任婧杰
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论文类型:期刊论文
发表时间:2016-09-01
发表刊物:CRYOGENICS
收录刊物:SCIE、EI、Scopus
卷号:78
页面范围:1-13
ISSN号:0011-2275
关键字:Submerged combustion vaporizer; Supercritical LNG; Heat transfer; Numerical simulation; Buoyancy effect; Secondary flow
摘要:The submerged combustion vaporizer (SCV) is indispensable general equipment for liquefied natural gas (LNG) receiving terminals. In this paper, numerical simulation was conducted to get insight into the flow and heat transfer characteristics of supercritical LNG on the tube-side of SCV. The SST model with enhanced wall treatment method was utilized to handle the coupled wall-to-LNG heat transfer. The thermal-physical properties of LNG under supercritical pressure were used for this study. After the validation of model and method, the effects of mass flux, outer wall temperature and inlet pressure on the heat transfer behaviors were discussed in detail. Then the non-uniformity heat transfer mechanism of supercritical LNG and effect of natural convection due to buoyancy change in the tube was discussed based on the numerical results. Moreover, different flow and heat transfer characteristics inside the bend tube sections were also analyzed. The obtained numerical results showed that the local surface heat transfer coefficient attained its peak value when the bulk LNG temperature approached the so-called pseudo-critical temperature. Higher mass flux could eliminate the heat transfer deteriorations due to the increase of turbulent diffusion. An increase of outer wall temperature had a significant influence on diminishing heat transfer ability of LNG. The maximum surface heat transfer coefficient strongly depended on inlet pressure. Bend tube sections could enhance the heat transfer due to secondary flow phenomenon. Furthermore, based on the current simulation results, a new dimensionless, semi-theoretical empirical correlation was developed for supercritical LNG convective heat transfer in a horizontal serpentine tube. The paper provided the mechanism of heat transfer for the design of high-efficiency SCV. (C) 2016 Elsevier Ltd. All rights reserved.