A Virtual Prognostic Tool for Nuclear Power Electronics Reliability

Amer B. Dababneh; Ben Goerdt; Timothy Marler; Ibrahim T. Ozbolat

doi:10.1080/16864360.2014.846097

A Virtual Prognostic Tool for Nuclear Power Electronics Reliability

Amer B. Dababneh, Ben Goerdt, Timothy Marler, Ibrahim T. Ozbolat

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

This research highlights new developments in a high fidelity virtual environment that allows prediction of total life time, overall reliability and maintainability for circuit cards and their components, through a new simulation methodology. This work demonstrates the application of statistical models to circuit cards, and the ability to predict system and sub-system performance based on component data. Quantitative accelerated life tests are designed to quantify the life of circuit cards under different thermal stresses. This research allows the user to identify the components that contribute the most to downtime and to determine the effect of design alternatives on system performance in a cost-effective manner. Most significantly, this work has proven the feasibility of a novel platform for physics-based reliability analysis.

Original language	English (US)
Pages (from-to)	228-238
Number of pages	11
Journal	Computer-Aided Design and Applications
Volume	11
Issue number	2
DOIs	https://doi.org/10.1080/16864360.2014.846097
State	Published - Mar 2014

All Science Journal Classification (ASJC) codes

Computational Mechanics
Computer Graphics and Computer-Aided Design
Computational Mathematics

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10.1080/16864360.2014.846097

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title = "A Virtual Prognostic Tool for Nuclear Power Electronics Reliability",

abstract = "This research highlights new developments in a high fidelity virtual environment that allows prediction of total life time, overall reliability and maintainability for circuit cards and their components, through a new simulation methodology. This work demonstrates the application of statistical models to circuit cards, and the ability to predict system and sub-system performance based on component data. Quantitative accelerated life tests are designed to quantify the life of circuit cards under different thermal stresses. This research allows the user to identify the components that contribute the most to downtime and to determine the effect of design alternatives on system performance in a cost-effective manner. Most significantly, this work has proven the feasibility of a novel platform for physics-based reliability analysis.",

author = "Dababneh, {Amer B.} and Ben Goerdt and Timothy Marler and Ozbolat, {Ibrahim T.}",

note = "Funding Information: This research is funded by the Electric Power Research Institute (EPRI) with the grant number “EP-P42490/C18498.”",

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AU - Dababneh, Amer B.

AU - Goerdt, Ben

AU - Marler, Timothy

AU - Ozbolat, Ibrahim T.

N1 - Funding Information: This research is funded by the Electric Power Research Institute (EPRI) with the grant number “EP-P42490/C18498.”

PY - 2014/3

Y1 - 2014/3

N2 - This research highlights new developments in a high fidelity virtual environment that allows prediction of total life time, overall reliability and maintainability for circuit cards and their components, through a new simulation methodology. This work demonstrates the application of statistical models to circuit cards, and the ability to predict system and sub-system performance based on component data. Quantitative accelerated life tests are designed to quantify the life of circuit cards under different thermal stresses. This research allows the user to identify the components that contribute the most to downtime and to determine the effect of design alternatives on system performance in a cost-effective manner. Most significantly, this work has proven the feasibility of a novel platform for physics-based reliability analysis.

AB - This research highlights new developments in a high fidelity virtual environment that allows prediction of total life time, overall reliability and maintainability for circuit cards and their components, through a new simulation methodology. This work demonstrates the application of statistical models to circuit cards, and the ability to predict system and sub-system performance based on component data. Quantitative accelerated life tests are designed to quantify the life of circuit cards under different thermal stresses. This research allows the user to identify the components that contribute the most to downtime and to determine the effect of design alternatives on system performance in a cost-effective manner. Most significantly, this work has proven the feasibility of a novel platform for physics-based reliability analysis.

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A Virtual Prognostic Tool for Nuclear Power Electronics Reliability

Abstract

All Science Journal Classification (ASJC) codes

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