Abstract
The standard Master Curve (MC) deals only with materials assumed to be homogeneous, but MC analysis methods for inhomogeneous materials have also been developed. Especially the bi-modal and multi-modal analysis methods are becoming more and more standard. Their drawback is that these methods are generally reliable only with sufficiently large data sets (number of valid tests, r = 15 - 20). Here, the possibility of using the multi-modal analysis method with smaller data sets is assessed, and a new procedure to conservatively account for possible inhomogeneities is proposed.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the ASME 2018 Pressure Vessels and Piping Conference |
| Subtitle of host publication | Codes and Standards |
| Publisher | American Society of Mechanical Engineers ASME |
| Volume | 1A |
| ISBN (Electronic) | 978-0-7918-5158-6 |
| DOIs | |
| Publication status | Published - 2018 |
| MoE publication type | Not Eligible |
| Event | ASME 2018 Pressure Vessels and Piping Conference, PVP2018 - Hotel Hilton, Prague, Czech Republic Duration: 15 Jul 2018 → 20 Jul 2018 Conference number: 52 |
Conference
| Conference | ASME 2018 Pressure Vessels and Piping Conference, PVP2018 |
|---|---|
| Abbreviated title | PVP2018 |
| Country | Czech Republic |
| City | Prague |
| Period | 15/07/18 → 20/07/18 |
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Assessment of master curve material inhomogeneity using small data sets. / Wallin, Kim.
Proceedings of the ASME 2018 Pressure Vessels and Piping Conference: Codes and Standards. Vol. 1A American Society of Mechanical Engineers ASME, 2018. PVP2018-84297.Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
TY - GEN
T1 - Assessment of master curve material inhomogeneity using small data sets
AU - Wallin, Kim
PY - 2018
Y1 - 2018
N2 - The standard Master Curve (MC) deals only with materials assumed to be homogeneous, but MC analysis methods for inhomogeneous materials have also been developed. Especially the bi-modal and multi-modal analysis methods are becoming more and more standard. Their drawback is that these methods are generally reliable only with sufficiently large data sets (number of valid tests, r = 15 - 20). Here, the possibility of using the multi-modal analysis method with smaller data sets is assessed, and a new procedure to conservatively account for possible inhomogeneities is proposed.
AB - The standard Master Curve (MC) deals only with materials assumed to be homogeneous, but MC analysis methods for inhomogeneous materials have also been developed. Especially the bi-modal and multi-modal analysis methods are becoming more and more standard. Their drawback is that these methods are generally reliable only with sufficiently large data sets (number of valid tests, r = 15 - 20). Here, the possibility of using the multi-modal analysis method with smaller data sets is assessed, and a new procedure to conservatively account for possible inhomogeneities is proposed.
UR - http://www.scopus.com/inward/record.url?scp=85056860740&partnerID=8YFLogxK
U2 - 10.1115/PVP2018-84297
DO - 10.1115/PVP2018-84297
M3 - Conference article in proceedings
VL - 1A
BT - Proceedings of the ASME 2018 Pressure Vessels and Piping Conference
PB - American Society of Mechanical Engineers ASME
ER -