| Popis: |
Centrifugal roof fans are traditionally considered as ‘small’ machines and as such did not attract much attention. They can be categorized as low power fans as their installed power is usually bellow 2kW. Nevertheless, they make approximately 30% of fans used in non-residential ventilation, which when considered on mass-scale makes them large energy consumers. Since they have relatively low efficiency (ranging between 0.3-0.5), considerable space for improvement exists. This resulted in various studies which include optimization coupled with CFD flow models. The most often used criterion was fan efficiency at single flow regime. Recent studies have shown that this is not a good approach since there can be multiple different solutions with almost the same single-regime efficiency. A better approach is to conduct optimization for multi-regime operating conditions or to use multi-objective optimization with the minimization of noise emission used as the second criterion. The predictions of numerical flow model must be robustly accurate (for various in impeller shapes and flow regimes). In this paper, enhanced CFD models for the prediction of fan energy performance and noise emissions are developed. First, the RANS based models with the frozen-rotor approach and k- epsilon / k-omega turbulence models were reviewed. The application of more advanced models of frozen-rotor RANS, URANS and LES models is investigated. The CFD predictions are compared to our experimental data from a previous study. The results show that improved prediction of energy efficiency is obtained with LES based CFD models for the off-design flow regimes. Meanwhile, the RANS and URANS models can also provide good results when using first-order upwind discretization scheme. The results show that using high-order discretization schemes deteriorates the CFD prediction of the fan performance. The fan noise emission was predicted using LES data and this allowed for the investigation of wide-spectra noise in comparison to simple models used in previous papers. The models developed in this paper can be used as the basis for shape optimization studies which require multi-fidelity simulations. |
