Effects of natural convection on thermal explosion in a closed vessel

文献信息

发布日期 2008-07-24

DOI 10.1039/B808222G

影响因子 3.676

作者

Ting-Yueh Liu, Alasdair N. Campbell, Silvana S. S. Cardoso, Allan N. Hayhurst

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摘要

A new way of ascertaining whether or not a reacting mixture will explode uses just three timescales: that for chemical reaction to heat up the fluid containing the reactants and products, the timescale for heat conduction out of the reactor, and the timescale for natural convection in the fluid. This approach is developed for an nth order chemical reaction, A → B occurring exothermically in a spherical, batch reactor without significant consumption of A. The three timescales are expressed in terms of the physical and chemical parameters of the system. Numerical simulations are performed for laminar natural convection occurring; also, a theoretical relation is developed for turbulent flow. These theoretical and numerical results agree well with previous experimental measurements for the decomposition of azomethane in the gas phase. The new theory developed here is compared with Frank-Kamenetskii’s classical criterion for explosion. This new treatment has the advantage of separating the two effects inhibiting explosion, viz. heat removal by thermal conduction and by natural convection. Also, the approach is easily generalised to more complex reactions and flow systems.

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来源期刊

Physical Chemistry Chemical Physics

CiteScore: 5.5

自引率: 10.3%

年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.