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Automatic Generation of Kinetic Skeletal Mechanisms for Biomass Combustion

机译:生物质燃烧动力学骨架机制的自动生成

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摘要

We present in this paper simplified chemical mechanisms for gas phase biomass combustion based on automatic reduction of detailed and comprehensive kinetics. The reduction method that has been employed is a combined reaction Bow and sensitivity analysis well-known to combustion, resulting in a necessity index ranking all chemical species for automatic reduction. The objective is to obtain more compact chemical models, so-called skeletal mechanisms, for implementation into computational fluid dynamics, CFD, in order to reduce computational time. In the current work, the physical system used for the development and validation of the chemical models is that of a tubular reactor, or plug flow reactor, with operating conditions typically found in biomass reactors. The focus has been on gas phase reactions only, and the fuel composition is based on experimental values from biomass and coal gasification. Emphasis has been on the reliability of the simplified models and the correct prediction of important emission parameters such as NO_X and important intermediate species. The original chemical model, consisting of several sub models for important reaction paths known in biomass combustion, contained 81 species and 1401 reactions. This was successfully reduced down to 36 species, providing a compact and reliable chemical model for implementation into CFD. The model still contains the reaction paths of C_2 species, allowing for more realistic fuel gas compositions. The model has been experimentally validated for a wide range of temperatures including low temperature chemistry and reducing conditions for NO_x. The computational time saved using the simplified models was significant with over 80% reduction in CPU time.
机译:我们在本文中提出了基于自动还原详细和综合动力学的气相生物质燃烧的简化化学机理。所采用的还原方法是结合反应弓和燃烧众所周知的敏感性分析,从而得出将所有化学物种进行自动还原的必要性指数。目的是获得更紧凑的化学模型,即所谓的骨架机制,以实施到计算流体动力学CFD中,以减少计算时间。在当前工作中,用于开发和验证化学模型的物理系统是管式反应器或活塞流反应器的系统,其操作条件通常在生物质反应器中发现。重点仅在于气相反应,燃料组成基于生物质和煤气化的实验值。重点放在简化模型的可靠性和重要排放参数(如NO_X和重要中间物种)的正确预测上。原始化学模型由生物质燃烧中重要反应路径的几个子模型组成,包含81种和1401个反应。它成功地减少到36种,为CFD实施提供了紧凑而可靠的化学模型。该模型仍然包含C_2物种的反应路径,从而允许更逼真的燃料气体成分。该模型已针对包括低温化学物质和NO_x还原条件在内的各种温度进行了实验验证。使用简化模型可以节省大量的计算时间,CPU时间减少了80%以上。

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  • 来源
    《Energy & fuels》 |2013年第novaadeca期|6979-6991|共13页
  • 作者单位

    Department of Energy and Process Engineering, Norwegian University of Sdence and Technology, Kolbjorn Hejes vei 1B, NO-7491 Trondheim, Norway;

    Technical Department, ENERGOS AS, Kvenildmyra 5, NO-7072 Heimdal, Norway;

    SINTEF Energy Research, Kolbjarn Hejes vei lA, NO-7465 Trondheim, Norway;

    SINTEF Energy Research, Kolbjarn Hejes vei lA, NO-7465 Trondheim, Norway;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
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