Sorce, F.S., Cogswell, D.J. and Davies, C.M. (2022) An investigation Into the applicability of Charpy dynamic fracture tests for a digital twin. In: Volume 4A: Materials and Fabrication. ASME 2022 Pressure Vessels & Piping Conference, 17-22 Jul 2022, Las Vegas, Nevada, USA. American Society of Mechanical Engineers ISBN 9780791886175
Abstract
The Charpy impact test has historically been used in a qualitative and comparative manner to infer toughness behaviour and determine the brittle to ductile transition temperature (TBD) of low alloy ferritic steels used in reactor pressure vessels (RPVs). The simple and quick setup makes it an attractive test given the ease of data generation to assess the suitability of a given material; however, the scatter in the data produced is significant and the test does not provide a value of fracture toughness. Quasi-static tests using high-constraint geometries (e.g. single-edge notch bend (SENB) specimens) are used to determine fracture toughness properties, whilst the Charpy impact test (governed by the ASTM E23 and ISO 148 standards) gives insight into the dynamic fracture response of a material. There is significant interest, demonstrated by recent work, in utilising Charpy impact test data to predict fracture toughness properties and material behaviour, which typically require expensive and time-consuming test procedures. The ongoing digital transformation of industry and proposals of digital twins becoming ubiquitous relies intrinsically on high-quality data inputs and fully understanding the underlying mechanistic relationships governing material behaviour. This work examines the relationships between microstructure, temperature, and quasi-static and dynamic fracture behaviour of a low alloy ferritic steel (comparable in composition to SA508). The microstructures are analysed before a Charpy impact pendulum is used to determine the energy absorbed by standard V-notch samples from −196 °C to 200 °C and the fracture surfaces examined. A distinct transition zone is observed and the data is compared to historic fracture data of the material. The results are discussed in light of applicability to a digital twin and the framework for a machine learning model to predict the fracture behaviour and reduce error in transition behaviour is proposed.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 by ASME |
Keywords: | charpy; fracture; digital twin; SA508 steel |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Materials Science and Engineering (Sheffield) |
Funding Information: | Funder Grant number MEDICAL RESEARCH COUNCIL MR/T02058X/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Jun 2023 10:45 |
Last Modified: | 08 Jun 2023 10:45 |
Status: | Published |
Publisher: | American Society of Mechanical Engineers |
Refereed: | Yes |
Identification Number: | 10.1115/pvp2022-84857 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199612 |