It is estimated that around 80% of all industrial processes deal with particulate materials. Some examples are conveyor belts, hoppers, mixers, cyclones and tabletting machines. The Mpacts software is able to simulate these processes and predict the effectiveness of different design options. By doing so, the cost for prototyping can be decreased or even removed entirely. Moreover, many particulate flows can suddenly exhibit process-critical behavior, such as blockage, jamming, fracture or fragmentation. These phenomena are very hard to predict using the continuum approximations that are adopted in classical CFD simulations. DEM simulations have to potential to help design industrial processes that either avoid or harness these complex system properties.
Example: Milling operations
This figures shows a milling simulation, where arbitrarily shaped particles are placed in a rotating drum. Typically, an abrasive action is desired on the particles, induced by the rotational motion of the mill.
Simulations can help answer a range of questions during the design phase of these milling machines. DEM simulations can predict the distribution of impact energies. With this information available, the mill can be either optimised to be as 'aggressive' as possible, or if only partial destruction is desired, e.g. when separating materials rather than milling it, an optimal impact distribution may be computed.
Another very common problem is process upscaling. How do the forces scale when a working-lab scale equipment is scaled up to an industrial scale? What are the new optimal setpoints for the rotational velocity, and how do we have to modify the industrial design to mimick the lab scale conditions as closely as possible?
Fruit and crop handling
Bruise damage in fruits and vegetables is an important source of economic losses and food waste. Especially soft fruits are very susceptible to bruises. Simulations using Mpacts with virtual fruit and vegetables are a powerful and cost-effective approach for improving fruit and crop handling.
For example, they can help guide the design of an optimal picking gripper for different fruit shapes. Simulations can also provide insight in the critical frequencies and amplitudes that should be avoided during transport. Using that knowledge, transport vehicles can be adjusted or packaging techniques and materials can be imporoved in order to obtain better damping of damaging vibrations.
Discrete Element Method simulations can help design sorting lines, and not only to help prevent bruise damage. Simulations of the fruit singulator in sorting lines can be used to examine at which rotational speed or with what type of diabolo a good singulation and fruit alignment can be realized.
Recent years have seen an elevated focus on tissue engineering, tissue/organ bio-printing, microfluidics, and lab-on-a-chip technologies which are characterized by bottom-up development strategies and an increased importance of controlling and manipulating inter-cellular interactions.
Particle-based simulations can aid the design of devices for manipulation, transport and manufacturing of cellular systems in industrial processes. For example, they can help devise microfluidic channels that efficiently transport cells while preventing jamming or flocculation.
This figure shows a simulation of budding yeast (saccharomyces cerevisiae) forming multicellular clusters (called flocs) in shear flow conditions. Industrially, flocculation in yeast is harnessed in beer brewing processes, where large flocs of yeast cells either settle at the bottom or float towards the top of a brew. Thereby, the yeast can be efficiently removed from the product.
As mobile platforms that perform mechanical operations on crops, agricultural machines benefit greatly from design changes that improve production output and/or reduce fuel consumption rates.
Moreover, they are often required to handle fragile biological materials for which mechanical damage/bruising can incur significant economic losses. The granular nature of these operations with complicated shapes and non-linear, history-dependent and soft mechanical behavior has hindered the widespread adoption of simulation-based computer aided product and process design. The software Mpacts is uniquely suited for simulating these systems, due to its capability of representing arbitrary and deformable shapes, its data-based material descriptions, and its innate extensibility. For example, crops can be represented as flexible rods composed out of capsule geometries, of which the mechanical behavior is calibrated based on a few inexpensive lab experiments (see image).
For a given machine design, simulations can predict how the crop flow influences the power consumption, which machine components are most likely to wear quickly, and how efficiently the crop is being processed.