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Collaboration of simulations and experiments for development and uncertainty quantification of a reduced char combustion model

机译:仿真和实验的协作和降低炭燃烧模型的不确定性定量

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Computational fluid dynamics (CFD) plays a decisive role in the development of cost-effective oxy-coal combustion technologies to improve process efficiency and to decrease pollutant emissions. The implementation of detailed physical models describing coal devolatilization, char oxidation, gas-phase reactions and pollutant formation ensures accurate CFD simulations of coal combustion but is still challenging for large-scale combustors due to the significant computational efforts required. especially in the framework of Large Eddy Simulation (LES). The development of reduced physics model with quantified model-form uncertainty is needed to overcome the challenges of performing LES of industrial coal-fired boilers. Reduced models must reproduce the main features of the detailed models and the capability of bridging scales and being predictive. A tight coupling of simulation and experiments is necessary to ensure predictivity with uncertainty quantification for a reduced model. This work proposes a combined experimental/numerical methodology that uses global sensitivity analysis to rank fundamental input parameters of a reduced char oxidation and gasification model describing reactions between char carbon and O_2, CO_2 and H_2O reagents in both air and oxy-coal conditions. A careful evaluation of uncertainty in the data, in the model form and in the model parameters is performed. The reference dataset, consisting of the experiments carried out in a laminar entrained flow reactor operated by Sandia National Laboratories, has been exploited. The methodology is based on the use of so-called instrument models to include all the physical sub-models and the sources of uncertainty considered in the experiments and in the numerical simulations and affecting the main quantities of interest, e.g. reaction rates. The quantified uncertainty in the instrument models provides the range of uncertainty for the reduced char combustion model. Then, the reduced model with quantified uncertainty will be validated against the experimental data. The reduced model capability to address heterogeneous reaction at the particle surface, mass transport of species in particle boundary layer, pore diffusion and internal surface area changes will be assessed.
机译:计算流体动力学(CFD)扮演的成本效益的氧煤燃烧技术的发展,以提高流程效率和减少污染物排放决定性的作用。描述煤脱挥发份详细的物理模型,碳氧化,气相反应和污染物形成的实施,确保煤炭燃烧的精确CFD模拟,但仍由于需要显著的计算努力具有挑战性的大型燃烧器。尤其是在大涡模拟(LES)的框架。用量化模型的形式不确定性减少物理模型的发展是需要克服的工业燃煤锅炉进行LES的挑战。缩减的模型必须复制模型的详细的主要特点和缩小规模和被预测的能力。仿真和实验的紧密耦合是必需的,以确保与不确定性量化预测能力为减小的模型。这项工作提出了一种组合的实验性/数值方法使用全局灵敏度分析,以描述在空气和氧 - 煤焦炭的条件和碳O_2,CO_2和H_2O试剂之间的反应减少的焦炭氧化和气化模型的秩基本输入参数。执行在数据不确定性,在该模型的形式和模型参数的仔细评估。引用数据集,由实验中由Sandia国家实验室操作的层夹带流反应器中进行,已被利用。该方法是基于使用所谓的仪器模型,包括所有的物理子模型,并在实验和数值模拟考虑不确定性的来源和影响的利益,例如主数量反应速率。在仪器模型的量化的不确定性提供了用于缩小焦炭燃烧模型的不确定性范围。然后,用量化的不确定性减少的模型将针对实验数据被验证。简化模型能力,以解决在颗粒表面非均相反应,在粒子边界层,孔扩散和内表面积的变化物种的质量传递将被评估。

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