This presentation was made at the 2019 NAFEMS World Congress in Quebec Canada

Resource Abstract

Off Road equipment customers make their purchase either to move soil or prepare, nurture or harvest their crop. Requirements are increasingly complex and critical due to market globalization and speed to commercialization. During the product development process multiple methods and tools are allowing engineers to model complex interactions between vehicle and soil/crop. Those are key components to full system modeling. Discrete Element Method (DEM) and computational Fluid Dynamics (CFD) are well known methods in the industry for modeling soil & crop to machine interactions. As part of those methodologies, a very critical aspect is the material model calibration. In addition, the sub-systems of a vehicle often lead to a different model or needs. For example, a combine harvester has over eight areas of engagement with the crop or soil (cutting head, cleaning shoe, grain tank, spreader, tire, etc.) and each potentially requiring different needs and approaches. Classical soil mechanics have developed multiple tests in the last 50 years to derive critical physics parameters such as internal angle of friction or modulus of elasticity which were used in the development of the models. The numerical methods used nowadays often requires additional parameters such as “damping” or meshing/particle size that are inherent to the numerical methods in place. Another aspect sometimes ignored is the interactions among the model parameters and that unique testing alone cannot solve for the complex problems at hand. A proposed solution relies on a combination of tests along with an optimization algorithm which allows to find an optimum compromise for a set of parameters. A validation is also required to narrow down the best possible solution among best set of candidates. This overall calibration process is necessary to tackle the large amount of materials that off-road equipment is interacting with. As an engineer, it enables understanding of critical components and handle system optimization.