Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Numerical Simulation on Double-nozzle Spray Evaporation of Desulfurization Wastewater

Version 1 : Received: 13 October 2021 / Approved: 14 October 2021 / Online: 14 October 2021 (10:40:08 CEST)

How to cite: Xu, H.; Feng, S.; Xiao, L.; Hao, Y.; Du, X. Numerical Simulation on Double-nozzle Spray Evaporation of Desulfurization Wastewater. Preprints 2021, 2021100213 (doi: 10.20944/preprints202110.0213.v1). Xu, H.; Feng, S.; Xiao, L.; Hao, Y.; Du, X. Numerical Simulation on Double-nozzle Spray Evaporation of Desulfurization Wastewater. Preprints 2021, 2021100213 (doi: 10.20944/preprints202110.0213.v1).

Abstract

To achieve the near zero emission of wastewater in the flue gas desulfurization (FGD) system in coal-fired power plant and better utilize the exhaust heat from flue gas, a feasible technology of spraying FGD wastewater in the flue duct for evaporation is discussed in the present study. A full-scale influencing factor investigation on the wastewater droplet evaporation performance is established under the Eulerian-Lagrangian model numerically. The dominant factors, including the characters of wastewater droplets, flue gas and the spray nozzles were analyzed under different conditions, respectively. Considering the multiple factors and conditions in the process, a Least-Square support vector machine (LSSVM) model is introduced to predict the evaporation rate based on the numerical results. Conclusions are made that the flue gas temperature and droplet diameter are of great importance in the evaporation process. The spray direction of droplet parallel with the flue gas flow direction is profitable for the dispersion of droplet, resulting the maximal evaporation rate. A double-nozzle arrangement optimized with relatively small flow rate is recommended. The LSSVM model can accurately predict the evaporation rate using the numerical results with different conditions.

Keywords

FGD wastewater spay evaporation; atomized droplet characteristics; Least-Square support vector machine prediction model

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.