How to use computational fluid dynamics (CFD) to analyze the function of machine room ventilation?

Computational fluid dynamics (CFD) is an efficient tool to estimate flow fields and their interaction with heat and humidity sources. What to take into the consideration when modeling complete machine room ventilation system?

Computational fluid dynamics (CFD) can be efficiently to be used to analyze the function of the machine room ventilation. With the calculation model can be estimated for example:

  1. How supply and exhaust air system modifications will effect on air movement inside the machine room?
  2. How temperature or humidity distribution will be changed due to the air system modifications or changes in process devices (heat and vapor loads)?
  3. How air system modifications should be done to get biggest benefit from the investment?

Model can include information about all air properties

In many cases the single phase fluid flow model can give enough good answers to evaluate the room ventilation function. However, often the minimum demand for the model is to use so-called non-isothermal model where temperature and its effect on the flow conditions is taken into the consideration. At the same time the temperature distribution for the entire air volume is produced.

Below is shown an example for the temperature distribution in the production facilities at height of 1.5 m. In this model heat loads and losses inside the machine room are included and fluid pattern with temperature distribution has been solved.

Improved design through CFD analysis

CFD can be used to estimate the effect of the changes in the air system. For example the effect of the new supply air unit can be analyzed by putting it into the model and making what-if-analysis by changing the inflow rate and supply air temperature. Below is shown an example where supply air flow is blown into the room both from the roof and the wall. Animation shows clearly the interaction between these two sources.

Tailor made models need good preparations

Model preparation, setting proper boundary conditions and creation of successful calculation strategy can be more time consuming tasks than estimated at the beginning. By setting sharp targets and by listing the questions where the answers are wanted, will give a good guidance for the model preparation.

The best results are achieved when the model designer and the process owner are in the tight co-operation through the whole modeling process. Without good preparations the modeling process can become an iterative process which takes lot of working and CPU-time and will give several useless calculation results.

Kalle Riihimäki

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