用于烃类高温热化学转化为乙炔的新型环形射流涡反应器

IF 4.3 Q2 ENGINEERING, CHEMICAL
Sreekanth Pannala*, Vladimir Shtern, Lei Chen and David West, 
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引用次数: 2

摘要

介绍了一种新型的石蜡烃高温热化学转化合成乙炔反应器。反应器采用锥形环形旋流射流,随着旋流强度的增大,射流变得非常薄。小的厚度提供了快速的质量,动量和热量传递,以促进快速加热和转化的反应物。我们采用了一个独特的壁面形状的会聚-发散燃烧区,保持相对较低的反应堆壁温度,避免了外部冷却的需要。根据Navier-Stokes方程和能量方程的近似解析解推导出壁面形状和角度,从而在极高的旋流条件下获得最大的射流速率,避免壁面分离。解析解预测了一个高速旋流,其中包括一个薄的环形锥形发散射流,在那里质量、动量和热流集中,化学反应可以迅速发生。在整个射流中,温度从大的近轴值急剧下降到小的近壁值。我们通过对Navier-Stokes方程、能量方程和物种方程的数值模拟以及概念验证实验来说明和研究这些特征。实验证实了火焰呈薄环形锥形,呈蓝色,透明,在喉部附近锚定良好。本装置产生一种流动模式,使反应器壁温度降到最低,同时生产具有高选择性和高转化率的轻质烯烃。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Novel Annular Jet Vortex Reactor for High-Temperature Thermochemical Conversion of Hydrocarbons to Acetylene

Novel Annular Jet Vortex Reactor for High-Temperature Thermochemical Conversion of Hydrocarbons to Acetylene

This paper describes a novel reactor for acetylene synthesis by high-temperature thermochemical conversion of paraffin hydrocarbons. The reactor utilizes a conical annular swirling jet, which becomes extremely thin as swirl intensifies. The small thickness provides fast mass, momentum, and heat transfer to facilitate the rapid heating and conversion of the reactants. We employ a unique wall shape for the converging–diverging combustion zone, which maintains relatively low reactor wall temperature and avoids the need for external cooling. The wall shape and angle were derived from an approximate analytical solution of the Navier–Stokes and energy equations, which leads to the maximal jet flow rate and avoids wall separation under extreme high swirling flow conditions. The analytical solution predicts a high-speed swirling flow, which includes a thin annular conical diverging jet where mass, momentum, and heat fluxes concentrate, and chemical reactions can occur rapidly. Across the jet, the temperature sharply drops from its large near-axis value to its small near-wall value. We illustrate and study these features with the help of numerical simulations of the Navier–Stokes, energy, and species equations and proof-of-concept experiments. The experiments confirm the thin annular conical shape of the flame, which is blue, transparent, and well anchored near the throat. The present device produces a flow pattern, which minimizes the reactor wall temperature, while producing light olefins with high selectivity and conversion.

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来源期刊
ACS Engineering Au
ACS Engineering Au 化学工程技术-
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期刊介绍: )ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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