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Virtual Oven to Assist Baking Industry
Computational fluid dynamics model the distribution of temperature and air velocity
by Michele Marcotte, Phd
Many companies in the baking industry have come to Agriculture and Agri-Food Canada’s Food Research and Development Centre (FRDC) in Saint-Hyacinthe, Quèbec, Canada, for help in understanding what happens inside a baking oven. While it is not difficult to measure temperatures inside the oven, it is time-consuming and expensive to experiment with many different oven configurations to provide just the right temperature profile for a given product.
The FRDC has overcome this problem by developing a virtual oven using computational fluid dynamics (CFD) to model the distribution of temperature and air velocity, the main factors affecting baking product quality, inside the oven. The new virtual oven makes it possible for food processing companies to quickly evaluate many oven designs to achieve the right cooking properties for the best products.
FRDC sponsors about 20 research teams that carry out joint research with the food industry. FRDC researchers offer high-caliber scientific support for research into bio-ingredients, dairy products, meat products, fruits and vegetables, bakery products, packaging and preservation technologies, fermentation, quality and traceability of foodstuffs, and food engineering.
The ISO-9001:2000 Industrial Program helps the Canadian food industry enhance its competitiveness by increasing, through research, the understanding of food systems and by fostering the development and transfer of new technologies and knowledge. Some 900 companies have carried out more than 1,600 research projects at the FRDC since 1987.
Challenges of Baking Equipment Design
The baking oven project was designed to address problems faced by smaller food processors in optimizing the design of baking equipment. These companies want to produce a product with just the right amount of volume expansion. They are concerned about the effects of the baking process on quality, color, texture, and other food properties.
Typically, these companies perform physical experiments in a small research oven in order to determine the conditions required to bake a product with exactly the right properties. The challenge then becomes reproducing these conditions throughout the interior of a much larger industrial oven.
The complexity of the physics and geometries involved makes it impossible in most practical designs to predict performance using conventional engineering calculations. As a result, the traditional approach to oven design involves creating an initial concept design based on engineering judgment and experience, building and testing a prototype, and then—based on the results—reconfiguring the design and repeating the entire process again and again until an acceptable design is achieved. Unfortunately, experiments such as these are usually quite expensive and time-consuming.
Design Optimization Impossible
Relying completely on experiments is not practical because an oven is normally required to meet production demands, and taking it out of service to perform experiments is expensive. And modifications to the oven may be required, and these add to the costs as well as to the downtime.
Indeed, the time needed to perform all of the experiments required to achieve the right conditions may delay the launch of a new product, sacrificing revenues to competitors. Moreover, cost and time constraints typically make it impossible to optimize a design. Instead, engineers face budget constraints and product introduction targets and often must settle for the first design good enough to meet the product specifications.
CFD can overcome these problems by a virtual oven that can perform a range of experiments by changing its geometry or process conditions. For any oven design engineers can imagine, CFD can compute detailed predictions of flow velocity and temperature for almost any piece of process equipment. Once created and validated, these virtual prototypes are used to investigate multiple design configurations, optimize manufacturing process parameters, and conduct safety studies. By making it possible to investigate more alternatives in less time and at lower cost, flow modeling can help bring better products to market while lowering development costs.
A 3-D, CFD Stand-Alone Virtual Oven
To make it easier and less expensive for smaller baking companies to take advantage of this technology, the FRDC recently developed a three-dimensional CFD stand-alone model of a small baking oven. The objective of the study was to investigate the distribution of temperature and the velocity of the air movement throughout the oven and to compare the simulation predictions with experimental results.
FRDC researchers selected FIDAP, CFD software from ANSYS of Canonsburg, Pa., as its modeling and analysis tool. FIDAP uses the finite element approach and unstructured grids, which provide considerably greater flexibility in modeling the complex and irregular geometries often associated with food processing. Unstructured grids also make it easy to automate the otherwise tedious process of fitting computational elements to the complex geometries used in food processing equipment, such as mixer blades.
The geometry of the 0.7 m x 0.48 m x 0.56 m oven was created and meshed with Gambit, preprocessor software from ANSYS. Three modes of heating were considered: conduction, wall-to-wall radiation, and convection. The thermal volume expansion of the air was considered as a source of air movement. Boundary and initial conditions were given as follows: initial temperature Ti=21°C; environment temperature Te=21°C; surface heat transfer coefficient h=10 W/m2°C; and air velocity on all the solid surfaces=0.
Simulation Results Match Physical Testing
The results predicted by the CFD model included temperature images and velocity vector plots at times of 100, 300, and 600 seconds. In order to validate the modeling performance, 12 thermocouples were installed at different locations inside the actual oven. The recorded temperatures were used for comparison to those from the CFD simulation. The statistical results of the modeling performance were characterized by a correlation coefficient (R2) of 0.92 and an average relative error (Er) of 7%. These values suggest that the CFD model matched the experimental results well.
The CFD analysis of the initial design for the oven provided the engineering team with a better understanding of the role of certain key design parameters than could have been gained by physical testing alone. The simulation could also be used to perform a sensitivity analysis, and the technique could be extended to more complicated cases.
In the near future, for example, the FRDC plans to extend the simulation to consider not only the heat, mass, and momentum transfer within the oven but also the heat and mass transfer within the product during baking and its effect on baking conditions, with particular focus on the effect of bakery product volume expansion.
Other Food Processing Applications
CFD also has the potential to improve the design of many other types of food processing equipment such as vibro-mixers, disk impellers embedded with dozens of small holes (perforations) that agitate a liquid by moving up and down. Vibro-mixers are commonly used in hermetically sealed vessels where it is impractical to use rotating seals. Common uses include bioprocessing applications such as fermentation.
On a typical vibro-mixer, the tapered ends of the perforations are oriented upward; fluid jets are emitted from the tops of the holes during the downward stroke of the impeller. During the upward stroke, fluid flows in the reverse direction into diverging conical volumes. The upward-directed jets are stronger and give rise to circulation patterns in the bulk fluid. The downward-directed jets are weak by comparison and quickly dissipate.
CFD can be used to help understand the flow patterns and circulation time characteristics of a particular mixer design and a given liquid. If there are solids in the system, the simulation can help determine the processing window of vibration frequency and amplitude to keep the solids in suspension. CFD can also be used to predict the performance of other types of mixers, to assess alterations made to an extrusion die design, and to evaluate design processes that will meet Hazard Analysis and Critical Control Points guidelines in food safety studies.
Computer simulation is an idea whose time has come for the food processing industry. New modeling techniques provide engineers with the ability to evaluate the performance of design concepts with reasonable accuracy without having to build prototypes.
CFD makes it possible to investigate many more designs than the traditional build-and-test approach, resulting in performance gains. At the same time, the lower cost and shorter lead times of simulation provide faster time to market and reduced development costs. In addition, because CFD simulation provides even more design data than physical testing, it is an indispensable option for engineers involved in food processing equipment design.
Dr. Marcotte is a research scientist at the Agriculture and Agri-Food Canada Food Research and Development Centre in Saint-Hyacinthe, Québec, Canada. She can be contacted at email@example.com.
For details on ANSYS Inc., visit www.ansys.com.