Overcome industrial food processing challenges with particle simulation
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Published on: January 14, 2020
Equipment manufacturers in a wide variety of industries acknowledge the power of simulation and modeling in engineering to develop robust, energy-efficient, and cost-effective designs. One key tenet is to apply virtual engineering upfront in the design cycle — well before major manufacturing costs are incurred. Although the food processing industry has its own particular challenges that differ from other sectors, it too can benefit from early simulation intervention. In developing innovative food processing technologies, modeling is an important tool for designing and optimizing operational parameters as well as for controlling product quality and safety.
No matter the industry, equipment manufacturing design decisions can play a critical role in R&D cost efficiency, since 70% of a project’s costs are committed by design decisions. This early phase — where only a tenth of the total cost is spent — is the ideal time to apply engineering simulation and modeling to meet project objectives. (Barton et. al, 2001)
Industry challenges
Food processing incorporates a range of both equipment and processing technologies: conveyor belts, mixing drums, granulation and seasoning processes, crushers that break up food particles, packaging, and end-product optimization. Leading industry organizations pay special attention to optimizing process capacity and efficiency. Of course, that’s never enough. Engineers study enhancing mixing and homogeneity of end products, hoping to improve areas that produce poor mixing. System – and component-level analyses look at eliminating particle attrition and breakage, analyzing coating spray patterns, and investigating conveyor loading/unloading pattern and flow rate.
The common thread in all these efforts is predicting how individual or aggregate particles, each with a distinct shape, will realistically react with each other and equipment that are designed for mixing, coating, loading, sorting, drying, or packaging. Computational tools that perform discrete element modeling (DEM) can supplement experiment and theory — and, more important, provide input that is often impossible or impractical to capture through real-life validation. Using simulation also greatly improves cost reduction and shortens time to market.
The best of DEM
Particle simulation is extremely valuable for studying how materials behave in a confined, often impossible-to-observe, space. In simulating the system and its components, Rocky DEM is a leading software for modeling particulate matter. The software produces real shapes, and this realistic physical representation brings accuracy to modeling granular flows, particle breakage, and other complex problems.
Rocky DEM produces solids (gummy bears), shells (potato chips), and fibers (pasta) that move realistically, enabling as many translational, rotational, and free body motion combinations as needed to describe the process.
A powerful motion kernel enables multibody dynamics analysis without coupling to external tools. In addition, Rocky’s solver performance is impressively fast, and parallelization in both CPU and GPU allows users to solve large problems. Equally important, Rocky DEM is integrated with ANSYS tools within the Workbench platform and provide solution to multiphysics problems.
Rocky’s breakage models preserve mass and volume; they can be used to evaluate forces (normal, bending, shear, torsional) applied to particles and equipment.
Food processing equipment examples
You can leverage Rocky DEM for food processing applications including mixing and blending, quality control, drying and heat exchange, controlling discharge, sorting and separation, and packaging processes. Here are a few examples.
V-blender
The goal of mixing and blending for this application was to increase product quality, achieve homogeneous powder distribution, optimize the loading procedure and mixing time, and observe real-scale mixing and material behavior. For this V-blender study, Rocky DEM post-processing tools showed the product distribution. By comparing different loading methods, a more-even distribution of materials has been achieved.
V-blender study.
Mixing drum
For a mixing drum application, the goal was to reduce time to complete mixing, analyze operating time while ensuring homogeneity under higher loads, and evaluate various mixing scenarios using parametric optimization tools. Rocky’s inclusive post-processing tools facilitated model analysis. You can represent discrete values in a continuous form and by collecting a sample, the mixing index can be determined. These real data points help in making operational decisions. Overall, Rocky DEM optimized the process to be energy-efficient working under a maximum load of particles.
Wet barley auger.
Conical dryer
This conical dryer application investigated heat exchange between particles and the equipment structure in an effort to increase efficiency and minimize operating time. Engineers determined that it was important to see the whole process defined within a single project, from filling to discharge. They analyzed temperature distribution in the bed to assure continuous drying.
Conical dryer application.
Coffee-roasting machine
For a coffee-roasting machine application, engineers needed to evaluate convective and conductive heat transfer using CFD-DEM coupling. Rocky DEM was applied to evaluate working conditions (temperature, rotor speed) for optimum working time, analyze loading level, and increase capacity. In addition, the real shape representation of coffee bean helps achieving a higher accuracy.
Coffee-roasting machine.
Particles collisions
End-product quality control is important in applications where particles collide frequently. Process design for this case was based on product quality criteria in a shear-induced environment. Rocky DEM was leveraged to determine optimum product quality based on end-product shape and design parameters, minimize product erosion, and gain deeper knowledge of the process behavior through physics-based representation.
Intra-Particle variation in average shear stress for different tablet shapes.
Liquid film and bridge
In this liquid film and bridge model, liquid covers each particle, and it must be evenly distributed. Rocky DEM was valuable in evaluating and improving the coating process, analyzing spray rate and position to achieve optimum coating time and end-product homogeneity, and performing virtual experiments on product lines with true physical representations.
Coating process in a drum.
Particle spraying
A ray tracing analysis used advanced post-processing techniques to evaluate spraying as particles pass through a spray zone. Engineers determined the particle’s partial or total occlusion through post-processing methods using Rocky DEM. Their goal was to quickly determine optimum sprayer position and evaluate design decisions.
Ray tracing analysis evaluating spraying.
V-belt conveyor
Controlling discharge from a V-belt conveyor, that transfer potatoes was analyzed for an efficient loading and unloading rates, via optimized equipment design simulation. Rocky DEM provided accurate prediction of geometry stresses and jamming propensity.
V-belt conveyor.
Snack chips filling
Particle simulation is beneficial to packaging processes as well. To improve the application of filling snack chips in a packaging bag, Rocky DEM helped the engineering team to analyze the filling procedure to achieve an optimum load of material while controlling final products breakage and attrition.
Snack chips packing.
Discrete element modeling can be a critical tool in performing virtual experiments on product lines and simulating real-world operations with true physical representations. As you can see, Rocky DEM tools play a vital role in many food processing applications, especially in giving deeper insight into the design details to make operations more efficient. Rocky DEM gives you comprehensive understanding of any particle problem and enables all-inclusive decision-making approaches.
Ahmad Haghnegahadar
Rocky DEM Applications Engineer
Ahmad Haghnegahadar, a Rocky DEM application engineer at ESSS, holds a master of science degree in chemical engineering from Oklahoma State University and brings experience in analyzing multiphase and turbulent flows in the field of biomechanics. Prior to joining ESSS, Ahmad developed and optimized chemical processes through data analysis tools in the oil and gas industry. Given his diverse background from petroleum to pharmaceutical, he recognizes and understands the challenges engineers face in simulating multiphysics systems across many industries.
