Appliances have issues. Flow and thermal issues to be exact. The movement of air, water, and other fluids at proper temperatures is vital to every appliance. Adding the ever-increasing demand for efficiency and environmental controls yields complex interactions that can determine the success or failure of a new or updated product.

Enlarge this picture In these simulated close-ups underneath a Wolf cooktop (top and bottom images above), vector arrows show direction of air movement and colors show velocity; blue is slower, red is faster.

Efforts to optimize thermal and flow characteristics for appliances can be aided by utilizing CFD early in the product development cycle. Using automated software to visualize flow and heat issues early in the design process enables greater design experimentation, reduces costs incurred with physical testing, and speeds the development cycle.

One appliance company that has benefited from upfront CFD is Wolf Appliance, Madison, Wis., which uses CFdesign software from Blue Ridge Numerics, Charlottesville, Va. Wolf has integrated the software into the development process for all of its products, including wall ovens, warming drawers, electric cooktops, induction cooktops, and dishwashers.

Appliance design challenges at Wolf are far from simple. Take, for example, the company’s signature oven. For proper self-cleaning, the interior surface of an oven door needs to reach at least 800 DegF for two hours, while about 2 in. away, the stainless steel surface must stay below 150 DegF to ensure consumer safety. A typical Wolf electric oven has five heating elements and two convection fans for even cooking; if there is a design flaw in the elements or the fans, the result could be uneven cooking and inefficient performance. 

Enlarge this picture Simulation of a 65-CFM fan operating underneath a cooktop.

Ben Hanson, design engineer for advanced product development at Wolf Appliance, has found that using CFdesign early in the development process can flag design flaws that may not have been seen until the prototyping stage. Discovering a flaw at that point previously had resulted in the project taking a major step backwards or concessions being made to work around the issue.

Hanson cites Wolf’s double-wall oven as an example of the value of upfront CFD. The oven has two cooling fans, and during initial design it appeared as if they would function properly. But when the CFdesign analysis was run, Wolf’s engineers found that the air ducting was not segregated enough. Hot air was re-looping between the two fans, causing the cooling system to run hotter than desired. The design was brought back into SolidWorks CAD software, where the ducting was changed and tested again in CFdesign until the problem was solved.

Correcting the issue enabled Wolf to pass UL and CSA testing and increase the oven’s efficiency, while saving money on costly physical prototyping.

According to Hanson, upfront CFD does not just save money by reducing the need for prototyping, it uncovers performance issues that cannot be ferreted out by physical testing. Wolf uses thermocouples and infrared imaging for temperature measurements, but finds it difficult to do physical testing to measure flow.

Enlarge this picture Simulation of a PCB with a multi-fin heat sink operating under a cooktop.

Hanson says that to physically perform tests, it was often necessary to disrupt the flow areas to insert the measurement equipment. He also notes that using smoke to analyze flow only provides a general idea of flow. By contrast, upfront CFD delivers a more comprehensive analysis that can be directly verified with the smoke traces, helping the engineers to visualize situations that are difficult to prototype in the physical world.

Another example can be found in the recent development of a Wolf 36-inch electric cooktop line, where the use of CFdesign in the early design stages eliminated multiple rounds of physical prototyping and enabled Wolf to develop the product in half the time it would have taken otherwise.

For appliance designers to fully benefit from performing CFD analysis in the early design stages, good practices are essential, and those practices can be summed up with four imperatives.

1. Provide adequate training. While upfront CFD tools are marketed based on ease of use, some companies mistakenly think that means “no training required.” It is important to train all the engineers who might need to use these tools and schedule follow-up training when the tools will be used sporadically.
2. Avoid the risk of placing all CFD expertise with a single person. Upfront technologies provide the optimal benefit when implemented throughout the engineering team. A thorough implementation will enhance the entire group’s efficiency and innovation, and the cumulative effect will reinforce a regular cycle of usage and success.
3. Build upfront CFD into the formal development process. Neglecting to schedule time for upfront activities in the official process will result in a “business as usual” process. If a company typically tracks and manages projects with Gantt charts and gate review systems, CFD milestones should be built into the plan.
4. Don’t lock onto one design only, but consider many. Upfront CFD tools are more fully exploited when used to evaluate many design options at the conceptual stages. When integrated with parametric CAD tools, upfront CFD allows engineers to perform numerous what-if studies with very little project definition. Dozens, or even hundreds, of potential directions can be quickly compared to help focus engineering effort.
   
   Once an upfront CFD tool is in place, there are several tips for optimizing the investment.

Enlarge this picture A typical fan-curve plot.

• Start with a basic model. Prepare a conceptual model containing only the most important geometry and indicate the fluid and heat-flow paths. Understand the critical physical effects to be studied. If the fluid is a gas, are compressibility effects significant?  If the fluid is a liquid, are any phase changes expected such as solidification or cavitation? Is the flow expected to be laminar or turbulent? What will move the fluid – a fan, buoyancy, known-pressure supply line, or some combination? Where does heat enter the system, and where does it leave?  How does heat leave – via conduction, convection, and/or radiation? Are internal body-to-body radiation effects significant?
• Check assumptions. Every calculation is founded on certain underlying assumptions, and upfront CFD is no different. It is important to understand whether the assumptions are conservative or non-conservative in relation to critical results such as the peak temperature, total flow through the system, and pressure drop in a system.

Typical flow assumptions include incompressible or compressible, laminar or turbulent, and slip or no-slip wall conditions. Typical thermal assumptions include perfect thermal contact, radiation or no radiation, adiabatic external walls or external leakage.

In a heating situation, for example, assuming perfect thermal contact is a non-conservative approach. Any contact resistance between two parts (which inevitability exists in real life) will cause actual temperatures to be higher than predicted by simulation.

The “no body-to-body radiation” assumption, on the other hand, is typically conservative.  Radiation between components and the exterior housing is an extra heat flow path alongside conduction and convection. Ignoring this path will typically cause higher temperatures in the simulation results.

• Keep it simple at first. Make the first simulation on a geometrically simple, but representative model of the system. Start with a relatively coarse mesh, but seek to include all the significant physical effects. This is most important for new designs or for someone early in their experience with the analysis tool. One reason for the simple approach is purely pragmatic.  When mistakes are inevitably made, it’s important to discover the effects quickly and clearly.

In addition, the initial simple representative model can be used to understand the general performance of the system, particularly in areas that require special attention. Where is the highest temperature? Where is the highest pressure gradient or choke-point in the flow? If using a fan, roughly where is the fan operating on its performance curve? Focusing more simulation attention on these critical areas can be accomplished later.

Keeping first models rough and simple permits the rapid processing of initial results and the ability to quickly move on to other scenarios. This approach also makes it possible to quickly test the relative importance of factors such as variance in material properties and mesh sensitivity. If it is determine later to run a model with production-level details, there will already be established a good sense of the potential impact of these factors on final results.