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A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts

Mark Evans Orcid Logo

Materials, Volume: 10, Issue: 10, Start page: 1190

Swansea University Author: Mark Evans Orcid Logo

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DOI (Published version): 10.3390/ma10101190

Abstract

Producing predictions of the probabilistic risks of operating materials for given lengths of time at stated operating conditions requires the assimilation of existing deterministic creep life prediction models (that only predict the average failure time) with statistical models that capture the rand...

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Published in: Materials
ISSN: 1996-1944
Published: MDPI AG 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa36106
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spelling 2020-10-16T14:46:16.6835592 v2 36106 2017-10-17 A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts 7720f04c308cf7a1c32312058780d20c 0000-0003-2056-2396 Mark Evans Mark Evans true false 2017-10-17 MTLS Producing predictions of the probabilistic risks of operating materials for given lengths of time at stated operating conditions requires the assimilation of existing deterministic creep life prediction models (that only predict the average failure time) with statistical models that capture the random component of creep. To date, these approaches have rarely been combined to achieve this objective. The first half of this paper therefore provides a summary review of some statistical models to help bridge the gap between these two approaches. The second half of the paper illustrates one possible assimilation using 1Cr1Mo-0.25V steel. The Wilshire equation for creep life prediction is integrated into a discrete hazard based statistical model—the former being chosen because of its novelty and proven capability in accurately predicting average failure times and the latter being chosen because of its flexibility in modelling the failure time distribution. Using this model it was found that, for example, if this material had been in operation for around 15 years at 823 K and 130 MPa, the chances of failure in the next year is around 35%. However, if this material had been in operation for around 25 years, the chance of failure in the next year rises dramatically to around 80%. Journal Article Materials 10 10 1190 MDPI AG 1996-1944 creep; Wilshire equation; deterministic and random components; parametric and non-parametric statistical models; discrete hazard based models 17 10 2017 2017-10-17 10.3390/ma10101190 COLLEGE NANME Materials Science and Engineering COLLEGE CODE MTLS Swansea University 2020-10-16T14:46:16.6835592 2017-10-17T10:17:38.7336322 Faculty of Science and Engineering School of Engineering and Applied Sciences - Materials Science and Engineering Mark Evans 0000-0003-2056-2396 1 0036106-17102017133329.pdf evans2017(8).pdf 2017-10-17T13:33:29.9730000 Output 677987 application/pdf Version of Record true 2017-10-17T00:00:00.0000000 true eng
title A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts
spellingShingle A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts
Mark Evans
title_short A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts
title_full A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts
title_fullStr A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts
title_full_unstemmed A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts
title_sort A Review of Statistical Failure Time Models with Application of a Discrete Hazard Based Model to 1Cr1Mo-0.25V Steel for Turbine Rotors and Shafts
author_id_str_mv 7720f04c308cf7a1c32312058780d20c
author_id_fullname_str_mv 7720f04c308cf7a1c32312058780d20c_***_Mark Evans
author Mark Evans
author2 Mark Evans
format Journal article
container_title Materials
container_volume 10
container_issue 10
container_start_page 1190
publishDate 2017
institution Swansea University
issn 1996-1944
doi_str_mv 10.3390/ma10101190
publisher MDPI AG
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Materials Science and Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Materials Science and Engineering
document_store_str 1
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description Producing predictions of the probabilistic risks of operating materials for given lengths of time at stated operating conditions requires the assimilation of existing deterministic creep life prediction models (that only predict the average failure time) with statistical models that capture the random component of creep. To date, these approaches have rarely been combined to achieve this objective. The first half of this paper therefore provides a summary review of some statistical models to help bridge the gap between these two approaches. The second half of the paper illustrates one possible assimilation using 1Cr1Mo-0.25V steel. The Wilshire equation for creep life prediction is integrated into a discrete hazard based statistical model—the former being chosen because of its novelty and proven capability in accurately predicting average failure times and the latter being chosen because of its flexibility in modelling the failure time distribution. Using this model it was found that, for example, if this material had been in operation for around 15 years at 823 K and 130 MPa, the chances of failure in the next year is around 35%. However, if this material had been in operation for around 25 years, the chance of failure in the next year rises dramatically to around 80%.
published_date 2017-10-17T03:45:06Z
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score 10.999161

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