6.5 Summary

Figure 1.1 depicts the general two-step approach for the translation of weather station data to driving rain data on a building envelope. In the present chapter, the second step (from site to building) was investigated by means of CFD simulations and by comparing the simulation results with the results of the measurements:

• modelling (sections 6.1 and 6.2):
  • the simulation of wind around the Main Building was carried out by the standard $K$-$\epsilon$ model as provided by Fluent. Except for $C_\mu = 0.032$ ([Bottema 1993a]), the standard model constants were applied,
  • the applied grid was a structured grid, which unfortunately creates undesired large grid expansion factors and cell aspect ratios in some parts of the grid. The size of the computational domain was determined by the rules of thumb given by [Bottema 1993a]. The domain included the Main Building, Auditorium and, optionally, Building T,
  • the size of the grid cells should be smaller than the stopping distance of the smallest considered raindrop. This implied a maximum dimension of 0.5 m near the façade, which is smaller than would be necessary for wind simulations alone,
  • it was assumed that raindrop trajectories do not influence wind flow. Consequently, raindrop trajectories were calculated for a previously calculated wind field. We also assumed that the lifetime of a drop is not affected by drop interaction (collision and break-up) nor by evaporation,
  • two models for drop trajectory calculations were applied: (1) without turbulent drop dispersion (resulting in `mean trajectories') and (2) with turbulent drop dispersion (``continuous random walk model''),
  • catch ratios $\eta (D)$ per façade section, reference wind speed and wind direction were obtained from the trajectory calculations. Driving rain intensities were calculated by assuming a certain raindrop spectrum: we used Wessels' [Wessels 1972] parameterisation of the [Best 1950] spectrum,
  • by doubling the number of released drops, we evaluated the convergence of the calculated values of $\eta (D)$ and thus determined the minimum number of drops to be released for a reliable $\eta (D)$ (figure 6.4);
• simulations versus measurements (sections 6.3 and 6.4):
  • the wind velocity simulations compare well with the full-scale wind measurements at position P4. Simulated mean pressure coefficients over the west façade compare quite well with wind tunnel and full-scale measurements of [Geurts 1997],

  • catch ratios $\eta (D)$ calculated with turbulent drop dispersion have higher values than without turbulent drop dispersion. Due to the (extra) turbulent velocity component, drops are more easily driven towards the façade when they come close to it. The smaller the drops are, the easier they are driven onto the façade. Moreover, the longer a drop flies closely to a façade, the higher is the probability that it is driven onto the façade. Figure 6.3 illustrates drop trajectories resulting from the two drop trajectory models; figures 6.10 to 6.14 show simulated catch ratios $\eta (D)$,

  • results of simulated driving rain intensity distributions over the façade are depicted in figures 6.16 to 6.19,

  • as $\eta (D)$ calculated with turbulent drop dispersion is more constant with drop diameter $D$ than without turbulent drop dispersion, differences in raindrop spectra with the same horizontal rain intensity have a smaller effect on the eventual driving rain intensities,

  • a comparison between the measurements and the simulations (based on the raindrop spectrum parameterisation of [Wessels 1972]) reveals that the results calculated with turbulent drop dispersion are likely to overestimate the measured driving rain intensities. The results calculated without turbulent drop dispersion are likely to underestimate the measurements,

  • the driving rain intensities simulated for a given façade section, reference wind speed and wind direction, and based on Wessels' raindrop spectrum parameterisation, result in an almost linear relation with horizontal rain intensity: $R_{\text{f}} \approx k(A) R_{\text{h}}$, where $k$ depends only on the shape (in our case, parameter $A$) of the raindrop spectrum,

  • in contrast to the previous item, the measured driving rain intensities for a given façade section, reference wind speed and wind direction show large variations. When measured raindrop spectra are used in the simulations, these simulated driving rain intensities show scatter too. Because the number of measured raindrop spectra during driving rain is rather small, we can not yet decisively conclude whether the relation mentioned in the previous item is actually valid.