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 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. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Guichuan Li [verfasserIn] Haiyu Li [verfasserIn] Xuan Li [verfasserIn] Zhichao Gong [verfasserIn] Qinghua Yang [verfasserIn] Yuxiang Huang [verfasserIn] Zuoli Fu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	buckwheat seeds discrete element parameter calibration DEM seed metering

Übergeordnetes Werk:	In: Agriculture - MDPI AG, 2012, 13(2023), 5, p 1024
Übergeordnetes Werk:	volume:13 ; year:2023 ; number:5, p 1024

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/agriculture13051024

Katalog-ID:	DOAJ094435715

Internformat


LEADER	01000naa a22002652 4500
001	DOAJ094435715
003	DE-627
005	20240413034948.0
007	cr uuu---uuuuu
008	240413s2023 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.3390/agriculture13051024 \|2 doi
035			\|a (DE-627)DOAJ094435715
035			\|a (DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a S1-972
100	0		\|a Guichuan Li \|e verfasserin \|4 aut
245	1	0	\|a Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test
264		1	\|c 2023
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
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.
650		4	\|a buckwheat seeds
650		4	\|a discrete element parameter calibration
650		4	\|a DEM
650		4	\|a seed metering
653		0	\|a Agriculture (General)
700	0		\|a Haiyu Li \|e verfasserin \|4 aut
700	0		\|a Xuan Li \|e verfasserin \|4 aut
700	0		\|a Zhichao Gong \|e verfasserin \|4 aut
700	0		\|a Qinghua Yang \|e verfasserin \|4 aut
700	0		\|a Yuxiang Huang \|e verfasserin \|4 aut
700	0		\|a Zuoli Fu \|e verfasserin \|4 aut
773	0	8	\|i In \|t Agriculture \|d MDPI AG, 2012 \|g 13(2023), 5, p 1024 \|w (DE-627)686948173 \|w (DE-600)2651678-0 \|x 20770472 \|7 nnns
773	1	8	\|g volume:13 \|g year:2023 \|g number:5, p 1024
856	4	0	\|u https://doi.org/10.3390/agriculture13051024 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa \|z kostenfrei
856	4	0	\|u https://www.mdpi.com/2077-0472/13/5/1024 \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2077-0472 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 13 \|j 2023 \|e 5, p 1024

Indexfelder

author_variant	g l gl h l hl x l xl z g zg q y qy y h yh z f zf
matchkey_str	article:20770472:2023----::salsmnadairtoodsrteeetoefrukhasebsdnttc
hierarchy_sort_str	2023
callnumber-subject-code	S
publishDate	2023
allfields	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
spelling	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
allfields_unstemmed	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
allfieldsSound	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
language	English
source	In Agriculture 13(2023), 5, p 1024 volume:13 year:2023 number:5, p 1024
sourceStr	In Agriculture 13(2023), 5, p 1024 volume:13 year:2023 number:5, p 1024
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	buckwheat seeds discrete element parameter calibration DEM seed metering Agriculture (General)
isfreeaccess_bool	true
container_title	Agriculture
authorswithroles_txt_mv	Guichuan Li @@aut@@ Haiyu Li @@aut@@ Xuan Li @@aut@@ Zhichao Gong @@aut@@ Qinghua Yang @@aut@@ Yuxiang Huang @@aut@@ Zuoli Fu @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	686948173
id	DOAJ094435715
language_de	englisch
fullrecord	<?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 code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Zhichao Gong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qinghua Yang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yuxiang Huang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Zuoli Fu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Agriculture</subfield><subfield code="d">MDPI AG, 2012</subfield><subfield code="g">13(2023), 5, p 1024</subfield><subfield code="w">(DE-627)686948173</subfield><subfield code="w">(DE-600)2651678-0</subfield><subfield code="x">20770472</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:13</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:5, p 1024</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/agriculture13051024</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2077-0472/13/5/1024</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2077-0472</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">13</subfield><subfield code="j">2023</subfield><subfield code="e">5, p 1024</subfield></datafield></record></collection>
callnumber-first	S - Agriculture
author	Guichuan Li
spellingShingle	Guichuan Li misc S1-972 misc buckwheat seeds misc discrete element parameter calibration misc DEM misc seed metering misc Agriculture (General) Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test
authorStr	Guichuan Li
ppnlink_with_tag_str_mv	@@773@@(DE-627)686948173
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	S1-972
illustrated	Not Illustrated
issn	20770472
topic_title	S1-972 Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test buckwheat seeds discrete element parameter calibration DEM seed metering
topic	misc S1-972 misc buckwheat seeds misc discrete element parameter calibration misc DEM misc seed metering misc Agriculture (General)
topic_unstemmed	misc S1-972 misc buckwheat seeds misc discrete element parameter calibration misc DEM misc seed metering misc Agriculture (General)
topic_browse	misc S1-972 misc buckwheat seeds misc discrete element parameter calibration misc DEM misc seed metering misc Agriculture (General)
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Agriculture
hierarchy_parent_id	686948173
hierarchy_top_title	Agriculture
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)686948173 (DE-600)2651678-0
title	Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test
ctrlnum	(DE-627)DOAJ094435715 (DE-599)DOAJc13fb15ca88149f89a66ef65075dceaa
title_full	Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test
author_sort	Guichuan Li
journal	Agriculture
journalStr	Agriculture
callnumber-first-code	S
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2023
contenttype_str_mv	txt
author_browse	Guichuan Li Haiyu Li Xuan Li Zhichao Gong Qinghua Yang Yuxiang Huang Zuoli Fu
container_volume	13
class	S1-972
format_se	Elektronische Aufsätze
author-letter	Guichuan Li
doi_str_mv	10.3390/agriculture13051024
author2-role	verfasserin
title_sort	establishment and calibration of discrete element model for buckwheat seed based on static and dynamic verification test
callnumber	S1-972
title_auth	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.
collection_details	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
container_issue	5, p 1024
title_short	Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test
url	https://doi.org/10.3390/agriculture13051024 https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa https://www.mdpi.com/2077-0472/13/5/1024 https://doaj.org/toc/2077-0472
remote_bool	true
author2	Haiyu Li Xuan Li Zhichao Gong Qinghua Yang Yuxiang Huang Zuoli Fu
author2Str	Haiyu Li Xuan Li Zhichao Gong Qinghua Yang Yuxiang Huang Zuoli Fu
ppnlink	686948173
callnumber-subject	S - General Agriculture
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.3390/agriculture13051024
callnumber-a	S1-972
up_date	2024-07-03T23:08:17.518Z
_version_	1803601153905131520
fullrecord_marcxml	<?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 code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Zhichao Gong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qinghua Yang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yuxiang Huang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Zuoli Fu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Agriculture</subfield><subfield code="d">MDPI AG, 2012</subfield><subfield code="g">13(2023), 5, p 1024</subfield><subfield code="w">(DE-627)686948173</subfield><subfield code="w">(DE-600)2651678-0</subfield><subfield code="x">20770472</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:13</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:5, p 1024</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/agriculture13051024</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/c13fb15ca88149f89a66ef65075dceaa</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2077-0472/13/5/1024</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2077-0472</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">13</subfield><subfield code="j">2023</subfield><subfield code="e">5, p 1024</subfield></datafield></record></collection>
score	7.399349

Nicht das Richtige dabei?

Schreiben Sie uns!

Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?