Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering
Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanica...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ivannikov, V. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Computational particle mechanics - Berlin : Springer, 2014, 10(2022), 2 vom: 21. Juni, Seite 185-207 |
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| Übergeordnetes Werk: |
volume:10 ; year:2022 ; number:2 ; day:21 ; month:06 ; pages:185-207 |
| Links: |
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| DOI / URN: |
10.1007/s40571-022-00486-6 |
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| Katalog-ID: |
SPR049479458 |
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| 520 | |a Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. | ||
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| 650 | 4 | |a Modeling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Powder processing |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Thomsen, F. |4 aut | |
| 700 | 1 | |a Ebel, T. |4 aut | |
| 700 | 1 | |a Willumeit–Römer, R. |4 aut | |
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10.1007/s40571-022-00486-6 doi (DE-627)SPR049479458 (SPR)s40571-022-00486-6-e DE-627 ger DE-627 rakwb eng Ivannikov, V. verfasserin (orcid)0000-0002-4311-7482 aut Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. Sintering (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Finite element method (dpeaa)DE-He213 Modeling (dpeaa)DE-He213 Powder processing (dpeaa)DE-He213 Thomsen, F. aut Ebel, T. aut Willumeit–Römer, R. aut Enthalten in Computational particle mechanics Berlin : Springer, 2014 10(2022), 2 vom: 21. Juni, Seite 185-207 (DE-627)780378857 (DE-600)2760376-3 2196-4386 nnns volume:10 year:2022 number:2 day:21 month:06 pages:185-207 https://dx.doi.org/10.1007/s40571-022-00486-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 10 2022 2 21 06 185-207 |
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10.1007/s40571-022-00486-6 doi (DE-627)SPR049479458 (SPR)s40571-022-00486-6-e DE-627 ger DE-627 rakwb eng Ivannikov, V. verfasserin (orcid)0000-0002-4311-7482 aut Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. Sintering (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Finite element method (dpeaa)DE-He213 Modeling (dpeaa)DE-He213 Powder processing (dpeaa)DE-He213 Thomsen, F. aut Ebel, T. aut Willumeit–Römer, R. aut Enthalten in Computational particle mechanics Berlin : Springer, 2014 10(2022), 2 vom: 21. Juni, Seite 185-207 (DE-627)780378857 (DE-600)2760376-3 2196-4386 nnns volume:10 year:2022 number:2 day:21 month:06 pages:185-207 https://dx.doi.org/10.1007/s40571-022-00486-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 10 2022 2 21 06 185-207 |
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10.1007/s40571-022-00486-6 doi (DE-627)SPR049479458 (SPR)s40571-022-00486-6-e DE-627 ger DE-627 rakwb eng Ivannikov, V. verfasserin (orcid)0000-0002-4311-7482 aut Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. Sintering (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Finite element method (dpeaa)DE-He213 Modeling (dpeaa)DE-He213 Powder processing (dpeaa)DE-He213 Thomsen, F. aut Ebel, T. aut Willumeit–Römer, R. aut Enthalten in Computational particle mechanics Berlin : Springer, 2014 10(2022), 2 vom: 21. Juni, Seite 185-207 (DE-627)780378857 (DE-600)2760376-3 2196-4386 nnns volume:10 year:2022 number:2 day:21 month:06 pages:185-207 https://dx.doi.org/10.1007/s40571-022-00486-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 10 2022 2 21 06 185-207 |
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10.1007/s40571-022-00486-6 doi (DE-627)SPR049479458 (SPR)s40571-022-00486-6-e DE-627 ger DE-627 rakwb eng Ivannikov, V. verfasserin (orcid)0000-0002-4311-7482 aut Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. Sintering (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Finite element method (dpeaa)DE-He213 Modeling (dpeaa)DE-He213 Powder processing (dpeaa)DE-He213 Thomsen, F. aut Ebel, T. aut Willumeit–Römer, R. aut Enthalten in Computational particle mechanics Berlin : Springer, 2014 10(2022), 2 vom: 21. Juni, Seite 185-207 (DE-627)780378857 (DE-600)2760376-3 2196-4386 nnns volume:10 year:2022 number:2 day:21 month:06 pages:185-207 https://dx.doi.org/10.1007/s40571-022-00486-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 10 2022 2 21 06 185-207 |
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10.1007/s40571-022-00486-6 doi (DE-627)SPR049479458 (SPR)s40571-022-00486-6-e DE-627 ger DE-627 rakwb eng Ivannikov, V. verfasserin (orcid)0000-0002-4311-7482 aut Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. Sintering (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Finite element method (dpeaa)DE-He213 Modeling (dpeaa)DE-He213 Powder processing (dpeaa)DE-He213 Thomsen, F. aut Ebel, T. aut Willumeit–Römer, R. aut Enthalten in Computational particle mechanics Berlin : Springer, 2014 10(2022), 2 vom: 21. Juni, Seite 185-207 (DE-627)780378857 (DE-600)2760376-3 2196-4386 nnns volume:10 year:2022 number:2 day:21 month:06 pages:185-207 https://dx.doi.org/10.1007/s40571-022-00486-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 10 2022 2 21 06 185-207 |
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Enthalten in Computational particle mechanics 10(2022), 2 vom: 21. Juni, Seite 185-207 volume:10 year:2022 number:2 day:21 month:06 pages:185-207 |
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Ivannikov, V. @@aut@@ Thomsen, F. @@aut@@ Ebel, T. @@aut@@ Willumeit–Römer, R. @@aut@@ |
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Ivannikov, V. |
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Ivannikov, V. misc Sintering misc Discrete element method misc Finite element method misc Modeling misc Powder processing Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering |
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Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering Sintering (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Finite element method (dpeaa)DE-He213 Modeling (dpeaa)DE-He213 Powder processing (dpeaa)DE-He213 |
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Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering |
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Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering |
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Ivannikov, V. |
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Computational particle mechanics |
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Ivannikov, V. Thomsen, F. Ebel, T. Willumeit–Römer, R. |
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coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering |
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Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering |
| abstract |
Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. © The Author(s) 2022 |
| abstractGer |
Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. © The Author(s) 2022 |
| abstract_unstemmed |
Abstract A novel discrete element method-based approach for modeling of solid state sintering of spherical metallic powder is presented. It tackles the interplay between the thermodynamical mass transport effects arising in the vicinity of the grain boundary between the particles and their mechanical interaction. To deal with the former, an elementary model is used that describes the behavior of the matter flow at the grain boundary such that neck growth and shrinkage are properly captured. The model solves a set of partial differential equations which drive the changes of the corresponding geometry parameters. Their evolution is transformed into the equivalent normal sintering force arising in each sinter neck. To capture the mechanical interaction of particles due to their rearrangement resulting from the geometry changes of each individual contact, the entire assembly is modeled as an assembly of 2-nodal structural elements with 6 degrees of freedom per node. The stiffness properties are estimated employing the approximations from the bonded DEM. The numerical implementation then constitutes a two-step staggered solution scheme, where these models are applied sequentially. The performed benchmarks reveal the plausibility of the proposed approach and exhibit good agreement of both neck growth and shrinkage rates obtained in the numerical simulations with the experimental data. © The Author(s) 2022 |
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| title_short |
Coupling the discrete element method and solid state diffusion equations for modeling of metallic powders sintering |
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https://dx.doi.org/10.1007/s40571-022-00486-6 |
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| author2 |
Thomsen, F. Ebel, T. Willumeit–Römer, R. |
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Thomsen, F. Ebel, T. Willumeit–Römer, R. |
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| doi_str |
10.1007/s40571-022-00486-6 |
| up_date |
2024-07-04T00:58:58.375Z |
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| score |
7.4004498 |