Application of an XML-based Database for Probabilistic Analysis

Millwater, Harry; Fitch, S.H.; Enright, Michael P.; Huyse, Luc

doi:10.2514/6.2003-1837

Cited by 2 publications

(1 citation statement)

References 5 publications

(7 reference statements)

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“…Pellissetti and Schueller [4] classified different reliability software depending on their features. Millwater et al [5] developed a database for probabilistic analysis.…”

Section: Introductionmentioning

confidence: 99%

Ontologies to Capture and Share Knowledge in a Distributed Environment Needed to Support Decision Making in Probabilistic Design

Lee¹,

Choi

2014

AMM

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Durability and reliability must be considered in the design of structural components. For this purpose, the failure probability is found using probabilistic analysis. A component in an automotive structure usually has many different designs depending on vehicle models. Even in the same vehicle model, the design of the component changes once in a few years. It is important to build up database so that engineers share knowledge in the design of components. The purpose of this study is to develop ontologies in the probabilistic analysis of structures. The ontologies can be used to capture and share knowledge for design process. They also help engineers make decisions on choosing appropriate software and algorithm for the probabilistic analysis of structures.

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“…Pellissetti and Schueller [4] classified different reliability software depending on their features. Millwater et al [5] developed a database for probabilistic analysis.…”

Section: Introductionmentioning

confidence: 99%

Ontologies to Capture and Share Knowledge in a Distributed Environment Needed to Support Decision Making in Probabilistic Design

Lee¹,

Choi

2014

AMM

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Convergent Zone-Refinement Method for Risk Assessment of Gas Turbine Disks Subject to Low-Frequency Metallurgical Defects

Millwater

Enright

Fitch³

2006

Journal of Engineering for Gas Turbines and Power

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Titanium gas turbine disks are subject to a rare but not insignificant probability of fracture due to metallurgical defects, particularly hard ␣. A probabilistic methodology has been developed and implemented in concordance with the Federal Aviation Administration (FAA) Advisory Circular 33.14-1 to compute the probability of fracture of gas turbine titanium disks subject to low-frequency metallurgical (hard ␣) defects. This methodology is further developed here to ensure that a robust, converged, accurate calculation of the probability is computed that is independent of discretization issues. A zonebased material discretization methodology is implemented, then refined locally through further discretization using risk contribution factors as a metric. The technical approach is akin to "h" refinement in finite element analysis; that is, a local metric is used to indicate regions requiring further refinement, and subsequent refinement yields a more accurate solution. Supporting technology improvements are also discussed, including localized finite element refinement and onion skinning for zone subdivision resolution, and a restart database and parallel processing for computational efficiency. A numerical example is presented for demonstration.

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Application of an XML-based Database for Probabilistic Analysis

Cited by 2 publications

References 5 publications

Ontologies to Capture and Share Knowledge in a Distributed Environment Needed to Support Decision Making in Probabilistic Design

Ontologies to Capture and Share Knowledge in a Distributed Environment Needed to Support Decision Making in Probabilistic Design

Convergent Zone-Refinement Method for Risk Assessment of Gas Turbine Disks Subject to Low-Frequency Metallurgical Defects

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