Assessment of master curve material inhomogeneity using small data sets

Kim Wallin

doi:10.1115/PVP2018-84297

Assessment of master curve material inhomogeneity using small data sets

Kim Wallin

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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	https://doi.org/10.1115/PVP2018-84297
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/Territory	Czech Republic
City	Prague
Period	15/07/18 → 20/07/18

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10.1115/PVP2018-84297

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title = "Assessment of master curve material inhomogeneity using small data sets",

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.",

author = "Kim Wallin",

note = "Funding Information: This work belongs to project LOST (long term operational aspects of structural integrity) that is part of SAFIR2018. (The Finnish Research Programme on Nuclear Power Plant Safety 2015 – 2018). Publisher Copyright: Copyright {\textcopyright} 2018 ASME. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; ASME 2018 Pressure Vessels and Piping Conference, PVP2018, PVP2018 ; Conference date: 15-07-2018 Through 20-07-2018",

year = "2018",

doi = "10.1115/PVP2018-84297",

language = "English",

volume = "1A",

booktitle = "Proceedings of the ASME 2018 Pressure Vessels and Piping Conference",

publisher = "American Society of Mechanical Engineers (ASME)",

address = "United States",

}

Wallin, K 2018, Assessment of master curve material inhomogeneity using small data sets. in Proceedings of the ASME 2018 Pressure Vessels and Piping Conference: Codes and Standards. vol. 1A, PVP2018-84297, American Society of Mechanical Engineers (ASME), ASME 2018 Pressure Vessels and Piping Conference, PVP2018, Prague, Czech Republic, 15/07/18. https://doi.org/10.1115/PVP2018-84297

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

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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.

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DO - 10.1115/PVP2018-84297

M3 - Conference article in proceedings

AN - SCOPUS:85056860740

VL - 1A

BT - Proceedings of the ASME 2018 Pressure Vessels and Piping Conference

PB - American Society of Mechanical Engineers (ASME)

T2 - ASME 2018 Pressure Vessels and Piping Conference, PVP2018

Y2 - 15 July 2018 through 20 July 2018

ER -

Assessment of master curve material inhomogeneity using small data sets

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