Localized Load-Sharing Rules and Markov-Weibull Fibers: A Comparison of Microcomposite Failure Data with Monte Carlo Simulations

Durham, S. D.; Lynch, James; Padgett, W. J.; Horan, T. J.; Owen, William J.; Surles, James G.

doi:10.1177/002199839703101805

Cited by 37 publications

(27 citation statements)

References 18 publications

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“…A comprehensive discussion about sharing rules (e.g., equal load sharing, tapered load sharing, local load-sharing, etc.) is provided by [3]. The load sharing mechanism introduces dependency between the times to failure among the components, making modeling and inference of such systems different from simpler redundant systems, such as a -out-of-system [4].…”

Section: B Overview Of Load Sharing Systems Modelsmentioning

confidence: 99%

A Load Sharing System Reliability Model With Managed Component Degradation

Revie

Walls

2014

IEEE Trans. Rel.

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Motivated by an industrial problem affecting a water utility, we develop a model for a load sharing system where an operator dispatches work load to components in a manner that manages their degradation. We assume degradation is the dominant failure type, and that the system will not be subject to sudden failure due to a shock. By deriving the time to degradation failure of the system, estimates of system probability of failure are generated, and optimal designs can be obtained to minimize the long run average cost of a future system. The model can be used to support asset maintenance and design decisions. Our model is developed under a common set of core assumptions. That is, the operator allocates work to balance the level of the degradation condition of all components to achieve system performance. A system is assumed to be replaced when the cumulative work load reaches some random threshold. We adopt cumulative work load as the measure of total usage because it represents the primary cause of component degradation. We model the cumulative work load of the system as a monotone increasing and stationary stochastic process. The cumulative work load to degradation failure of a component is assumed to be inverse Gaussian distributed. An example, informed by an industry problem, is presented to illustrate the application of the model under different operating scenarios.

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Section: B Overview Of Load Sharing Systems Modelsmentioning

confidence: 99%

A Load Sharing System Reliability Model With Managed Component Degradation

Revie

Walls

2014

IEEE Trans. Rel.

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“…For more details and applications of various load-sharing rules, the reader is referred to Durham et al (1997) where several load-sharing rules are considered.…”

Section: Parameter Estimation Under Exponential and Weibull Distributmentioning

confidence: 99%

“…This is referred to as the equal load-sharing rule. For other load-sharing rules, the reader is referred to Durham et al (1997), who considered equal load-sharing, tapered loadsharing, local load-sharing, nearest-neighbor load-sharing, and a hybrid load-sharing rule. Other early works on loadsharing systems are referenced by Daniels (1945), Coleman (1957aColeman ( , 1957b, Birnbaum and Saunders (1958), Rosen (1964), Harlow andPhoenix (1978, 1982), Phoenix (1978), and Phoenix and Tierney (1983), while more recent results are considered by Lee et al (1995), Harlow (1997), Wang et al (1998), Durham and Lynch (2000), Wang et al (2000), Kim and Kvam (2004), Kvam and Peña (2005), Yang and Younis (2005), and Singh et al (2008).…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation for the reliability of load-sharing systems

Park

2010

IIE Transactions

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Consider a multi-component system connected in parallel. In this system, as components fail one by one, the total load or traffic applied to the system is redistributed among the remaining surviving components, which is commonly referred to as load-sharing. This develops parameter estimation methods for these type of systems. A closed-form Maximum Likelihood Estimator (MLE) and Best Unbiased Estimator (BUE) are provided under a general load-sharing rule when the underlying lifetime distribution of the components in the system is exponential. As an extension, it is assumed that the underlying lifetime distribution of the components is Weibull and it is shown that, after the shape parameter is estimated by solving the one-dimensional log-likelihood estimating equation, the closed-form MLE and conditional BUE of the rate parameter are easily obtained. The asymptotic distribution of the proposed MLE is also provided. Illustrative examples and Monte Carlo simulation results are also presented and these substantiate the proposed methods.

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“…II, example 7.10). The most common load-sharing approaches may be classified into equal load-sharing, tapered load-sharing, local load-sharing, nearest-neighbor load-sharing, and hybrid load-sharing (Durham et al 1997). The widely used Daniels system (Daniels 1945) assumes equal load-sharing where all components share equal parts of the total load.…”

Section: Introductionmentioning

confidence: 99%

Target geotechnical reliability for redundant foundation systems

Naghibi

Fenton

2017

Can. Geotech. J.

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Geotechnical support systems (e.g., deep and shallow foundations) generally involve at least some redundancy. For example, if a building is supported by n p separate foundations, then failure (e.g., excessive settlement) of a single foundation will generally not result in failure of the building if the building is able to shed the load from the failed foundation to adjacent foundations. This load-shedding ability lends the foundation system redundancy -system failure only occurs if multiple foundations fail. This paper investigates the relationship between the level of geotechnical redundancy, individual foundation reliability, and system reliability for deep foundations (piles). In the particular case where the pile resistance remains constant after achieving its ultimate capacity (at a certain displacement), the relationship between individual and system reliabilities is computed theoretically. The more general case, where the load carried by the pile reduces after exceeding its ultimate capacity, is investigated by Monte Carlo simulation. Charts relating system and individual reliability indices are presented, which can be used to aid in the design of individual piles as part of a pile support system.Key words: reliability-based design, deep foundation design, redundant systems, probabilistic modeling.Résumé : Les systèmes de soutien géotechnique (par ex., des fondations superficielles et profondes) comportent en général au moins une certaine redondance. Par exemple, si un bâtiment est soutenu par n p des fondations, alors la défaillance (p. ex., le tassement excessif) d'une seule fondation n'entraînera généralement pas la défaillance de l'immeuble, si l'immeuble est en mesure de délester la charge de la fondation échouée aux fondations adjacentes. Cette capacité de délestage de la fondation prête la redondance au système de fondation -la défaillance du système se produit uniquement si plusieurs fondations échouent. Cet article étudie la relation entre le niveau de redondance géotechnique, la fiabilité de fondation individuelle et la fiabilité du système de fondations profondes (pieux). Dans le cas particulier où la résistance de pieu demeure constante après la réalisation de sa capacité ultime (à un certain déplacement), la relation entre la fiabilité individu et la fiabilité du système est calculée théoriquement. Le cas plus général, où la charge transmise par le pieu diminue après avoir dépassé sa capacité ultime, est étudié par simulation de Monte-Carlo. Des tableaux montrant des indices de fiabilité de systèmes et individus sont présentés, qui peuvent être utilisés pour faciliter la conception de pieux individuels dans le cadre d'un système de soutien de pieu. [Traduit par la Rédaction] Mots-clés : conception basée sur la fiabilité, conception des fondations profondes, systèmes redondants, modélisation probabiliste.

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Localized Load-Sharing Rules and Markov-Weibull Fibers: A Comparison of Microcomposite Failure Data with Monte Carlo Simulations

Cited by 37 publications

References 18 publications

A Load Sharing System Reliability Model With Managed Component Degradation

A Load Sharing System Reliability Model With Managed Component Degradation

Parameter estimation for the reliability of load-sharing systems

Target geotechnical reliability for redundant foundation systems

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