• Title/Summary/Keyword: probabilistic models

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Analysis of Consolidation considering Uncertainties of Geotechnical Parameters and Reliability method (지반특성의 불확실성과 신뢰성 기법을 고려한 압밀해석)

  • Lee, Kyu-Hwan
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.11 no.4
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    • pp.138-146
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    • 2007
  • Geotechnical performance at the soft ground is strongly dependent on the properties of the soil beneath and adjacent to the structure of interest. These soil properties can be described using deterministic and/or probabilistic models. Deterministic models typically use a single discrete descriptor for the parameter of interest. Probabilistic models describe parameters by using discrete statistical descriptors or probability distribution density functions. The consolidation process depends on several uncertain parameters including the coefficients of consolidation and coefficients of permeability in vertical and horizontal directions. The implication of this uncertain parameter in the design of prefabricated vertical drains for soil improvement is discussed. A sensitivity analysis of the degree of consolidation and calculation of settlements to these uncertain parameters is presented for clayey deposits.

Quantitative microbial risk assessment of Campylobacter jejuni in jerky in Korea

  • Ha, Jimyeong;Lee, Heeyoung;Kim, Sejeong;Lee, Jeeyeon;Lee, Soomin;Choi, Yukyung;Oh, Hyemin;Yoon, Yohan
    • Asian-Australasian Journal of Animal Sciences
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    • v.32 no.2
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    • pp.274-281
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    • 2019
  • Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

System dynamics simulation of the thermal dynamic processes in nuclear power plants

  • El-Sefy, Mohamed;Ezzeldin, Mohamed;El-Dakhakhni, Wael;Wiebe, Lydell;Nagasaki, Shinya
    • Nuclear Engineering and Technology
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    • v.51 no.6
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    • pp.1540-1553
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    • 2019
  • A nuclear power plant (NPP) is a highly complex system-of-systems as manifested through its internal systems interdependence. The negative impact of such interdependence was demonstrated through the 2011 Fukushima Daiichi nuclear disaster. As such, there is a critical need for new strategies to overcome the limitations of current risk assessment techniques (e.g. the use of static event and fault tree schemes), particularly through simulation of the nonlinear dynamic feedback mechanisms between the different NPP systems/components. As the first and key step towards developing an integrated NPP dynamic probabilistic risk assessment platform that can account for such feedback mechanisms, the current study adopts a system dynamics simulation approach to model the thermal dynamic processes in: the reactor core; the secondary coolant system; and the pressurized water reactor. The reactor core and secondary coolant system parameters used to develop system dynamics models are based on those of the Palo Verde Nuclear Generating Station. These three system dynamics models are subsequently validated, using results from published work, under different system perturbations including the change in reactivity, the steam valve coefficient, the primary coolant flow, and others. Moving forward, the developed system dynamics models can be integrated with other interacting processes within a NPP to form the basis of a dynamic system-level (systemic) risk assessment tool.

Seismic vulnerability macrozonation map of SMRFs located in Tehran via reliability framework

  • Amini, Ali;Kia, Mehdi;Bayat, Mahmoud
    • Structural Engineering and Mechanics
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    • v.78 no.3
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    • pp.351-368
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    • 2021
  • This paper, by applying a reliability-based framework, develops seismic vulnerability macrozonation maps for Tehran, the capital and one of the most earthquake-vulnerable city of Iran. Seismic performance assessment of 3-, 4- and 5-story steel moment resisting frames (SMRFs), designed according to ASCE/SEI 41-17 and Iranian Code of Practice for Seismic Resistant Design of Buildings (2800 Standard), is investigated in terms of overall maximum inter-story drift ratio (MIDR) and unit repair cost ratio which is hereafter known as "damage ratio". To this end, Tehran city is first meshed into a network of 66 points to numerically locate low- to mid-rise SMRFs. Active faults around Tehran are next modeled explicitly. Two different combination of faults, based on available seismological data, are then developed to explore the impact of choosing a proper seismic scenario. In addition, soil effect is exclusively addressed. After building analytical models, reliability methods in combination with structure-specific probabilistic models are applied to predict demand and damage ratio of structures in a cost-effective paradigm. Due to capability of proposed methodology incorporating both aleatory and epistemic uncertainties explicitly, this framework which is centered on the regional demand and damage ratio estimation via structure-specific characteristics can efficiently pave the way for decision makers to find the most vulnerable area in a regional scale. This technical basis can also be adapted to any other structures which the demand and/or damage ratio prediction models are developed.

Robust Optimization of Automotive Seat by Using Constraint Response Surface Model (제한조건 반응표면모델에 의한 자동차 시트의 강건최적설계)

  • 이태희;이광기;구자겸;이광순
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.04b
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    • pp.168-173
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    • 2000
  • Design of experiments is utilized for exploring the design space and for building response surface models in order to facilitate the effective solution of multi-objective optimization problems. Response surface models provide an efficient means to rapidly model the trade-off among many conflicting goals. In robust design, it is important not only to achieve robust design objectives but also to maintain the robustness of design feasibility under the effects of variations, called uncertainties. However, the evaluation of feasibility robustness often needs a computationally intensive process. To reduce the computational burden associated with the probabilistic feasibility evaluation, the first-order Taylor series expansions are used to derive individual mean and variance of constraints. For robust design applications, these constraint response surface models are used efficiently and effectively to calculate variances of constraints due to uncertainties. Robust optimization of automotive seat is used to illustrate the approach.

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Development of Probability-Based LRFD Formats for R.C Structure (신뢰성 이론에 기초한 철근콘크리트 건축구조물의 하중 및 저하계수 설계식에 관한 연구)

  • 김상효;조형근;배규웅
    • Magazine of the Korea Concrete Institute
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    • v.4 no.4
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    • pp.123-133
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    • 1992
  • 확률이론을 이용한 구조물 신뢰성에 관한 연구가 최근 급속히 발달함과 동시에 구조물의 저하능력과 작용하중들의 확률적 특성들에 대한 인식이 제고됨에 따라 여러나라에서 확률이론에 근거한 설계규준이 개발되고 있다. 작용하중이나 구조저항력의 확률적 특성을 보이고 있기 때문에 외국의 설계규준을 직접 도입하는 것은 여러 가지 문제점이 있으며, 따라서 국내현실에 적합한 설계규준에 대한 연구가 필요하다. 본 연구에서는 국내 철근콘크리트 구조물의 합리적인 설계규준을 제시하기 위하여 국내에서 수집\ulcorner분석된 구조부재강도 및 작용하중의 확률적 모형을 이용하여 현행 설계규준에 내포된 신뢰도를 검정하고 나아가 최적하중계수를 분석하였다.

Variable Selection in Linear Random Effects Models for Normal Data

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.27 no.4
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    • pp.407-420
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    • 1998
  • This paper is concerned with selecting covariates to be included in building linear random effects models designed to analyze clustered response normal data. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting premising subsets of covariates. The approach reformulates the linear random effects model in a hierarchical normal and point mass mixture model by introducing a set of latent variables that will be used to identify subset choices. The hierarchical model is flexible to easily accommodate sign constraints in the number of regression coefficients. Utilizing Gibbs sampler, the appropriate posterior probability of each subset of covariates is obtained. Thus, In this procedure, the most promising subset of covariates can be identified as that with highest posterior probability. The procedure is illustrated through a simulation study.

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A Multi-target Tracking Algorithm for Application to Adaptive Cruise Control

  • Moon Il-ki;Yi Kyongsu;Cavency Derek;Hedrick J. Karl
    • Journal of Mechanical Science and Technology
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    • v.19 no.9
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    • pp.1742-1752
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    • 2005
  • This paper presents a Multiple Target Tracking (MTT) Adaptive Cruise Control (ACC) system which consists of three parts; a multi-model-based multi-target state estimator, a primary vehicular target determination algorithm, and a single-target adaptive cruise control algorithm. Three motion models, which are validated using simulated and experimental data, are adopted to distinguish large lateral motions from longitudinally excited motions. The improvement in the state estimation performance when using three models is verified in target tracking simulations. However, the performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. The MTT-ACC system is tested under lane changing situations to examine how much the system performance is improved when multiple models are incorporated. Simulation results show system response that is more realistic and reflective of actual human driving behavior.

Safety Analysis on the Tritium Release Accidents

  • Yang, Hee joong
    • Journal of Korean Society for Quality Management
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    • v.19 no.2
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    • pp.96-107
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    • 1991
  • At the design stage of a plant, the plausible causes and pathways of release of hazardous materials are not clearly known. Thus there exist large amount of uncertainties on the consequences resulting from the operation of a fusion plant. In order to better handle such uncertain circumstances, we utilize the Probabilistic Risk Assessment(PRA) for the safety analyses on fusion power plant. In this paper, we concentrate on the tritium release accident. We develop a simple model that describes the process and flow of tritium, by which we figure out the locations of tritium inventory and their vulnerability. We construct event tree models that lead to various levels of tritium release from abnormal initiating events. Branch parameters on the event tree are assessed from the fault tree analysis. Based on the event tree models we construct influence diagram models which are more useful for the parameter updating and analysis. We briefly discuss the parameter updating scheme, and finally develop the methodology to obtain the predictive distribution of consequences resulting from the operating a fusion power plant. We also discuss the way to utilize the results of testing on sub-systems to reduce the uncertain ties on over all system.

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Comparative analysis among deterministic and stochastic collision damage models for oil tanker and bulk carrier reliability

  • Campanile, A.;Piscopo, V.;Scamardella, A.
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.10 no.1
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    • pp.21-36
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    • 2018
  • The incidence of collision damage models on oil tanker and bulk carrier reliability is investigated considering the IACS deterministic model against GOALDS/IMO database statistics for collision events, substantiating the probabilistic model. Statistical properties of hull girder residual strength are determined by Monte Carlo simulation, based on random generation of damage dimensions and a modified form of incremental-iterative method, to account for neutral axis rotation and equilibrium of horizontal bending moment, due to cross-section asymmetry after collision events. Reliability analysis is performed, to investigate the incidence of collision penetration depth and height statistical properties on hull girder sagging/hogging failure probabilities. Besides, the incidence of corrosion on hull girder residual strength and reliability is also discussed, focussing on gross, hull girder net and local net scantlings, respectively. The ISSC double hull oil tanker and single side bulk carrier, assumed as test cases in the ISSC 2012 report, are taken as reference ships.