HVAC systems are directly related to comfort (human health, productivity, etc.) and energy consumption. Depending on the application and geographical area, they may become a key disruptive and energy starving system. The research discussed in this paper describes a CFD-based approach for robust HVAC system design aimed at reducing variability in the conditioned area by adjusting operating parameters. Since robust design techniques aim at minimum variance (via S/N ratio), the solutions obtained allow the selection of operating parameters leading to more uniform distribution. Three variables were used: air velocity (to control energy transfer from people to the surrounding air), Unit usage (a ratio to consider the air conditioning system inertia compared to air conditioning requirements), and room temperature set point (representing the relation between the machine and the conditions room).
Embedded codes with field functions in the CFD software allow the simulation of a very basic operation strategy, and demonstrate a quasi-dynamic operation for different cooling capacities and air velocity. Results allow allocating operating parameters that lead to a more uniform temperature and relative humidity distributions, therefore, this approach can be adequately combined with statistical design of experiments for better conditions.