Efficient and accelerated process development in the agricultural industry using Rocky DEM
Published on: December 2, 2019
The agricultural sector relies on complex equipment that can handle seeds, soil and tailings, among other materials. Problems that occur during farming operations usually are due to material blockages, equipment wear-and-tear, and inefficient chopping and separation. Our role in all this is to develop tools that will help industry easily and quickly improve agricultural equipment and processes.
Although many other industries have incorporated predictive tools that enable virtual design on a computer, the agricultural industry has not been so fortunate: Computer models that can represent complex material shapes and highly anisotropic behavior have not been available. Until recently, computer-based discrete element modeling (DEM, which tracks particle motion by solving equations that govern their rotation and translational movement) was not developed sufficiently to serve as part of the multi-physics simulation tool kit. Thus, such applications have lagged in leveraging the predictive power of virtual prototyping. Key technology advances in Rocky DEM make it a powerful predictive tool in the agricultural sector, thereby reducing the amount of physical testing and prototyping needed, which is both time- and cost-prohibitive.
Realistic particle shapes
What has been the issue? In a word, particles: grains, seeds, fibers, crops, soils and stems. Agricultural raw materials are often elongated — such as sugar cane and hay fibers — and non-spherical — such as corn and seeds. Traditional DEM codes consider the aspherical nature of shapes by modeling them using a clustered or “glued-” sphere approach. Although this method was easy to implement due to simple contact-detection algorithms for spheres, it does have significant disadvantages, such as the inability to efficiently model large-scale simulations containing high-aspect ratio particles, like hay and fiber. For example, to model an elongated hay particle accurately with an aspect ratio of 1,000, at least 1,000 spheres (diameter 1 mm) need to be glued together, resulting in high memory requirements and long solution times.
Rocky DEM software has advanced particle modeling with unique polyhedral shape representation that is more representative of naturally occurring particles, greatly improving simulation accuracy. Fiber, shell and volume shapes (solid concave and solid convex) mimic 1-D, 2-D and 3-D particles. Figure 1 compares common shapes such as hay, leaves and corn, that are modeled using both the traditional glued-sphere approach and the polyhedral representation in Rocky DEM. You can clearly see that the glued-sphere shape is “bumpy” and not an accurate representation of the material. Because of this bumpy surface, the traditional approach produces an artificial friction/interlocking behavior. The polyhedral representation does not have this limitation and, although the contact detection for such accurate shapes is quite complex, advances in solver technology (using GPU hardware) enable users to model several hundreds to millions of particles.
In addition to accurate shape representation, DEM material models must capture accurate physics when the material is subjected to stresses within processing equipment. For example, Rocky’s particle shapes can stretch, bend and twist due to repeated stresses. Material like hay and sugarcane, which flex and snap during operations, can be modeled in Rocky using a joint 1-D particle fiber model (Figure 2). The design engineer creates the particle by connecting sphero-cylinder elements. In the initial undeformed position, the centers of the hemispherical caps of contiguous elements coincide. The user can make a more complex shape using this model. Barley or wood branches, for example, which have stems and leaves, can be created using a branched fiber model, as shown in a wood chipper simulation below. The concept can also be applied to joints in 2-D and 3-D elements (Figure 2). Because these flexible joints can break when subjected to high normal and shear loads, Rocky’s extended breakage capability predicts a more accurate prediction of flow in harvesting equipment.
Complex particle and machine interactions
Most agricultural machines, like combine harvesters, incorporate several components as well as complex motion mechanisms comprising gears, belts, pulleys, etc. To model equipment motion, most DEM codes require a coupling solution that involves external third-party multibody software, commonly resulting in a difficult setup along with long modeling and run times. To help overcome these issues, Rocky DEM embeds a motion kernel, capable of representing such motions without third-party code coupling, enabling very short modeling and simulation time. Time reduction can range from weeks to several days.
Faster, better computations with GPU capabilities
Large-scale DEM simulations with millions of particles use huge amounts of hardware memory. The multi-GPU solver in Rocky DEM overcomes this obstacle by efficiently distributing and managing the combined memory of two or more GPU cards within a single motherboard, reaching a solution in a reasonable time frame that is well-suited for product development. The result is considerable time savings, allowing your company to perform more calculations more quickly. And because GPUs can expedite large, complex problems, Rocky DEM is now an invaluable tool for modeling real industry problems.
As agricultural companies attempt to solve challenges related to quality and reliability of their machines, they must also innovate and deliver solutions that are tailored to industry demands. Predicting particle behavior is critical to this effort, and Rocky DEM is proving to be a valuable agricultural solution in reducing this complexity.
Because Rocky DEM is fully integrated with the ANSYS simulation suite, users can easily perform particle–CFD and particle–FEA analyses to address multiphysics challenges (Figure 5). Robust coupling with ANSYS Mechanical using Rocky DEM data, for example, enables static, transient, harmonic, fatigue, and dynamic analyses to be completed on equipment. Similarly, ANSYS Fluent precisely predicts how particles and fluid flow interact, considering momentum and heat exchanged.
Other ANSYS tools help users to maximize geometry components and perform design of experiment studies.
Vice President of Rocky DEM Business Development and Technical Services
Dr. Rahul Bharadwaj has over a decade of experience in the development, validation, and application of computational tools such as Discrete Element Modeling (DEM), CFD, and FEA. After completing his Ph.D. in Mechanical Engineering at Purdue University, he was a senior scientist at Pfizer R&D and senior engineer at Jenike and Johanson Inc, where he has several years of consulting experience in the field of bulk material handling. He is an active member of the American Institute of Chemical Engineers (AIChE), the American Association of Pharmaceutical Scientists (AAPS), and is the founder and past-chair of AAPS's Process Modeling and Simulation Focus Group.
Get Fresh Updates on Email
We'll never share your email address, and you can opt out at any time, we promise.