Journal article 171 views 22 downloads
Estimating the Monkman−Grant relation in the presence of errors in measurement of times to failure and minimum creep rates: with application to some high temperature materials
Materials at High Temperatures, Pages: 1 - 16
Swansea University Author: Mark Evans
-
PDF | Version of Record
© 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.
Download (2.08MB)
DOI (Published version): 10.1080/09603409.2024.2377497
Abstract
The Monkman-Grant relation has the potential to reduce the development cycle for new materials, as it provides a means of lifing based on minimum creep rates that are typically observed early on. This paper outlines problems in estimating the nature of this relation using the least squares technique...
Published in: | Materials at High Temperatures |
---|---|
ISSN: | 0960-3409 1878-6413 |
Published: |
Informa UK Limited
2024
|
Online Access: |
Check full text
|
URI: | https://cronfa.swan.ac.uk/Record/cronfa66985 |
Abstract: |
The Monkman-Grant relation has the potential to reduce the development cycle for new materials, as it provides a means of lifing based on minimum creep rates that are typically observed early on. This paper outlines problems in estimating the nature of this relation using the least squares technique that stems from errors made in measuring failure times and minimum creep rates. The paper outlines some solutions to this problem that have been proposed within the scientific literature – such as reverse regression and the Deming regression. The evidence from the materials studied in this paper, suggest that the use of least squares results in overly conservative lifetime predictions when using the Monkman-Grant relation. It was found that for 2.25Cr-1Mo steel, the life expected for a minimum creep rate of 3.67E-12s- 1 was 57 years when the least squares technique was used, but this increased to 78 years when using the Deming regression. |
---|---|
Keywords: |
Monkman-Grant relation; measurement errors; least squares; total least squares; Deming regression |
College: |
Faculty of Science and Engineering |
Funders: |
Swansea University |
Start Page: |
1 |
End Page: |
16 |