CIESC Journal ›› 2016, Vol. 67 ›› Issue (S1): 76-83.doi: 10.11949/j.issn.0438-1157.20160603

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Numerical predictions of sulfuric acid corrosion on novel heat transfer surfaces

WANG Yuchen, TANG Guihua   

  1. Key Laboratory of Thermo-Fluid Science and Engineering, Ministry of Education, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
  • Received:2016-05-09 Revised:2016-05-19 Online:2016-08-31 Published:2016-08-31
  • Supported by:

    supported by the National Natural Science Foundation of China (51576156).

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Abstract:

Low temperature corrosion determined by the sulfuric acid dew point temperature and the sulfuric acid vapor and water vapor condensation rate is an important reason denoting the failures of heat transfer equipment. In this study, the sulfuric acid dew point temperature and sulfuric acid vapor and water vapor condensation rate on the wall and fin surface are calculated by considering both the vapor-liquid equilibrium effect and multi-component diffusion effect. In addition, the local distribution of acid dew point temperature on the fin surface is numerically predicted. It provides a precise guidance for the design of heat exchanger. The results show that the acid dew point temperature is affected by the factors of fuel type, fly ash particle (size and quantity) and structure of heat transfer fins. The fuel type, which affects the flue gas compositions and the combustion temperature, plays an important role on the sulfuric acid dew point temperature. The condensation of the sulfuric acid vapor on the ash particle surface leads to the decrease of sulfuric acid dew point temperature. The studied novel heat transfer fins (the H-type fin with compound dimples and rectangular longitudinal vortex generators) can reduce the local sulfuric acid dew point temperature and the sulfuric acid vapor and water vapor condensation rate on the fin surface.

Key words: sulfuric acid dew point, sulfuric acid vapor condensation rate, water vapor condensation rate, novel fins, surface, numerical simulation, prediction

CLC Number: 

  • TK124
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