Quantitative evaluation of the non-uniformity of inclusion distribution in free cutting steel using the Delaunay triangulation method

Delaunay triangulation converts two-dimensional scatter images into statistical data. Parameters derived from the triangulation—such as triangle area, edge length, neighboring triangle area, and neighbor distance—are all related to particle distribution uniformity. In this work, Delaunay triangulation is applied to simulated scatter plots with varying densities and non-uniformity levels to identify an indicator that accurately reflects distribution non-uniformity. Statistical results show that the coefficient of variation of the Delaunay edge lengths ( v d ) sensitively captures differences in non-uniformity while being minimally influenced by areal density, establishing it as a reliable single-value indicator. For MnS inclusions in free-cutting steel, v d exhibits a significant positive correlation between cutting resistance. This a quantitative microstructure-property link, enabling prediction of machining performance from inclusion distribution features.

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Publication Details

Journal
Materials Science and Technology
Published
2026-04-30
DOI
https://doi.org/10.1177/02670836261446121
Primary Topic
Advanced machining processes and optimization
Type
article
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article

Quantitative evaluation of the non-uniformity of inclusion distribution in free cutting steel using the Delaunay triangulation method

Chunlian Yan, Yang Meng, X Y Ju, Naibing Lyu
Materials Science and Technology
Advanced machining processes and optimization
article

Quantitative evaluation of the non-uniformity of inclusion distribution in free cutting steel using the Delaunay triangulation method

Chunlian Yan, Yang Meng, X Y Ju, Naibing Lyu
article en

Abstract

Delaunay triangulation converts two-dimensional scatter images into statistical data. Parameters derived from the triangulation—such as triangle area, edge length, neighboring triangle area, and neighbor distance—are all related to particle distribution uniformity. In this work, Delaunay triangulation is applied to simulated scatter plots with varying densities and non-uniformity levels to identify an indicator that accurately reflects distribution non-uniformity. Statistical results show that the coefficient of variation of the Delaunay edge lengths ( v d ) sensitively captures differences in non-uniformity while being minimally influenced by areal density, establishing it as a reliable single-value indicator. For MnS inclusions in free-cutting steel, v d exhibits a significant positive correlation between cutting resistance. This a quantitative microstructure-property link, enabling prediction of machining performance from inclusion distribution features.

Materials Science and Technology
Shougang Institute of Technology (CN), Beijing Advanced Sciences and Innovation Center (CN)
Openalex Percentile: Top 13%
Advanced machining processes and optimization
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