Protocol for CFD prediction of cooling-tower drift in an urban environment

Abstract

A computational fluid dynamics (CFD) code including Lagrangian prediction of the gravity driven but stochastic trajectory descent of droplets is considered to predict plume rise and surface drift deposition from mechanical draft cooling towers. CFD drift deposition calculations are performed for a specific urban cooling tower situation with and without the urban buildings surrounding the cooling tower complex present to produce a set of multiplicative factors that could be used to correct seasonal or annual predictions for the presence of large urban structures.

Crosswinds effect on the performance of natural draft wet cooling towers

“…These studies have covered the simplest analytical models, higherlevel integral models, numerical predictions using CFD and experimental studies. The main concentration of those studies, however, was on single plumes with fewer studies reported on multiple plumes [6,11]. One of the significant findings from the study of multiple plumes was the non-existence of symmetry in the flow at certain conditions.…”

Cooling tower plume abatement and plume modeling: a review

“…The trajectories of drift droplets as a discrete phase were resolved using a Lagrangian stochastic approach. Later Meroney [102] tested the CFD model of Meroney [101] for urban cooling towers with surrounding buildings. One deficiency of Meroney's CFD model is that the effect of droplet evaporation was not accounted for.…”

Review of CFD Guidelines for Dispersion Modeling

“…Several professional organizations have established committees and groups to focus on the quality of and trust in CFD applied to practical situations [9,[12][13][14]. Scientists routinely validate their CFD calculations of bluff-body or urban street-canyon configurations by comparing their predictions with measurements taken during field or physical model simulations [15][16][17][18][19][20][21][22][23][24][25]. Such comparisons reveal which configurations can be modeled with confidence, and which situations are less realistic.…”