Increasing costs associated with separators - often in difficult, remote applications - drives the desire to improve separator selection and avoid oversizing the device by improving confidence in separator performance predictions. Accurate predictions of separation performance of a dispersed phase depend upon accurate estimates of entrainment and size distribution of the dispersed droplets entering the separator. For relatively efficient separation devices, the performance prediction is highly sensitive to the small end of the size distribution. A common practice is to characterize the droplet field with a two-parameter distribution based on predictions of two large droplet sizes such as the maximum and median droplets. This approach allows small errors associated with the predictions of large droplets to produce large errors in the small end of the distribution and can significantly compromise the performance prediction.
This presentation will discuss a modified two-parameter methodology in which the minimum droplet size that can be created from available energy along with the maximum droplet size that can survive in the flow are used to characterize the droplet size distribution. Evaluations of this methodology over a range of dispersion suggest that the approach can be universally applied to dispersions of liquid in gas, liquid in liquid, and gas in liquid.