Staff View: Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements

Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements

This work presents a study on the correlation between the crystallographic texture and the pitting corrosion susceptibility of API 5L steels. The crystallographic textures of API 5L steel samples (codified as S1, S2, S3, and S4) were studied using EBSD measurements. A deterministic model based on sy...

Full description

Saved in:

Bibliographic Details
Main Authors:	L.Hernández-Maya, E.M.Arce-Estrada, M.Corrales-Luna, J.M.Hallen, Le ManhTu
Format:	Bài trích
Language:	English
Published:	Elsevier 2022
Subjects:	Predicting average Microtexture measurements
Online Access:	https://www.sciencedirect.com/science/article/abs/pii/S246802302200267X?via%3Dihub https://dlib.phenikaa-uni.edu.vn/handle/PNK/5933 https://doi.org/10.1016/j.surfin.2022.101999
Tags:	Add Tag No Tags, Be the first to tag this record!

id	oai:localhost:PNK-5933
record_format	dspace
spelling	oai:localhost:PNK-59332022-08-17T05:54:56Z Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements L.Hernández-Maya E.M.Arce-Estrada M.Corrales-Luna J.M.Hallen Le ManhTu Predicting average Microtexture measurements This work presents a study on the correlation between the crystallographic texture and the pitting corrosion susceptibility of API 5L steels. The crystallographic textures of API 5L steel samples (codified as S1, S2, S3, and S4) were studied using EBSD measurements. A deterministic model based on symmetric spherical surface harmonics was proposed to describe the strong dependence of the pitting corrosion susceptibility on the crystallographic (grains) orientation of the (body-centered cubic) material. Using the model, pitting corrosion susceptibility index values estimated from EBSD raw data agreed in relative magnitudes (from sample to sample) with the predictions made from X-ray macrotexture measurements, and the results derived from other techniques such as cyclic polarization tests and analyses of SEM and AFM images. This agreement verified the capacity of EBSD to estimate the pitting corrosion susceptibility indices of carbon steels having different microstructures and textures, which were found to be 0.60, 0.53, 0.51, and 0.44 for S1, S2, S3, and S4, respectively. It was established that the higher the values of pitting corrosion susceptibility indices, the higher the tendency to present pitting corrosion of the material; thus, S1>S2>S3>S4. Moreover, the results have shown that the crystallographic texture plays a more decisive role in the behaviour of pitting corrosion in carbon steels compared to other microstructural and chemical parameters such as the grain size and inclusion content. The proposed (deterministic) model could be a novel tool for predicting pitting corrosion of the material, forming part of a novel method for the material selection process. 2022-07-13T01:59:59Z 2022-07-13T01:59:59Z 2022 Bài trích https://www.sciencedirect.com/science/article/abs/pii/S246802302200267X?via%3Dihub https://dlib.phenikaa-uni.edu.vn/handle/PNK/5933 https://doi.org/10.1016/j.surfin.2022.101999 en Elsevier
institution	Digital Phenikaa
collection	Digital Phenikaa
language	English
topic	Predicting average Microtexture measurements
spellingShingle	Predicting average Microtexture measurements L.Hernández-Maya E.M.Arce-Estrada M.Corrales-Luna J.M.Hallen Le ManhTu Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements
description	This work presents a study on the correlation between the crystallographic texture and the pitting corrosion susceptibility of API 5L steels. The crystallographic textures of API 5L steel samples (codified as S1, S2, S3, and S4) were studied using EBSD measurements. A deterministic model based on symmetric spherical surface harmonics was proposed to describe the strong dependence of the pitting corrosion susceptibility on the crystallographic (grains) orientation of the (body-centered cubic) material. Using the model, pitting corrosion susceptibility index values estimated from EBSD raw data agreed in relative magnitudes (from sample to sample) with the predictions made from X-ray macrotexture measurements, and the results derived from other techniques such as cyclic polarization tests and analyses of SEM and AFM images. This agreement verified the capacity of EBSD to estimate the pitting corrosion susceptibility indices of carbon steels having different microstructures and textures, which were found to be 0.60, 0.53, 0.51, and 0.44 for S1, S2, S3, and S4, respectively. It was established that the higher the values of pitting corrosion susceptibility indices, the higher the tendency to present pitting corrosion of the material; thus, S1>S2>S3>S4. Moreover, the results have shown that the crystallographic texture plays a more decisive role in the behaviour of pitting corrosion in carbon steels compared to other microstructural and chemical parameters such as the grain size and inclusion content. The proposed (deterministic) model could be a novel tool for predicting pitting corrosion of the material, forming part of a novel method for the material selection process.
format	Bài trích
author	L.Hernández-Maya E.M.Arce-Estrada M.Corrales-Luna J.M.Hallen Le ManhTu
author_facet	L.Hernández-Maya E.M.Arce-Estrada M.Corrales-Luna J.M.Hallen Le ManhTu
author_sort	L.Hernández-Maya
title	Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements
title_short	Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements
title_full	Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements
title_fullStr	Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements
title_full_unstemmed	Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements
title_sort	symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from ebsd microtexture measurements
publisher	Elsevier
publishDate	2022
url	https://www.sciencedirect.com/science/article/abs/pii/S246802302200267X?via%3Dihub https://dlib.phenikaa-uni.edu.vn/handle/PNK/5933 https://doi.org/10.1016/j.surfin.2022.101999
_version_	1751856289188675584
score	8.881002

Symmetric spherical surface harmonics for predicting average pitting corrosion susceptibility index of carbon steels from EBSD microtexture measurements

Similar Items