Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying
In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of sc...
Ausführliche Beschreibung
Autor*in: |
Changpu Shen [verfasserIn] Yongxiang Li [verfasserIn] Xuemeng Xu [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2021 |
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Übergeordnetes Werk: |
In: Journal of Engineering - Hindawi Limited, 2013, (2021) |
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Übergeordnetes Werk: |
year:2021 |
Links: |
Link aufrufen |
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DOI / URN: |
10.1155/2021/6671511 |
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Katalog-ID: |
DOAJ062157876 |
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520 | |a In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. | ||
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10.1155/2021/6671511 doi (DE-627)DOAJ062157876 (DE-599)DOAJ2836081620594da3a8e837b686ad0350 DE-627 ger DE-627 rakwb eng TA1-2040 Changpu Shen verfasserin aut Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. Engineering (General). Civil engineering (General) Yongxiang Li verfasserin aut Xuemeng Xu verfasserin aut In Journal of Engineering Hindawi Limited, 2013 (2021) (DE-627)770026338 (DE-600)2736230-9 23144912 nnns year:2021 https://doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/article/2836081620594da3a8e837b686ad0350 kostenfrei http://dx.doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/toc/2314-4904 Journal toc kostenfrei https://doaj.org/toc/2314-4912 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2021 |
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10.1155/2021/6671511 doi (DE-627)DOAJ062157876 (DE-599)DOAJ2836081620594da3a8e837b686ad0350 DE-627 ger DE-627 rakwb eng TA1-2040 Changpu Shen verfasserin aut Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. Engineering (General). Civil engineering (General) Yongxiang Li verfasserin aut Xuemeng Xu verfasserin aut In Journal of Engineering Hindawi Limited, 2013 (2021) (DE-627)770026338 (DE-600)2736230-9 23144912 nnns year:2021 https://doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/article/2836081620594da3a8e837b686ad0350 kostenfrei http://dx.doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/toc/2314-4904 Journal toc kostenfrei https://doaj.org/toc/2314-4912 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2021 |
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10.1155/2021/6671511 doi (DE-627)DOAJ062157876 (DE-599)DOAJ2836081620594da3a8e837b686ad0350 DE-627 ger DE-627 rakwb eng TA1-2040 Changpu Shen verfasserin aut Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. Engineering (General). Civil engineering (General) Yongxiang Li verfasserin aut Xuemeng Xu verfasserin aut In Journal of Engineering Hindawi Limited, 2013 (2021) (DE-627)770026338 (DE-600)2736230-9 23144912 nnns year:2021 https://doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/article/2836081620594da3a8e837b686ad0350 kostenfrei http://dx.doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/toc/2314-4904 Journal toc kostenfrei https://doaj.org/toc/2314-4912 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2021 |
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10.1155/2021/6671511 doi (DE-627)DOAJ062157876 (DE-599)DOAJ2836081620594da3a8e837b686ad0350 DE-627 ger DE-627 rakwb eng TA1-2040 Changpu Shen verfasserin aut Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. Engineering (General). Civil engineering (General) Yongxiang Li verfasserin aut Xuemeng Xu verfasserin aut In Journal of Engineering Hindawi Limited, 2013 (2021) (DE-627)770026338 (DE-600)2736230-9 23144912 nnns year:2021 https://doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/article/2836081620594da3a8e837b686ad0350 kostenfrei http://dx.doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/toc/2314-4904 Journal toc kostenfrei https://doaj.org/toc/2314-4912 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2021 |
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10.1155/2021/6671511 doi (DE-627)DOAJ062157876 (DE-599)DOAJ2836081620594da3a8e837b686ad0350 DE-627 ger DE-627 rakwb eng TA1-2040 Changpu Shen verfasserin aut Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. Engineering (General). Civil engineering (General) Yongxiang Li verfasserin aut Xuemeng Xu verfasserin aut In Journal of Engineering Hindawi Limited, 2013 (2021) (DE-627)770026338 (DE-600)2736230-9 23144912 nnns year:2021 https://doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/article/2836081620594da3a8e837b686ad0350 kostenfrei http://dx.doi.org/10.1155/2021/6671511 kostenfrei https://doaj.org/toc/2314-4904 Journal toc kostenfrei https://doaj.org/toc/2314-4912 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2021 |
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TA1-2040 Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying |
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Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying |
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Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying |
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calibration of discrete element simulation parameters for powder screw conveying |
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Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying |
abstract |
In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. |
abstractGer |
In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. |
abstract_unstemmed |
In order to obtain the accurate contact parameters in the simulation process of powder screw conveying, this paper took wheat flour as an example, based on the discrete element JKR (Johnson-Kendall-Roberts) contact model, and directly calibrated the simulation contact parameters in the process of screw conveying in response to the mass flow rate of wheat flour. Firstly, the simulation density of wheat flour particles was calibrated, and the simulation density of wheat flour particles was 1320 kg/m. Then, Plackett-Burman experiment was used to screen out the parameters that had significant influence on the mass flow rate: surface energy JKR, coefficient of static friction between wheat flour and wheat flour, and the coefficient of static friction between wheat flour and stainless steel. The second-order regression model of mass flow rate and significance parameters was established and optimized based on Box-Behnken experiment, and the optimal combination of significance parameters: JKR was obtained to be 0.364; the static friction coefficient of wheat flour to wheat flour was 0.437; and the static friction coefficient of wheat flour to stainless steel was 0.609. Finally, the calibration parameters were used for simulation. By comparing the mass flow rate of simulation and experiment, the relative error of the two was 1.37%. The simulation and experiment flow rate values at different rotating speeds (60 r/min, 80 r/min, 100 r/min, 120 r/min, and 140 r/min) were further compared, and the errors were all within 3%. The method of directly calibrating the simulation contact parameters through the screw conveying process can improve the accuracy of screw conveying simulation, and providing a method and basis for powder contact parameters calibration and screw conveying simulation of wheat flour. |
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Calibration of Discrete Element Simulation Parameters for Powder Screw Conveying |
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https://doi.org/10.1155/2021/6671511 https://doaj.org/article/2836081620594da3a8e837b686ad0350 http://dx.doi.org/10.1155/2021/6671511 https://doaj.org/toc/2314-4904 https://doaj.org/toc/2314-4912 |
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