Computational Cost Reduction and Validation of Cluster-Cluster Aggregation Model
This study introduces a new collision detection method obtained by modifying the grid partitioning method, which employs spatial- and cell-partitioning, into an aggregate mean free path-cluster-cluster aggregation (AMP-CCA) model. This modification allows the AMP-CCA model to calculate the three-dim...
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| Veröffentlicht in: | Funtai Kogakkaishi 2014-01, Vol.52 (8), p.426-434 |
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| container_title | Funtai Kogakkaishi |
| container_volume | 52 |
| creator | Ono, Kiminori Matsukawa, Yoshiya Watanabe, Aki Dewa, Kazuki Saito, Yasuhiro Matshushita, Yohsuke Aoki, Hideyuki Era, Koki Aoki, Takayuki Yamaguchi, Togo |
| description | This study introduces a new collision detection method obtained by modifying the grid partitioning method, which employs spatial- and cell-partitioning, into an aggregate mean free path-cluster-cluster aggregation (AMP-CCA) model. This modification allows the AMP-CCA model to calculate the three-dimensional aggregate morphology and particle size distributions (PSDs) with computational efficiency. As compared with the previous model, the new model successfully calculates the morphology in 15% of the computational time. The calculated PSDs for a coalesced spherical particle aggregate, as calculated by the AMP-CCA model, are in reasonable agreement with the results of the sectional model regardless of concentration. The morphology calculated by the AMP-CCA model is in good agreement with previous experimental and numerical results. The AMP-CCA model, employing direct Monte Carlo simulation, serves as a useful tool to calculate the aggregate morphology and PSDs with reasonable accuracy. |
| format | Article |
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This modification allows the AMP-CCA model to calculate the three-dimensional aggregate morphology and particle size distributions (PSDs) with computational efficiency. As compared with the previous model, the new model successfully calculates the morphology in 15% of the computational time. The calculated PSDs for a coalesced spherical particle aggregate, as calculated by the AMP-CCA model, are in reasonable agreement with the results of the sectional model regardless of concentration. The morphology calculated by the AMP-CCA model is in good agreement with previous experimental and numerical results. The AMP-CCA model, employing direct Monte Carlo simulation, serves as a useful tool to calculate the aggregate morphology and PSDs with reasonable accuracy.</description><identifier>ISSN: 0386-6157</identifier><identifier>EISSN: 1883-7239</identifier><language>eng</language><subject>Accuracy ; Agglomeration ; Aggregates ; Computational efficiency ; Computer simulation ; Mathematical models ; Morphology ; Powder technology</subject><ispartof>Funtai Kogakkaishi, 2014-01, Vol.52 (8), p.426-434</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Ono, Kiminori</creatorcontrib><creatorcontrib>Matsukawa, Yoshiya</creatorcontrib><creatorcontrib>Watanabe, Aki</creatorcontrib><creatorcontrib>Dewa, Kazuki</creatorcontrib><creatorcontrib>Saito, Yasuhiro</creatorcontrib><creatorcontrib>Matshushita, Yohsuke</creatorcontrib><creatorcontrib>Aoki, Hideyuki</creatorcontrib><creatorcontrib>Era, Koki</creatorcontrib><creatorcontrib>Aoki, Takayuki</creatorcontrib><creatorcontrib>Yamaguchi, Togo</creatorcontrib><title>Computational Cost Reduction and Validation of Cluster-Cluster Aggregation Model</title><title>Funtai Kogakkaishi</title><description>This study introduces a new collision detection method obtained by modifying the grid partitioning method, which employs spatial- and cell-partitioning, into an aggregate mean free path-cluster-cluster aggregation (AMP-CCA) model. This modification allows the AMP-CCA model to calculate the three-dimensional aggregate morphology and particle size distributions (PSDs) with computational efficiency. As compared with the previous model, the new model successfully calculates the morphology in 15% of the computational time. The calculated PSDs for a coalesced spherical particle aggregate, as calculated by the AMP-CCA model, are in reasonable agreement with the results of the sectional model regardless of concentration. The morphology calculated by the AMP-CCA model is in good agreement with previous experimental and numerical results. 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| identifier | ISSN: 0386-6157 |
| ispartof | Funtai Kogakkaishi, 2014-01, Vol.52 (8), p.426-434 |
| issn | 0386-6157 1883-7239 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1800438137 |
| source | EZB-FREE-00999 freely available EZB journals |
| subjects | Accuracy Agglomeration Aggregates Computational efficiency Computer simulation Mathematical models Morphology Powder technology |
| title | Computational Cost Reduction and Validation of Cluster-Cluster Aggregation Model |
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