Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test
Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In thi...
Ausführliche Beschreibung
Autor*in: |
Guichuan Li [verfasserIn] Haiyu Li [verfasserIn] Xuan Li [verfasserIn] Zhichao Gong [verfasserIn] Qinghua Yang [verfasserIn] Yuxiang Huang [verfasserIn] Zuoli Fu [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Übergeordnetes Werk: |
In: Agriculture - MDPI AG, 2012, 13(2023), 5, p 1024 |
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Übergeordnetes Werk: |
volume:13 ; year:2023 ; number:5, p 1024 |
Links: |
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DOI / URN: |
10.3390/agriculture13051024 |
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Katalog-ID: |
DOAJ094435715 |
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520 | |a Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. | ||
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10.3390/agriculture13051024 doi (DE-627)DOAJ094435715 (DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa DE-627 ger DE-627 rakwb eng S1-972 Guichuan Li verfasserin aut Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. buckwheat seeds discrete element parameter calibration DEM seed metering Agriculture (General) Haiyu Li verfasserin aut Xuan Li verfasserin aut Zhichao Gong verfasserin aut Qinghua Yang verfasserin aut Yuxiang Huang verfasserin aut Zuoli Fu verfasserin aut In Agriculture MDPI AG, 2012 13(2023), 5, p 1024 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:13 year:2023 number:5, p 1024 https://doi.org/10.3390/agriculture13051024 kostenfrei https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa kostenfrei https://www.mdpi.com/2077-0472/13/5/1024 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 13 2023 5, p 1024 |
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10.3390/agriculture13051024 doi (DE-627)DOAJ094435715 (DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa DE-627 ger DE-627 rakwb eng S1-972 Guichuan Li verfasserin aut Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. buckwheat seeds discrete element parameter calibration DEM seed metering Agriculture (General) Haiyu Li verfasserin aut Xuan Li verfasserin aut Zhichao Gong verfasserin aut Qinghua Yang verfasserin aut Yuxiang Huang verfasserin aut Zuoli Fu verfasserin aut In Agriculture MDPI AG, 2012 13(2023), 5, p 1024 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:13 year:2023 number:5, p 1024 https://doi.org/10.3390/agriculture13051024 kostenfrei https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa kostenfrei https://www.mdpi.com/2077-0472/13/5/1024 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 13 2023 5, p 1024 |
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10.3390/agriculture13051024 doi (DE-627)DOAJ094435715 (DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa DE-627 ger DE-627 rakwb eng S1-972 Guichuan Li verfasserin aut Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. buckwheat seeds discrete element parameter calibration DEM seed metering Agriculture (General) Haiyu Li verfasserin aut Xuan Li verfasserin aut Zhichao Gong verfasserin aut Qinghua Yang verfasserin aut Yuxiang Huang verfasserin aut Zuoli Fu verfasserin aut In Agriculture MDPI AG, 2012 13(2023), 5, p 1024 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:13 year:2023 number:5, p 1024 https://doi.org/10.3390/agriculture13051024 kostenfrei https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa kostenfrei https://www.mdpi.com/2077-0472/13/5/1024 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 13 2023 5, p 1024 |
allfieldsGer |
10.3390/agriculture13051024 doi (DE-627)DOAJ094435715 (DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa DE-627 ger DE-627 rakwb eng S1-972 Guichuan Li verfasserin aut Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. buckwheat seeds discrete element parameter calibration DEM seed metering Agriculture (General) Haiyu Li verfasserin aut Xuan Li verfasserin aut Zhichao Gong verfasserin aut Qinghua Yang verfasserin aut Yuxiang Huang verfasserin aut Zuoli Fu verfasserin aut In Agriculture MDPI AG, 2012 13(2023), 5, p 1024 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:13 year:2023 number:5, p 1024 https://doi.org/10.3390/agriculture13051024 kostenfrei https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa kostenfrei https://www.mdpi.com/2077-0472/13/5/1024 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 13 2023 5, p 1024 |
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10.3390/agriculture13051024 doi (DE-627)DOAJ094435715 (DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa DE-627 ger DE-627 rakwb eng S1-972 Guichuan Li verfasserin aut Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. buckwheat seeds discrete element parameter calibration DEM seed metering Agriculture (General) Haiyu Li verfasserin aut Xuan Li verfasserin aut Zhichao Gong verfasserin aut Qinghua Yang verfasserin aut Yuxiang Huang verfasserin aut Zuoli Fu verfasserin aut In Agriculture MDPI AG, 2012 13(2023), 5, p 1024 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:13 year:2023 number:5, p 1024 https://doi.org/10.3390/agriculture13051024 kostenfrei https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa kostenfrei https://www.mdpi.com/2077-0472/13/5/1024 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 13 2023 5, p 1024 |
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Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test |
abstract |
Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. |
abstractGer |
Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. |
abstract_unstemmed |
Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ094435715</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240413034948.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240413s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/agriculture13051024</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ094435715</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">S1-972</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Guichuan Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">buckwheat seeds</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">discrete element parameter calibration</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">DEM</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">seed metering</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Agriculture (General)</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Haiyu Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xuan Li</subfield><subfield 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