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Calibration of discrete element method soil models based on penetrometer and direct shear box tests using a genetic algorithm

• Bence Szabo
• Taddeus Szabo
• Kornel Tamas

(2024). ECMS 2024, 38th Proceedings
Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2024
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-84-5
ISBN: 978-3-937436-83-8 (CD) Communications of the ECMS Volume 38, Issue 1, June 2024, Cracow, Poland June 4th – June 7th, 2024

https://doi.org/10.7148/2024-0216

Bence szabo, Taddeus szabo, Kornel tamas (2024). Calibration of discrete element method soil models based on penetrometer and direct shear box tests using a genetic algorithm, ECMS 2024, Proceedings Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation. doi:10.7148/2024-0216

The investigation and mechanical modeling of agricultural soil play an important role in studying the interaction between soil and tillage tools. One of the possible numerical methods for soil modeling is the discrete element method (DEM). Achieving reliable numerical soil-tool interaction studies poses a significant challenge in calibrating various soil models. Calibration of soil models based on physical measurements is feasible. The general aim of calibration is to match as many behavioural mechanical properties of a soil model as possible with the macromechanical properties of the actual soil. Calibration based on physical measurements has previously been an extensive process because during calibration, the micromechanical parameters of the DEM soil model can not be measured directly during physical tests. This research aims to calibrate complex and automated DEM soil model using genetic algorithms based on penetration and laboratory direct shear box tests. The research results demonstrate that the parameters of the appropriate DEM soil model can be effectively adjusted using genetic algorithms based on the soil’s macromechanical properties determined by physical measurements.