An investigation on structural parameters optimization and coupled heat transfer of LNG submerged combustion vaporizer

材料科学 经销商 传热 阀体孔板 机械 热交换器 传热系数 汽化器 压力降 强化传热 热力学 机械工程 工程类 废物管理 物理
作者
Changliang Han,Y. M. Huang,Zhipeng Chen,Yanyan Wu,Shunyu Bao,Fangwei Zhao,Xibing Li
出处
期刊:Cryogenics [Elsevier]
卷期号:136: 103764-103764
标识
DOI:10.1016/j.cryogenics.2023.103764
摘要

Submerged combustion vaporizer (SCV) owns an extremely efficient multiphase heat exchanger adopted in the coastal liquefied natural gas (LNG) receiving terminal. Overall vaporization efficiency of SCV mostly depends on the matching relationship of structural parameters and coupled heat transfer characteristics, which has been rarely addressed in previous studies. In the present work, an integrated SCV experimental platform with handling capacity of 50 kg/h was set up to validate the reliability of numerical model and method. Additionally, on account of multi-parameter orthogonal combination optimization method, the effects and sensitivity orders of structural parameters (transverse tube pitch, longitudinal tube pitch, orifice size and number of distributor branch) on dynamics performance of SCV were investigated. Finally, the coupled heat transfer between gas–liquid two-phase flow and supercritical LNG gasification was revealed in view of optimized parameters. Results indicated that the transient numerical tube-side outlet temperature could be consistent with experimental data. For the shell-side heat transfer coefficient, the sensitivity order was transverse tube pitch > orifice size > longitudinal tube pitch > number of distributor branch. Nevertheless, for the shell-side pressure drop, the sensitivity order was longitudinal tube pitch > transverse tube pitch > orifice size > number of distributor branch. Under the condition of optimization scheme, the heat provided by gas–liquid two-phase flow could meet the requirements of supercritical LNG gasification, the NG outlet temperature might achieve approximately 272 K. The present outcomes could lay a foundation for the optimization design and deep understanding for actual SCV facility.
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