2019
DOI: 10.1007/s11104-019-04327-z
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Energy-based fibre bundle model algorithms to predict soil reinforcement by roots

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Cited by 30 publications
(11 citation statements)
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References 49 publications
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“…This 'sawtooth' effect may be partially responsible for FBMs overestimating experimentally-measured root reinforcement as the number of classes used in practice is relatively small, e.g. 4 (Genet et al 2008;Mao et al 2012;Ji et al 2020), 15 (Schwarz et al 2010;Moos et al 2016) or 20 (Comino et al 2010). Adding Weibull survival functions reduces but not eradicates this error.…”
Section: Discussionmentioning
confidence: 99%
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“…This 'sawtooth' effect may be partially responsible for FBMs overestimating experimentally-measured root reinforcement as the number of classes used in practice is relatively small, e.g. 4 (Genet et al 2008;Mao et al 2012;Ji et al 2020), 15 (Schwarz et al 2010;Moos et al 2016) or 20 (Comino et al 2010). Adding Weibull survival functions reduces but not eradicates this error.…”
Section: Discussionmentioning
confidence: 99%
“…This error may also be reduced by artificially distributing the root diameters within each class, for example by using probabilistic functions (e.g. Ji et al 2020). Using the continuous approach eliminates the need for iterative calculation algorithms which may a source of additional (numerical) errors.…”
Section: Discussionmentioning
confidence: 99%
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“…e e e d 0 W r , also called deformation energy, represents the ability of a root to absorb energy without failing and is an intrinsic mechanical quality of root tissue as a material that jointly considers strength and deformation (Ji et al 2020). The higher W r value that a root possesses, the tougher the root tissue.…”
Section: Introductionmentioning
confidence: 99%