Stochastic Simulation Model of Surface Microrelief after Machining with an Abrasive Tool

The article presents a stochastic simulation model of surface microrelief formation after abrasive machining. The model considers the shape and dimensions of abrasive grains, their stochastic distribution, and kinematic parameters. The calculations are implemented in the MATLAB environment in the form of a height matrix generated by superimposing individual slices. Analytical dependences for calculating slice geometry depending on the grain shape and cutting depth are presented. The results of the simulation provide a visualization of the surface and an estimation of roughness parameter Sa. The model is applicable for predicting machining quality and optimizing process modes.

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Publication Details

Journal
Russian Engineering Research
Published
2025-10-01
DOI
https://doi.org/10.3103/s1068798x25702223
Primary Topic
Mechanical Systems and Engineering
Type
article
Field-Weighted Citation Impact
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article

Stochastic Simulation Model of Surface Microrelief after Machining with an Abrasive Tool

Ф. В. Гречников, Pavel Melnikov, А. Н. Попов, И. Н. Бобровский
Russian Engineering Research
Mechanical Systems and Engineering
article

Stochastic Simulation Model of Surface Microrelief after Machining with an Abrasive Tool

Ф. В. Гречников, Pavel Melnikov, А. Н. Попов, И. Н. Бобровский
article en

Abstract

The article presents a stochastic simulation model of surface microrelief formation after abrasive machining. The model considers the shape and dimensions of abrasive grains, their stochastic distribution, and kinematic parameters. The calculations are implemented in the MATLAB environment in the form of a height matrix generated by superimposing individual slices. Analytical dependences for calculating slice geometry depending on the grain shape and cutting depth are presented. The results of the simulation provide a visualization of the surface and an estimation of roughness parameter Sa. The model is applicable for predicting machining quality and optimizing process modes.

Russian Engineering ResearchVol. 45(10)
Togliatti State University (RU), Samara Federal Research Scientific Center (RU)
Openalex Percentile: Top 73%
Mechanical Systems and Engineering
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