A study on grain growth using a novel grain size calculation tool
|Author:||Koskenniska, Sami1; Seppälä, Oskari1; Kömi, Jukka1|
1Materials and Mechanical Engineering, Centre for Advanced Steel Research, University of Oulu, P.O. Box 8000, FI-90014 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020091069229
|Publish Date:|| 2020-09-10
The growth of prior austenite grains (PAG) of low alloyed martensitic steel is proven to be one of the key attributes contributing to the mechanical properties of ultrahigh-strength steels. The mean linear intercept -method (MLI) is traditionally used to acquire average PAG sizes from light optical microscopy images, which are from experimental test samples. The MLI -method is arduous and time-consuming as well as a highly generalizing method, where you lose information about the grain size distribution. Therefore, a more sophisticated and computerised method is in high demand among metallurgists.
A program has been developed that encompasses an importing, digitalizing and calculating tool, which provides grain sizes and their distribution from multiple images. The tool mimics the workflow of manual MLI -method so the user sets the measure lines and marks all the linear intercepts. After this the tool calculates the MLI grain sizes and their 95 % confidence limits. Additionally, the tool provides the size of each intercepted grain and combines them to create a distribution. This information has been used to study the effects of holding temperature and time on grain sizes throughout the test samples in a case where abnormal grain growth at the centreline was expected.
In the present study, PAG sizes were studied before and after deformation at ¼ and ½ thicknesses at various temperatures and holding times using the grain size calculation tool. The average MLI grain sizes show very little differences between temperatures and holding times, so information about grain size distribution is needed. Traditional presentation of the grain size distributions also shows too much variation to interpret the data properly. Instead, using the grain size distribution information and grouping grains to small, medium and large instances gives more profound data, especially in cases where grain size variation is significantly large.
Distribution data from the test series also showed abnormal grain growth at the centreline of the test sample. The grain size calculation tool is used to quantify the effect of temperature and hold time on abnormal grain growth and its root cause is examined briefly.
|Pages:||684 - 688|
|Host publication editor:||
18th International Conference on Metal Forming 2020
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
216 Materials engineering
The authors are grateful for Business Finland for financing this work as a part of the research project STEFA – Steel Ecosystem for Focused Applications.
© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)