Dishwasher Simulation in PreonLab

Using a camera inside the dishwasher is one way to go. However, if you are the engineer who is designing a dishwasher or analysing its performance, you want to know more about the details and are interested in quickly testing and analysing various design variants.

With the help of simulation methods (an important one of which being CFD), the design process of a dishwasher becomes easier and less expensive. This is the main reason why dishwasher manufacturers (and in general, the white goods sector) face a growing need for using high-fidelity simulation tools.

When it comes to simulating fluid flows in a dishwasher, the grid-based simulation methods are extremely demanding from both pre-processing and computational time perspectives. This makes the gridless CFD methods, more specifically said smoothed particle hydrodynamics (SPH) used in PreonLab, of high benefit and a reason why it has found its way to the white goods sector.

Depending on what the design/analysis engineers are looking for by performing CFD simulations, the simulation can look differently. They might be interested in improving the water distribution through optimizing the shapes as well as the directions of the spray nozzles. For doing so, it might not be necessary at the beginning to include the dishware in the simulation. Moreover, simulating for only a single full rotation of the spray arm might suffice for this purpose. One strategy could be to place some planes properly positioned in the tub connected to PreonLab’s wetting sensors in order to observe how well they get wet for a number of design variants to improve the design probably in an iterative manner. An example of how such simulations could look like in PreonLab is depicted below.

Simulations including the dishware could also be performed in order to test and potentially optimize the initial design of the jets in a more realistic case for multiple scenarios depending on the size and the form of the dishware. Such simulations could also help the engineers to come up with best practices for designing the baskets, which to a great extent dictate how the dishware should be arranged as well as where each category of dishware are to be placed. Moreover, best practices for arranging the dishware can be concluded and introduced to the users. In the video below, you can see how such simulations could look like in PreonLab:

An example problem to be addressed could be finding a solution for what you might already have experienced after the dishwashing process is finished; formation of water puddles on top of some dishware, esp. the cups as can be seen in the figure below:

PreonLab sensors could also be of great help when it comes to optimizing and analysis of the flow as well as its interaction with the solid parts (mainly the dishware). Wetting sensors are capable of measuring the time each point of a solid has been in contact with a fluid (called wetting time in PreonLab). In the figure below, the distribution of wetting time for the dishware is demonstrated.

Moreover, force sensors can be used for measuring the shear stress applied by water to the dishware. This can be one of the decisive metrics regarding the washing efficiency. The figure below shows the distribution of the maximum shear viscosity on the surface of the dishware.

One further step would be to include the dirt in the simulation. This can be achieved by performing multiphase simulations in PreonLab. Let’s assume ketchup sauce is to be modeled in the simulation. Since ketchup is not a Newtonian fluid, a more complicated model is needed to be used for it when compared to that of water. In PreonLab, for such fluids the Herschel–Bulkley fluid model is used. Since there are several ketchup types each having its own properties, it is up to the user whether or not to go for values coming from their own precise experiments (if available) or to go with some values coming from a reference. In the video below, values used for the ketchup properties have been taken from an online reference.

Note that the effects of detergents and in general, the solubility of the dirt in water can not be taken into account at the moment in PreonLab.

One way to take spray arm rotation into account would be to define the arm rotation (constant or variable rotational speed) in conjunction with the introduction of area sources functioning as nozzle outputs. Another alternative, which is more precise and therefore costlier, is to employ PreonLab’s rigid body solver which enables the capability to model the interaction between rigids and fluids, in this case, the spray arm and water. The following video is an example of the latter.

PreonLab is also very strong when it comes to photo-realistic renderings. This has been proven to be of benefit for demonstration and presentation purposes in order to make the results more insightful and of stronger impact. There are some material presets available for both solids and fluids in PreonLab which make the setup for such renderings easier. Glass, steel, rubber and water are some of the presets relevant for the dishwasher simulation. Moreover, a textured surface material makes it possible to project a texture onto a given mesh, as is the case for the knife handle in the figure below.