSA has complemented gates with many non-rare events. In this paper, the PSM is explained, and the accuracy of the PSM is validated by its applications to a few MUPSAs.

A Study on the Computational Model of Word Sense Disambiguation, based on Corpora and Experiments on Native Speaker's Intuition (직관 실험 및 코퍼스를 바탕으로 한 의미 중의성 해소 계산 모형 연구)

  • Kim, Dong-Sung;Choe, Jae-Woong
    • Korean Journal of Cognitive Science
    • /
    • v.17 no.4
    • /
    • pp.303-321
    • /
    • 2006
  • According to Harris'(1966) distributional hypothesis, understanding the meaning of a word is thought to be dependent on its context. Under this hypothesis about human language ability, this paper proposes a computational model for native speaker's language processing mechanism concerning word sense disambiguation, based on two sets of experiments. Among the three computational models discussed in this paper, namely, the logic model, the probabilistic model, and the probabilistic inference model, the experiment shows that the logic model is first applied fer semantic disambiguation of the key word. Nexr, if the logic model fails to apply, then the probabilistic model becomes most relevant. The three models were also compared with the test results in terms of Pearson correlation coefficient value. It turns out that the logic model best explains the human decision behaviour on the ambiguous words, and the probabilistic inference model tomes next. The experiment consists of two pans; one involves 30 sentences extracted from 1 million graphic-word corpus, and the result shows the agreement rate anong native speakers is at 98% in terms of word sense disambiguation. The other pm of the experiment, which was designed to exclude the logic model effect, is composed of 50 cleft sentences.

  • PDF

On an Optimal Artillery Deployment Plan (포대의 적정배치 방안)

  • Yun, Yun-Sang;Kim, Seong-Sik
    • Journal of the military operations research society of Korea
    • /
    • v.8 no.2
    • /
    • pp.17-30
    • /
    • 1982
  • This paper offers an optimal artillery deployment scheme for the defending unit when two forces are confronted at a military front line. When proposed gun sites, types and number of guns as well as targets are given, the solutions of the two models in this paper direct each (unit of) guns to a certain location. The aim of the models is to maximize the number of guns which can hit important targets. Unlike widely used target assignment models, these models are formulated using the set covering problem concept. These models do not contain probabilities and time. Thus they are simple as models, easy in implementation, and yield tractable solutions. The dynamic and probabilistic feature of battle situations is implicitly reflected on the models. The first model is for the case that enemies' approaching route is clearly predictable, while the second model is for the unpredictable approaching route case.

  • PDF

Comprehensive Cumulative Shock Common Cause Failure Models and Assessment of System Reliability (포괄적 누적 충격 공통원인고장 모형 및 시스템 신뢰도 평가)

  • Lim, Tae-Jin
    • Journal of Korean Society for Quality Management
    • /
    • v.39 no.2
    • /
    • pp.320-328
    • /
    • 2011
  • This research proposes comprehensive models for analyzing common cause failures (CCF) due to cumulative shocks and to assess system reliability under the CCF. The proposed cumulative shock models are based on the binomial failure rate (BFR) model. Six kinds of models are proposed so as to explain diverse cumulative shock phenomena. The models are composed of the initial failure probability, shape parameter, and the total shock number. Some parameters of the proposed models can not be explicitly estimated, so we adopt the Expectation-maximization (EM) algorithm in order to obtain the maximum likelihood estimator (MLE) for the parameters. By estimating the parameters for the cumulative shock models, the system reliability with CCF can be assessed sequentially according to the number of cumulative shocks. The result can be utilizes in dynamic probabilistic safety assessment (PSA), aging studies, or risk management for nuclear power plants. Replacement or maintenance policies can also be developed based on the proposed model.

Simplification of the Plant Models in PSA

  • Kim, Myung-Ro;Lee, Beom-Su;Kang, Sun-Koo
    • Proceedings of the Korean Nuclear Society Conference
    • /
    • 1996.05b
    • /
    • pp.499-504
    • /
    • 1996
  • Current Probabilistic Safety Assessment (PSA) techniques are not usually utilized for day-to-day applications in nuclear power plants. The major reason for this anomaly is the complexity of plant models developed for PSA studies and the multitude of resulting fault trees. This impediment can be overcome by the use of simplified plant models. However, oversimplified models usually result in loss of valuable information and therefore. simplification approaches have to be used judiciously in order to achieve accurate and meaningful results. For this reason. development of an appropriate simplification approach must be performed using extreme caution followed with results verification in sequence as well as system levels. If there are no significant differences between the simplified and the original models, the simplified model can be efficiently used in the application of the PSA. This paper presents a methodology for how to develop a suitable simplification technique and the results of its verification for sample systems and sequences. The results show that the utilization of simplified plant models will significantly reduce the number of fault trees with no significant loss of accuracy.

  • PDF

A GPD-BASED DISCRIMINATIVE TRAINING ALGORITHM FOR PREDICTIVE NEURAL NETWORK MODELS

  • Na, Kyung-Min;Rheem, Jae-Yeol;Ann, Sou-Guil
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • 1994.06a
    • /
    • pp.997-1002
    • /
    • 1994
  • Predictive neural network models are powerful speech recognition models based on a nonlinear pattern prediction. Those models can effectively normalize the temporal and spatial variability of speech signals. But those models suffer from poor discrimination between acoustically similar words. In this paper, we propose a discriminative training algorithm for predictive neural network models based on a generalized probabilistic descent (GPD) algorithm and minimum classification error formulation (MCEF). The Evaluation of our training algorithm on ten Korean digits shows its effectiveness by 40% reduction of recognition error.

  • PDF

A Simultaneous Design of TSK - Linguistic Fuzzy Models with Uncertain Fuzzy Output

  • Kwak, Keun-Chang;Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 2005.06a
    • /
    • pp.427-432
    • /
    • 2005
  • This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

  • PDF