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A robust and frugal model of biomass pyrolysis in the range 100-800 °C: Inverse analysis of DAEM parameters, validation on static tests and determination of heats of reaction

机译:100-800°C范围内的生物质热解的鲁棒和节俭模型:逆分辨率参数,验证静态试验和反应热的测定

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摘要

This paper presents a robust and frugal Distributed Activation Energy Model to simulate pyrolysis of lignocellulosic biomass (spruce and poplar) over a wide range of temperature and residence time. The learning database consists of dynamic TGA-DSC experiments performed up to 800 degrees C at four heating rates (1, 2, 5 and 10 K/min). By employing one non-symmetrical distribution, three distributions and only 9 independent parameters were needed to correctly fit the experimental data: a Gaussian distribution for hemicelluloses, a Gaussian function degenerated into a Dirac function for cellulose and a gamma function degenerated into an exponential function for lignins. The robustness of the model was successfully validated with 2-h isothermal tests (250 degrees C to 500 degrees C with increments of 50 degrees C). The heats of reaction were determined using the heat flux measured under fast dynamic conditions, thus reducing the crucial problem of baseline drift. The prediction potential of the model is highlighted by two examples: pathway in the Van Krevelen's diagram and control of the temperature rise to limit the heat source due to reactions. The model equations, the discretization and computational implementation, as well as the complete set of model parameters are presented in great detail, so that the reader can use them for process modelling, including the crucial concern of thermal runaway occurring in large particles or packed beds.
机译:本文介绍了一种坚固且节俭的分布式激活能量模型,以在宽范围的温度和停留时间模拟木质纤维素生物量(云杉和杨树)的热解。学习数据库由动态TGA-DSC实验组成,在四个加热速率(1,2,5和10k / min)中最多可达800℃。通过采用一个非对称分布,需要三个分布和仅需要9个独立参数来正确拟合实验数据:对半纤维素的高斯分布,将高斯函数退化为纤维素的DIAC函数,并将伽马函数退化为指数函数木质素。模型的稳健性已成功验证2-H等温测试(250摄氏度至500摄氏度,增量为50℃)。使用在快动力条件下测量的热通量测定反应热量,从而降低基线漂移的关键问题。模型的预测电位由两个示例突出显示:van Krevelen的途径和对温度升高的控制,以限制由于反应引起的热源。模型方程,离散化和计算实现,以及完整的模型参数,使得读者可以使用它们进行过程建模,包括在大型颗粒或填充床中发生的热失控的关键问题。

著录项

  • 来源
    《Fuel》 |2021年第15期|119692.1-119692.13|共13页
  • 作者单位

    Ctr Europeen Biotechnol & Bioecon CEBB CentraleSupelec LGPM 3 Rue Rouges Terres F-51110 Pomacle France|Univ Paris Saclay CentraleSupelec LGPM F-91190 Gif Sur Yvette France;

    Univ Paris Saclay CentraleSupelec LGPM F-91190 Gif Sur Yvette France;

    Ctr Europeen Biotechnol & Bioecon CEBB CentraleSupelec LGPM 3 Rue Rouges Terres F-51110 Pomacle France;

    Univ Paris Saclay CentraleSupelec LGPM F-91190 Gif Sur Yvette France;

    Univ Paris Saclay CentraleSupelec LGPM F-91190 Gif Sur Yvette France;

    Ctr Europeen Biotechnol & Bioecon CEBB CentraleSupelec LGPM 3 Rue Rouges Terres F-51110 Pomacle France|Univ Paris Saclay CentraleSupelec LGPM F-91190 Gif Sur Yvette France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Computational modeling; Identification; Poplar; Prediction; Spruce; Validation;

    机译:计算建模;识别;杨树;预测;云杉;验证;
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