A random algorithm for 3D modeling of solid particles considering elongation, flatness, sphericity, and convexity
Generating particles with specific shape characteristics is regarded as a critical issue in the research of granular materials. Improving the particle generation method to consider more comprehensive shape descriptors becomes a central challenge in this field. We described a novel solution for param...
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Veröffentlicht in: | Computational particle mechanics 2023-02, Vol.10 (1), p.19-44 |
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creator | Han, Songling Wang, Changming Liu, Xiaoyang Li, Bailong Gao, Ruiyuan Li, Shuo |
description | Generating particles with specific shape characteristics is regarded as a critical issue in the research of granular materials. Improving the particle generation method to consider more comprehensive shape descriptors becomes a central challenge in this field. We described a novel solution for parametrically generate non-convex particles to meet this challenge. First, to conveniently capture particle characteristics, this work established estimation functions of 3D shape parameters (elongation, flatness, sphericity, and convexity). Then, the present study proposed a novel stochastic algorithm for generating non-convex particles. (This algorithm successfully controls the above particle shape parameters.) Finally, this work verified the mechanical properties of the generated particles are similar to those of realistic-shaped particles, by comparing the numerical results of three-dimensional compression of granular materials. The proposed algorithm has a good performance in controlling particle shape parameters and generate particles quickly. |
doi_str_mv | 10.1007/s40571-022-00475-9 |
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Improving the particle generation method to consider more comprehensive shape descriptors becomes a central challenge in this field. We described a novel solution for parametrically generate non-convex particles to meet this challenge. First, to conveniently capture particle characteristics, this work established estimation functions of 3D shape parameters (elongation, flatness, sphericity, and convexity). Then, the present study proposed a novel stochastic algorithm for generating non-convex particles. (This algorithm successfully controls the above particle shape parameters.) Finally, this work verified the mechanical properties of the generated particles are similar to those of realistic-shaped particles, by comparing the numerical results of three-dimensional compression of granular materials. The proposed algorithm has a good performance in controlling particle shape parameters and generate particles quickly.</description><identifier>ISSN: 2196-4378</identifier><identifier>EISSN: 2196-4386</identifier><identifier>DOI: 10.1007/s40571-022-00475-9</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Classical and Continuum Physics ; Computational Science and Engineering ; Convexity ; Elongation ; Engineering ; Flatness ; Granular materials ; Mechanical properties ; Parameters ; Particle shape ; Shape ; Theoretical and Applied Mechanics ; Three dimensional models</subject><ispartof>Computational particle mechanics, 2023-02, Vol.10 (1), p.19-44</ispartof><rights>The Author(s) under exclusive licence to OWZ 2022</rights><rights>The Author(s) under exclusive licence to OWZ 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c385t-8d5811b5dacd5f9174dc09117314f8846b684e9266075cbde5831c06937b4ff13</citedby><cites>FETCH-LOGICAL-c385t-8d5811b5dacd5f9174dc09117314f8846b684e9266075cbde5831c06937b4ff13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40571-022-00475-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40571-022-00475-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Han, Songling</creatorcontrib><creatorcontrib>Wang, Changming</creatorcontrib><creatorcontrib>Liu, Xiaoyang</creatorcontrib><creatorcontrib>Li, Bailong</creatorcontrib><creatorcontrib>Gao, Ruiyuan</creatorcontrib><creatorcontrib>Li, Shuo</creatorcontrib><title>A random algorithm for 3D modeling of solid particles considering elongation, flatness, sphericity, and convexity</title><title>Computational particle mechanics</title><addtitle>Comp. Part. Mech</addtitle><description>Generating particles with specific shape characteristics is regarded as a critical issue in the research of granular materials. Improving the particle generation method to consider more comprehensive shape descriptors becomes a central challenge in this field. We described a novel solution for parametrically generate non-convex particles to meet this challenge. First, to conveniently capture particle characteristics, this work established estimation functions of 3D shape parameters (elongation, flatness, sphericity, and convexity). Then, the present study proposed a novel stochastic algorithm for generating non-convex particles. (This algorithm successfully controls the above particle shape parameters.) Finally, this work verified the mechanical properties of the generated particles are similar to those of realistic-shaped particles, by comparing the numerical results of three-dimensional compression of granular materials. The proposed algorithm has a good performance in controlling particle shape parameters and generate particles quickly.</description><subject>Algorithms</subject><subject>Classical and Continuum Physics</subject><subject>Computational Science and Engineering</subject><subject>Convexity</subject><subject>Elongation</subject><subject>Engineering</subject><subject>Flatness</subject><subject>Granular materials</subject><subject>Mechanical properties</subject><subject>Parameters</subject><subject>Particle shape</subject><subject>Shape</subject><subject>Theoretical and Applied Mechanics</subject><subject>Three dimensional models</subject><issn>2196-4378</issn><issn>2196-4386</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLw0AUhQdRsNT-AVcDbhudybyXpT6h4EbXQzKPNiXJpDOp2H9vYkR3ru69nHvOgQ-Aa4xuMULiLlHEBM5QnmcIUcEydQZmOVY8o0Ty899dyEuwSGmPEMKMCCXJDBxWMBatDQ0s6m2IVb9roA8RknvYBOvqqt3C4GEKdWVhV8S-MrVL0IQ2VdbFUXZ1aLdFX4V2CX1d9K1LaQlTtxtkU_WnJRwKRseH-xzOK3Dhizq5xc-cg_fHh7f1c7Z5fXpZrzaZIZL1mbRMYlwyWxjLvMKCWoMUxoJg6qWkvOSSOpVzjgQzpXVMEmwQV0SU1HtM5uBmyu1iOBxd6vU-HGM7VOpcCIEo5UPYHOTTl4khpei87mLVFPGkMdIjXT3R1QNd_U1Xq8FEJlPqRgIu_kX_4_oCyAZ9Nw</recordid><startdate>20230201</startdate><enddate>20230201</enddate><creator>Han, Songling</creator><creator>Wang, Changming</creator><creator>Liu, Xiaoyang</creator><creator>Li, Bailong</creator><creator>Gao, Ruiyuan</creator><creator>Li, Shuo</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20230201</creationdate><title>A random algorithm for 3D modeling of solid particles considering elongation, flatness, sphericity, and convexity</title><author>Han, Songling ; Wang, Changming ; Liu, Xiaoyang ; Li, Bailong ; Gao, Ruiyuan ; Li, Shuo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c385t-8d5811b5dacd5f9174dc09117314f8846b684e9266075cbde5831c06937b4ff13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Classical and Continuum Physics</topic><topic>Computational Science and Engineering</topic><topic>Convexity</topic><topic>Elongation</topic><topic>Engineering</topic><topic>Flatness</topic><topic>Granular materials</topic><topic>Mechanical properties</topic><topic>Parameters</topic><topic>Particle shape</topic><topic>Shape</topic><topic>Theoretical and Applied Mechanics</topic><topic>Three dimensional models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Han, Songling</creatorcontrib><creatorcontrib>Wang, Changming</creatorcontrib><creatorcontrib>Liu, Xiaoyang</creatorcontrib><creatorcontrib>Li, Bailong</creatorcontrib><creatorcontrib>Gao, Ruiyuan</creatorcontrib><creatorcontrib>Li, Shuo</creatorcontrib><collection>CrossRef</collection><jtitle>Computational particle mechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Han, Songling</au><au>Wang, Changming</au><au>Liu, Xiaoyang</au><au>Li, Bailong</au><au>Gao, Ruiyuan</au><au>Li, Shuo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A random algorithm for 3D modeling of solid particles considering elongation, flatness, sphericity, and convexity</atitle><jtitle>Computational particle mechanics</jtitle><stitle>Comp. Part. Mech</stitle><date>2023-02-01</date><risdate>2023</risdate><volume>10</volume><issue>1</issue><spage>19</spage><epage>44</epage><pages>19-44</pages><issn>2196-4378</issn><eissn>2196-4386</eissn><abstract>Generating particles with specific shape characteristics is regarded as a critical issue in the research of granular materials. Improving the particle generation method to consider more comprehensive shape descriptors becomes a central challenge in this field. We described a novel solution for parametrically generate non-convex particles to meet this challenge. First, to conveniently capture particle characteristics, this work established estimation functions of 3D shape parameters (elongation, flatness, sphericity, and convexity). Then, the present study proposed a novel stochastic algorithm for generating non-convex particles. (This algorithm successfully controls the above particle shape parameters.) Finally, this work verified the mechanical properties of the generated particles are similar to those of realistic-shaped particles, by comparing the numerical results of three-dimensional compression of granular materials. The proposed algorithm has a good performance in controlling particle shape parameters and generate particles quickly.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s40571-022-00475-9</doi><tpages>26</tpages></addata></record> |
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subjects | Algorithms Classical and Continuum Physics Computational Science and Engineering Convexity Elongation Engineering Flatness Granular materials Mechanical properties Parameters Particle shape Shape Theoretical and Applied Mechanics Three dimensional models |
title | A random algorithm for 3D modeling of solid particles considering elongation, flatness, sphericity, and convexity |
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