The inclusive and simplified forms of Bayesian interpolation for general and monotonic models using Gaussian and Generalized Beta distributions with application to Monte Carlo simulations

Rajabalinejad, Mohammad; Mahdi, Tew‐Fik

doi:10.1007/s11069-010-9560-3

Cited by 10 publications

(9 citation statements)

References 10 publications

(8 reference statements)

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“…The Beta probability distribution function is defined with two Beta parameters, p and q, in the interval a to c (Williams, 2003). The mean value and standard deviation of the Beta distribution are defined by the Beta parameters, as indicated, for instance, in Rajabalinejad and Mahdi (2010).…”

Section: Beta Score Function and Uncertainty Estimationmentioning

confidence: 99%

Incorporating Uncertainty into the Design Management Process

Rajabalinejad

Spitas²

2011

Design Management Journal

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Design and management are ubiquitous words that are used in different contexts. We read or hear about automobile designers, dress designers, architectural designers, system designers, aircraft designers, and so on. We also hear about people who are project managers, office managers, product managers, and the like. In fact, design and management are part of human history, and people have always designed artifacts and managed processes in any way that was necessary.Early designs were well integrated with manufacture; people tested their designs and tried to address their shortcomings or failures. With accumulating experience, rules of thumb and best practices were established. Modeling of phenomena related to product function through physics and other theoretical disciplines augmented predictive power and made it more possible to quantify design parameters a priori.

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Section: Beta Score Function and Uncertainty Estimationmentioning

confidence: 99%

Incorporating Uncertainty into the Design Management Process

Rajabalinejad

Spitas²

2011

Design Management Journal

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“…The Monte Carlo family of methods includes the so-called variance optimization schemes for improving the computational efficiency. Among these, the most widely used are the importance sampling (IS), as explained in (Melchers 1999) and directional sampling (DS) presented in (Nie and Ellingwood 2000) and some recently developed methods such as Bayesian Monte Carlo (BMC) presented in (Rajabalinejad 2010;Rajabalinejad and Mahdi 2010), dynamic bounds (DB) described in (Rajabalinejad 2009) and improved dynamic bounds (IDB) presented in (Rajabalinejad et al 2010a) . Each method has its advantages and disadvantages when it is coupled with finite elements.…”

Section: Problem Statementmentioning

confidence: 99%

Stochastic methods for safety assessment of the flood defense system in the Scheldt Estuary of the Netherlands

Rajabalinejad

Mahdi

Gelder³

2010

Nat Hazards

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In this study, we address the effective method to apply a novel reliability method integrated with finite element models to the safety assessment of pilot site Scheldt in the Netherlands. This site was considered as one of the three main pilot sites in Europe to assess the application of newly suggested techniques in order to reduce and manage the flood risk in the Floodsite project. http://www.floodsite.net, 2004-2009). The novel method of dynamic bounds (DB) is applied to this site after a successful experience in (Rajabalinejad in Reliability methods for finite element models, 1 edn. IOS Press, Amsterdam, 2009). In this study, the bi-functional response of the finite element model is considered, and the dimensional uncertainty is defined presenting the expected uncertainty for a certain dimension in the DB method. The uncertainty is used as a judgment tool to choose the dimension for the DB method for the desired accuracy. The results obtained by applying this technique are presented in this paper.

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“…Rajabalinéjad et al (2010aRajabalinéjad et al ( , 2010b et Rajabalinejad et Mahdi (2010) ont proposé une nouvelle méthode, méthode des limites dynamiques, pour réduire l'exigence en temps de calcul de la méthode probabiliste des éléments finis. Cette dernière offre une meilleure compréhension des mé-canismes de rupture.…”

Section: Introductionunclassified

Modélisation probabiliste du débit de rupture par submersion d’un barrage en remblai

2014

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Les barrages en remblai, et les barrages en général, sont dimensionnés pour résister aux différents facteurs (mé-téorologique, sismique, humain) qui pourraient causer leur rupture. Cependant, le risque zéro n'existe pas et la probabilité que chaque barrage soit détruit n'est pas nulle. Dans une optique d'optimisation de la sécurisation des zones en aval du barrage, la méthodologie présentée permet de probabiliser la rupture du barrage par submersion, afin de dépasser la simple évaluation de rupture -non rupture. Le calcul de la probabilité de rupture constitue la première étape, les scénarios de rupture étant principalement liés aux occurrences des crues. La deuxième étape est la probabilisation des hydrogrammes de crue au travers de leurs caractéristiques principales, le débit maximal et la durée nécessaire pour atteindre ce débit.Mots-clés : barrage en remblai, rupture, submersion, probabilisation, hydrogramme.Abstract: Earthfill dams, and even all dams, are designed to withstand different factors (meteorological, seismic, and human), which might be responsible for their failure. Yet there is no such thing as zero risk, and the possibilities of failure exist. With a view to optimize the safety of downstream areas, dam failures by overtopping can be studied from a probabilistic point of view, in order to go further than a simple failure -non failure evaluation. Probability calculation of the failure, mainly with flood studies, is the first step. Then, in order to improve the prediction of the failure, the failure hydrograph is probabilized by its maximum discharge and the time this discharge needs to be reached.

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The inclusive and simplified forms of Bayesian interpolation for general and monotonic models using Gaussian and Generalized Beta distributions with application to Monte Carlo simulations

Cited by 10 publications

References 10 publications

Incorporating Uncertainty into the Design Management Process

Incorporating Uncertainty into the Design Management Process

Stochastic methods for safety assessment of the flood defense system in the Scheldt Estuary of the Netherlands

Modélisation probabiliste du débit de rupture par submersion d’un barrage en remblai

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