Effect of short-term data on predicted creep rupture life

Pivoting effect and optimized censoring

Stefan Holmström, Pertti Auerkari

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)

Abstract

Fitting data to classical creep rupture models can result in unrealistically high extrapolated long-term strength. As a consequence, the standard strength values for new steel grades have frequently needed downward correction after obtaining more long-term test data. The reasons for non-conservative extrapolation include the influence of short-term data, which are easiest to produce but tend to pivot upwards the extrapolated values of creep rupture strength. Improvement in extrapolation could be expected by reducing this effect through model rigidity correction and censoring of very short-term data, but it may not be immediately clear how to justify the correction of particular models or censoring.

Analogously to the instability parameter in the minimum commitment model for creep rupture, a rigidity parameter correction (RPC) is introduced to assess the pivoting effect of creep rupture models for the purpose of reducing potential to non-conservativeness in extrapolation. The RPC approach can be used with any creep rupture model for comparing the model rigidity and the potential benefit from censoring short-term data. The correction itself will never introduce non-conservatism, regardless of the model. The RPC approach is demonstrated by analyzing an ECCC data set for cross-welded 9%Cr steel (E911).
Original languageEnglish
Pages (from-to)103-109
Number of pages7
JournalMaterials at High Temperatures
Volume25
Issue number3
DOIs
Publication statusPublished - 2008
MoE publication typeA1 Journal article-refereed

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Creep
rigidity
Rigidity
Extrapolation
extrapolation
Steel
creep rupture strength
steels
pivots
grade

Keywords

  • Creep rupture life
  • Optimized censoring
  • Pivoting effect
  • Short-term data

Cite this

@article{c39965a5d05241c3aec21d86d57b2af5,
title = "Effect of short-term data on predicted creep rupture life: Pivoting effect and optimized censoring",
abstract = "Fitting data to classical creep rupture models can result in unrealistically high extrapolated long-term strength. As a consequence, the standard strength values for new steel grades have frequently needed downward correction after obtaining more long-term test data. The reasons for non-conservative extrapolation include the influence of short-term data, which are easiest to produce but tend to pivot upwards the extrapolated values of creep rupture strength. Improvement in extrapolation could be expected by reducing this effect through model rigidity correction and censoring of very short-term data, but it may not be immediately clear how to justify the correction of particular models or censoring.Analogously to the instability parameter in the minimum commitment model for creep rupture, a rigidity parameter correction (RPC) is introduced to assess the pivoting effect of creep rupture models for the purpose of reducing potential to non-conservativeness in extrapolation. The RPC approach can be used with any creep rupture model for comparing the model rigidity and the potential benefit from censoring short-term data. The correction itself will never introduce non-conservatism, regardless of the model. The RPC approach is demonstrated by analyzing an ECCC data set for cross-welded 9{\%}Cr steel (E911).",
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language = "English",
volume = "25",
pages = "103--109",
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Effect of short-term data on predicted creep rupture life : Pivoting effect and optimized censoring. / Holmström, Stefan; Auerkari, Pertti.

In: Materials at High Temperatures, Vol. 25, No. 3, 2008, p. 103-109.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Effect of short-term data on predicted creep rupture life

T2 - Pivoting effect and optimized censoring

AU - Holmström, Stefan

AU - Auerkari, Pertti

PY - 2008

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N2 - Fitting data to classical creep rupture models can result in unrealistically high extrapolated long-term strength. As a consequence, the standard strength values for new steel grades have frequently needed downward correction after obtaining more long-term test data. The reasons for non-conservative extrapolation include the influence of short-term data, which are easiest to produce but tend to pivot upwards the extrapolated values of creep rupture strength. Improvement in extrapolation could be expected by reducing this effect through model rigidity correction and censoring of very short-term data, but it may not be immediately clear how to justify the correction of particular models or censoring.Analogously to the instability parameter in the minimum commitment model for creep rupture, a rigidity parameter correction (RPC) is introduced to assess the pivoting effect of creep rupture models for the purpose of reducing potential to non-conservativeness in extrapolation. The RPC approach can be used with any creep rupture model for comparing the model rigidity and the potential benefit from censoring short-term data. The correction itself will never introduce non-conservatism, regardless of the model. The RPC approach is demonstrated by analyzing an ECCC data set for cross-welded 9%Cr steel (E911).

AB - Fitting data to classical creep rupture models can result in unrealistically high extrapolated long-term strength. As a consequence, the standard strength values for new steel grades have frequently needed downward correction after obtaining more long-term test data. The reasons for non-conservative extrapolation include the influence of short-term data, which are easiest to produce but tend to pivot upwards the extrapolated values of creep rupture strength. Improvement in extrapolation could be expected by reducing this effect through model rigidity correction and censoring of very short-term data, but it may not be immediately clear how to justify the correction of particular models or censoring.Analogously to the instability parameter in the minimum commitment model for creep rupture, a rigidity parameter correction (RPC) is introduced to assess the pivoting effect of creep rupture models for the purpose of reducing potential to non-conservativeness in extrapolation. The RPC approach can be used with any creep rupture model for comparing the model rigidity and the potential benefit from censoring short-term data. The correction itself will never introduce non-conservatism, regardless of the model. The RPC approach is demonstrated by analyzing an ECCC data set for cross-welded 9%Cr steel (E911).

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KW - Optimized censoring

KW - Pivoting effect

KW - Short-term data

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DO - 10.3184/096034008X354747

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