Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings

Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffus...
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Autor*in:	Bate, Bate [verfasserIn] Nie, Shaokai [verfasserIn] Chen, Zejian [verfasserIn] Zhang, Fengshou [verfasserIn] Chen, Yunmin [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Soil–water characteristic curve Granular materials Packing Toroidal model Discrete element method

Anmerkung:	© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021

Übergeordnetes Werk:	Enthalten in: Acta geotechnica - Berlin : Springer, 2006, 16(2021), 6 vom: 25. Jan., Seite 1949-1960
Übergeordnetes Werk:	volume:16 ; year:2021 ; number:6 ; day:25 ; month:01 ; pages:1949-1960

Links:	Volltext

DOI / URN:	10.1007/s11440-021-01140-w

Katalog-ID:	SPR044146434

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520			\|a Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment.
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700	1		\|a Chen, Yunmin \|e verfasserin \|4 aut
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allfields	10.1007/s11440-021-01140-w doi (DE-627)SPR044146434 (DE-599)SPRs11440-021-01140-w-e (SPR)s11440-021-01140-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Bate, Bate verfasserin aut Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021 Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. Soil–water characteristic curve (dpeaa)DE-He213 Granular materials (dpeaa)DE-He213 Packing (dpeaa)DE-He213 Toroidal model (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Nie, Shaokai verfasserin aut Chen, Zejian verfasserin aut Zhang, Fengshou verfasserin aut Chen, Yunmin verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 16(2021), 6 vom: 25. Jan., Seite 1949-1960 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:16 year:2021 number:6 day:25 month:01 pages:1949-1960 https://dx.doi.org/10.1007/s11440-021-01140-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 16 2021 6 25 01 1949-1960
spelling	10.1007/s11440-021-01140-w doi (DE-627)SPR044146434 (DE-599)SPRs11440-021-01140-w-e (SPR)s11440-021-01140-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Bate, Bate verfasserin aut Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021 Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. Soil–water characteristic curve (dpeaa)DE-He213 Granular materials (dpeaa)DE-He213 Packing (dpeaa)DE-He213 Toroidal model (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Nie, Shaokai verfasserin aut Chen, Zejian verfasserin aut Zhang, Fengshou verfasserin aut Chen, Yunmin verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 16(2021), 6 vom: 25. Jan., Seite 1949-1960 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:16 year:2021 number:6 day:25 month:01 pages:1949-1960 https://dx.doi.org/10.1007/s11440-021-01140-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 16 2021 6 25 01 1949-1960
allfields_unstemmed	10.1007/s11440-021-01140-w doi (DE-627)SPR044146434 (DE-599)SPRs11440-021-01140-w-e (SPR)s11440-021-01140-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Bate, Bate verfasserin aut Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021 Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. Soil–water characteristic curve (dpeaa)DE-He213 Granular materials (dpeaa)DE-He213 Packing (dpeaa)DE-He213 Toroidal model (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Nie, Shaokai verfasserin aut Chen, Zejian verfasserin aut Zhang, Fengshou verfasserin aut Chen, Yunmin verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 16(2021), 6 vom: 25. Jan., Seite 1949-1960 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:16 year:2021 number:6 day:25 month:01 pages:1949-1960 https://dx.doi.org/10.1007/s11440-021-01140-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 16 2021 6 25 01 1949-1960
allfieldsGer	10.1007/s11440-021-01140-w doi (DE-627)SPR044146434 (DE-599)SPRs11440-021-01140-w-e (SPR)s11440-021-01140-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Bate, Bate verfasserin aut Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021 Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. Soil–water characteristic curve (dpeaa)DE-He213 Granular materials (dpeaa)DE-He213 Packing (dpeaa)DE-He213 Toroidal model (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Nie, Shaokai verfasserin aut Chen, Zejian verfasserin aut Zhang, Fengshou verfasserin aut Chen, Yunmin verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 16(2021), 6 vom: 25. Jan., Seite 1949-1960 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:16 year:2021 number:6 day:25 month:01 pages:1949-1960 https://dx.doi.org/10.1007/s11440-021-01140-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 16 2021 6 25 01 1949-1960
allfieldsSound	10.1007/s11440-021-01140-w doi (DE-627)SPR044146434 (DE-599)SPRs11440-021-01140-w-e (SPR)s11440-021-01140-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Bate, Bate verfasserin aut Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021 Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. Soil–water characteristic curve (dpeaa)DE-He213 Granular materials (dpeaa)DE-He213 Packing (dpeaa)DE-He213 Toroidal model (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Nie, Shaokai verfasserin aut Chen, Zejian verfasserin aut Zhang, Fengshou verfasserin aut Chen, Yunmin verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 16(2021), 6 vom: 25. Jan., Seite 1949-1960 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:16 year:2021 number:6 day:25 month:01 pages:1949-1960 https://dx.doi.org/10.1007/s11440-021-01140-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 16 2021 6 25 01 1949-1960
language	English
source	Enthalten in Acta geotechnica 16(2021), 6 vom: 25. Jan., Seite 1949-1960 volume:16 year:2021 number:6 day:25 month:01 pages:1949-1960
sourceStr	Enthalten in Acta geotechnica 16(2021), 6 vom: 25. Jan., Seite 1949-1960 volume:16 year:2021 number:6 day:25 month:01 pages:1949-1960
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Soil–water characteristic curve Granular materials Packing Toroidal model Discrete element method
dewey-raw	550
isfreeaccess_bool	false
container_title	Acta geotechnica
authorswithroles_txt_mv	Bate, Bate @@aut@@ Nie, Shaokai @@aut@@ Chen, Zejian @@aut@@ Zhang, Fengshou @@aut@@ Chen, Yunmin @@aut@@
publishDateDaySort_date	2021-01-25T00:00:00Z
hierarchy_top_id	513533192
dewey-sort	3550
id	SPR044146434
language_de	englisch
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author	Bate, Bate
spellingShingle	Bate, Bate ddc 550 bkl 56.20 misc Soil–water characteristic curve misc Granular materials misc Packing misc Toroidal model misc Discrete element method Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings
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topic_title	550 ASE 56.20 bkl Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings Soil–water characteristic curve (dpeaa)DE-He213 Granular materials (dpeaa)DE-He213 Packing (dpeaa)DE-He213 Toroidal model (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213
topic	ddc 550 bkl 56.20 misc Soil–water characteristic curve misc Granular materials misc Packing misc Toroidal model misc Discrete element method
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title	Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings
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title_full	Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings
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title_sort	construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings
title_auth	Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings
abstract	Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021
abstractGer	Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021
abstract_unstemmed	Abstract The soil–water characteristic curve (SWCC) of granular materials is crucial for many emerging engineering applications, such as permeable pavement and methane hydrate extraction. Laboratory determination of the SWCC of granular materials suffers from inaccurate volume readings by the diffused air bubbles in the hanging column and sudden desaturation at small matric suction intervals. Theoretical determination of the SWCC of granular materials also suffers from semi-empirical nature in the prediction from grain size distribution, or from the limitation of assumed cubic packing or face-centred cubic packing with a toroid meniscus water model. In this study, real three-dimensional particle packing was first rendered with the discrete element method using approximation of spheres. Then, the Young–Laplace equation was applied to calculate the volume of toroidal meniscus water between each pair of spheres, which adds to the water content in the pendular regime of the SWCC. Additionally, a digitized image algorithm was used to identify the pore throats and calculate the air entry value and residual matric suction, the connection of which yields a straight line approximating the funicular regime. The SWCC was thus constructed. Comparison with laboratory-measured SWCCs suggested that although reasonable agreement was reached in general for glass beads, residual water content was underestimated, especially for non-spherical granular materials. Several possible reasons were discussed including the existence of patchy water accounting for the major portion of water in the beginning of pendular regime of granular materials, which was also observed in microscopic photographs through a special desaturation experiment. © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021
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container_issue	6
title_short	Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings
url	https://dx.doi.org/10.1007/s11440-021-01140-w
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author2	Nie, Shaokai Chen, Zejian Zhang, Fengshou Chen, Yunmin
author2Str	Nie, Shaokai Chen, Zejian Zhang, Fengshou Chen, Yunmin
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doi_str	10.1007/s11440-021-01140-w
up_date	2024-07-03T23:10:11.383Z
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Construction of soil–water characteristic curve of granular materials with toroidal model and artificially generated packings

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