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Energy-based fibre bundle model algorithms to predict soil reinforcement by roots

Abstract : Modelling and predicting soil reinforcement by roots is a central quest in eco-engineering to assess the effectiveness of vegetation in landslide or erosion mitigation. Several fibre bundle model algorithms (FBMs) have been successfully introduced for soil reinforcement estimation and have achieved satisfactory results. However, FBMs yield variable reinforcement estimates due to their different hypotheses on the progressive root failure mode in soil (e.g., failure driven by load, strength or strain of roots); thus, they lack consensus in mechanism and application. Herein, we proposed three new FBMs, namely, FBMs-W, in which the root failure mode is driven by energy (i.e., work), and compared them with others using ground truth data. These FBMs-W allow, to some extent, reconciliation of the previous assumptions in conflicts because both load and displacement of roots affect in root failure procedures.
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https://hal.umontpellier.fr/hal-02404245
Contributeur : Yannick Brohard <>
Soumis le : mercredi 11 décembre 2019 - 11:21:33
Dernière modification le : jeudi 3 septembre 2020 - 11:12:04

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Jinnan Ji, Zhun Mao, Wenbin Qu, Zhiqiang Zhang. Energy-based fibre bundle model algorithms to predict soil reinforcement by roots. Plant and Soil, Springer Verlag, 2020, 446, pp.307-329. ⟨10.1007/s11104-019-04327-z⟩. ⟨hal-02404245⟩

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