UNS S32304 duplex stainless steel metallography image processing and analysis.

Name: Carlos Alberto Rosa Neto
Type: MSc dissertation
Publication date: 17/06/2020

Namesort descending Role
Marcos Tadeu DAzeredo Orlando Advisor *

Examining board:

Namesort descending Role
Carlos Augusto Cardoso Passos External Examiner *
Cherlio Scandian External Examiner *
Estefano Aparecido Vieira External Examiner *
Marcos Tadeu DAzeredo Orlando Advisor *

Summary: The evolution of electronic systems for image acquisition, registration, processing and visualization and the integration in computer systems, has been increasing its application in an extraordinary way in association with experimental techniques that use the image as a primary source of experimental information and / or as a way main part of your resentation. This integration allows the most effective exploration of the
available information, extracting qualitative and quantitative results from images acquired from optical microscopy and scanning electron. For this purpose, Digital Image Processing and Analysis (PADI) has been developed and has been increasingly used to streamline processes, increase the accuracy, safety and reliability of data extracted from images in the most diverse areas of research. In the present work all
the steps of PADI are explained and applied in the metallographic analysis and quantitative stereology of nitrides and microstructure of a duplex stainless steel UNS S32304, which underwent nine conditions of thermomechanical treatment at 700ºC varying time and strain rates. The metallographic images were obtained by optical microscopy and scanning electron and all processing and data extracted from the micrographs took place through the free software FIJI (ImageJ). The results obtained
using PADI and free software were compared with analyzes performed by manual counting of the ASTM standard, the Backscattered Electron Diffraction technique (EBSD) and X-Ray Diffraction (DRX). As a conclusion, it was verified that the automatic image processing using the FIJI is an optimized process and with scientific reliability, and the Bernsen and Sauvola segmentation techniques ideal for phase and nitride
quantification, respectively.

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