Calibration of flexible grass-root discrete-element fragmentation model using improved hippopotamus algorithm

Accurate weed models are critical for elucidating mechanical weeding interactions. However, key parameters and targeted models for flexible weed-body fracture are lacking. We propose a novel, discrete-element model (DEM) for simulating flexible weed stress fracture using the Hertz–Mindlin with Bonding V2 contact model. The proposed model facilitates high-fidelity root-architecture reconstruction and accurately reproduces root mechanical responses, including fracture, fragmentation, tension, and shear. A full-chain multi-index constrained parameter calibration system was established via physico-mechanical testing of barnyard grass ( Echinochloa crus-galli ) roots, with a simulated-measured contact-angle deviation of just 2.23%. The key calibrated parameters included a normal stiffness and shear stiffness of 1.98243 × 10 14 N·m −3 , normal strength and shear strength of 2.03399 × 10 10 MPa, bonding V2 radius of 5.771 × 10 −2 mm, and inter-particle contact radius of 6.627 × 10 −2 mm, ensuring model accuracy and biological authenticity. Moreover, we developed an adaptive evolutionary genetic hippopotamus optimisation algorithm (AEG-HOA) for the global optimization of DEM parameters, with the ultimate tensile and shear strengths as response metrics. Comparative results revealed that AEG-HOA achieved 1.11% and 1.08% calibration errors, far below those of conventional methods (4.23% and 3.23%, respectively), attaining convergence within nine iterations with robust stability. This work provides a high-precision standardised DEM for mechanical weeding interaction research and efficient plant-simulation-parameter calibration.