It is important to be able to predict the creep life and other creep properties of materials used in power plants and aeroengines. Whilst existing studies have compared different creep models using different measures of predictive performance, none have identified whether these differences are real from a statistical significance perspective. This paper proposes several tests based on a review of the literature. These tests were applied to two creep models using failure time data on 2.25Cr–1Mo steel to develop a recommended approach for practitioners to adopt when selecting a creep model. All such tests concluded that the Evans model produced better long-term life predictions using only short-term data, and that this difference was statistically significant at the 5% significance level.
EvansM. Creep in materials – origins, analysis and prediction methodologies. Journal of Materials Education2008; 30(3–4): 96–211.
2.
HoldsworthSRAskinsBBakerMA, et al.Factors influencing creep 598 model equation selection. International Journal of Pressure Vessels and Piping2008; 5: 80–88.
3.
EvansM. An estimation method (LOESS) for dealing with the imperfections of existing parametric creep models for time to failure: Illustrated using 2.25Cr–1Mo steel. International Journal of Pressure Vessels and Piping2023; 206: 105047.
4.
EvansM. Semi-parametric estimation of the Wilshire creep life prediction model: an application to 2.25Cr–1Mo steel. Materials Science and Technology2019; 35: 1977–1987.
5.
HoldsworthSRMercklingG. ECCC developments in the assessment of creep-rupture data. In: Proceedings of sixth international Charles Parsons Conference on engineering issues in turbine machinery, power plant and renewables, Trinity College, Dublin, 16–18 September, (200).
6.
AbdallahZGrayVWhittakerM,et al.A critical analysis of the conventionally employed creep lifing methods. Materials2014; 7: 3371–3398.
7.
Francisco dos Reis SobrinhoJBuenoL. Correlation between creep and hot tensile behaviour for 2.25Cr–1Mo steel from 500°C to 700°C. Part 2: an assessment according to different parameterization methodologies. Revista Matéria2005; 10: 463–471.
8.
Wilshire BScharningP. A new methodology for analysis of creep and creep fracture data for 9–12% chromium steels. International Materials Reviews2008; 53(2): 91–104.
9.
EvansM. Estimating threshold stresses using parametric equations for creep: application to low-alloy steels. Materials Science and Technology2023; 39(6): 1–16.
10.
EvansM. Assessing the predictive performance of creep models using absolute rather than squared prediction errors: an application to 2.25Cr–1Mo steel. Materials at High Temperatures 2023. Published Online: 16 Oct 2023.
11.
DieboldFXMarianoRS. Comparing predictive accuracy. Journal of Business and Economic Statistics1995; 13: 253–263.
12.
HarveyDLeybourneSNewboldP. Testing the equality of prediction mean squared errors. International Journal of Forecasting1997; 13: 281–291.
13.
AshleyLRGrangerCWJSchmalenseeR. Advertising and aggregate consumption: an analysis of causality. Econometrica1980; 48: 1149–1168.
14.
MorganWA. A test for significance of the difference between the two variances in a sample from a normal bivariate population. Biometrika1939–1940; 31: 13–19.
15.
GrangerCWJNewboldP. Forecasting economic time series. Orlando, FL: Academic Press, 1977.
16.
GrangerCWJNewboldP. Some comments on the evaluation of economic forecasts. Applied Economics1973; 5: 35–47.
17.
MendenhallWReinmuthJE. Statistics for management and economics. Boston, Mass.: Duxbury Press, 1982.
18.
DoornikJAHansenH. An omnibus test for univariate and multivariate normality. Oxford Bulletin of Economics and Statistics2008; 70: 927–939.
19.
JarqueCMBeraAK. Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters1980; 6: 255–259.
20.
WhiteH. A heteroskedastic-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica1980; 48: 817–838.
21.
NichollsDFPaganAR. Heteroscedasticity in models with lagged dependent variables. Econometrica1983; 51: 1233–1242.
22.
DornJEShepherdLA. What We Need to Know About Creep. In Proceedings of the STP 165 Symposium on The Effect of Cyclical Heating and Stressing on Metals at Elevated Temperatures, Chicago, IL, USA, 17 June 1954.
23.
WilshireBBattenboughAJ. Creep and creep fracture of polycrystalline copper. Materials Science and Engineering A2007; 443: 156–166.
24.
YangMWangQSongXL, et al.On the prediction of long term creep strength of creep resistant steels. International Journal of Materials Research2016; 107(2): 133–138.
25.
WangQYangMSongXL, et al.Rationalization of creep data of creep-resistant steels on the basis of the new power law creep equation. Metallurgical and Materials Transactions A2016; 47A: 3479–3487.
26.
EvansM. Testing model structure through a unification of some modern parametric models of creep: an application to 316H stainless steel. Metallurgical and Materials Transactions A2020; 51: 697–707.
27.
WilshireBWhittakerM. Long term creep life prediction for grade 22 (2.25Cr–1Mo) steels. Materials Science and Technology2011; 27: 642–647.
28.
WhittakerMTEvansMWilshireB. Long-term creep data prediction for type 316H stainless steel. Materials Science and Engineering A2016; 552: 145–150.
29.
ChenLDongZSongXL, et al.Determination of activation energy and prediction of long-term strength of creep rupture for alloy Inconel 740/740H: a method based on a new tensile creep rupture model. Metallurgical and Materials Transactions A2022; 53: 1–5.
30.
WhittakerMTHarrisonW. The evolution of the Wilshire equations for creep life prediction. Materials at High Temperatures2014; 31: 233–238.
31.
BrearJM. A perspective on the Wilshire creep equations. Strength, Fracture and Complexity2022; 15: 79–98.
NIMS Creep Data Sheet No. 3B. Data sheets on the elevated-temperature properties of 2.25Cr–1Mo steel for boiler and heat exchanger seamless tubes (STBA 24). Tokyo, Japan: National Research Institute for Metals, 1986.
34.
NIMS Creep Data Sheet No.50A. Long-term creep rupture data obtained after publishing the final edition of the creep data sheets. Tokyo, Japan: National Research Institute for Metals, 2015.
35.
EvansM. The important role played by high-temperature tensile testing in the representation of minimum creep rates using S-shaped curve models. Metallurgical and Materials Transactions A2023; 54: 4796–4805.
