Determination of prior austenite grain-and martensitic substructure size from metallographic etchings using a multi-step image processing algorithm
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T. Hönigmann
studied Physics at technical university Graz, Austria. At the time of publication, he is studying martensitic steels used in aviation and is modelling correlations between their thermomechanical processing, microstructure and fracture toughness in the context of his PhD thesis at Materials Center Leoben Forschung GmbH.
is a former member of the Chair of Ferrous Metallurgy at Montanuniversität Leoben. In 2013 she joined Materials Center Leoben Forschung GmbH in the field of Microelectronics. She is currently focused on optical light microscopy.
Abstract
State-of-the-art modelling algorithms allowing for prediction of macroscopic properties of martensitic steels are primarily based on microstructural parameters such as prior austenite grain size as well as martensite packet-and block size distribution. The latter are usually obtainable via electron backscatter diffraction (EBSD) measurements. However, determination via light microscopy would present a more cost-effective determination method. This work presents a python-based multi-step image processing algorithm capable of separating the grain boundaries and the martensitic substructure from etched micrographs. Additionally, the viability of a characteristic mean free path parameter λ of the martensitic substructure for comparison of different martensitic microstructures is tested. To this end, a microstructure variation of PH15-5 was performed using different heat treatments and the specimens were analyzed using EBSD and electrolytically etched micrographs.
Kurzfassung
Moderne Modellierungsalgorithmen, die eine Vorhersage der makroskopischen Eigenschaften martensitischer Stähle ermöglichen, basieren in erster Linie auf mikrostrukturellen Parametern wie der ehemaligen Austenitkorngröße sowie der Martensitpaket- und Blockgrößenver teilung. Letztere lassen sich in der Regel durch Rückstreuelektronenbeugung (EBSD) ermitteln. Eine Bestimmung mittels Lichtmikroskopie würde jedoch eine kostengünstigere Methode darstellen. In dieser Arbeit wird ein auf Python basierender mehrstufiger Bildverarbeitungsalgorithmus vorgestellt, der in der Lage ist, die Korngrenzen und die martensitische Substruktur aus geätzten Schliffbildern zu separieren. Darüber hinaus wird die Eignung eines charakteristischen Parameters λ für die mittlere freie Weglänge des martensitischen Gefüges zum Vergleich verschiedener martensitischer Gefüge getestet. Zu diesem Zweck wurde eine Gefügevariation von PH15-5 unter Verwendung verschiedener Wärmebehandlungen durchgeführt, und die Proben wurden mit EBSD und elektrolytisch geätzten Schliffbildern analysiert.
About the authors
studied Physics at technical university Graz, Austria. At the time of publication, he is studying martensitic steels used in aviation and is modelling correlations between their thermomechanical processing, microstructure and fracture toughness in the context of his PhD thesis at Materials Center Leoben Forschung GmbH.
is a former member of the Chair of Ferrous Metallurgy at Montanuniversität Leoben. In 2013 she joined Materials Center Leoben Forschung GmbH in the field of Microelectronics. She is currently focused on optical light microscopy.
5 Acknowledgement
The authors gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center “Integrated Computational Material, Process and Product Engineering (IC-MPPE)” (Project No 886385). This program is supported by the Austrian Federal Ministries for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Digital and Economic Affairs (BMDW), represented by the Austrian Research Promotion Agency (FFG), and the federal states of Styria, Upper Austria and Tyrol.
5 Danksagung
Die Autoren bedanken sich für die finanzielle Unterstützung im Rahmen des Programms COMET innerhalb des K2 Zentrums “Integrated Computational Material, Process and Product Engineering (IC-MPPE)” (Projekt-Nr. 886385). Dieses Programm wird unterstützt vom österreichischen Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie (BMK) und vom österreichischen Bundesministerium Digitalisierung und Wirtschaftsstandort (BMDW), vertreten durch die Österreichische Forschungsförderungsgesellschaft (FFG) und die Bundesländer Steiermark, Oberösterreich und Tirol.
References / Literatur
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Artikel in diesem Heft
- Contents
- Editorial
- Editorial
- Challenges in the determination of the macroscopic degree of cleanliness determined by ultrasonic immersion testing of (ultra-clean) gear steels
- Determination of prior austenite grain-and martensitic substructure size from metallographic etchings using a multi-step image processing algorithm
- Failure Analysis
- Multiple Drive Shaft Fractures in Lift Oil Pumps
- Picture of the Month
- Picture of the month
- News
- News
- Meeting diary
- Meeting diary
Artikel in diesem Heft
- Contents
- Editorial
- Editorial
- Challenges in the determination of the macroscopic degree of cleanliness determined by ultrasonic immersion testing of (ultra-clean) gear steels
- Determination of prior austenite grain-and martensitic substructure size from metallographic etchings using a multi-step image processing algorithm
- Failure Analysis
- Multiple Drive Shaft Fractures in Lift Oil Pumps
- Picture of the Month
- Picture of the month
- News
- News
- Meeting diary
- Meeting diary
