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A Validation of Flare Combustion Efficiency from LES

机译:LES的燃烧燃烧效率验证

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Our objective is to predict the combustion efficiency of industrial flares by using Large Eddy Simulations (LES). The practical utility of the results of a computer simulation is proportional to the degree to which the error and uncertainty in the simulation results have been quantified by validation with experimental data. The available combustion efficiency data from flare experiments is both expensive and sparse. The International Flare Consortium has recently released experimental data on tests performed at the CANMET wind tunnel flare facility. For this paper we have used experimental data from the 4 inch flare tests for measured outlet species concentrations to obtain combustion efficiency as a function of crosswind velocity. We have also included data from buoyant helium plumes measured by Sandia National Laboratory in the validation hierarchy. We have used this validation process to demonstrate and advocate a validation procedure that is philosophically influenced by the Scientific Method, made quantitatively rigorous by Bayesian Inference, but made simple and practical through the use of a consistency constraint. The consistency constraint requires all experiments and all simulations to be bounded by their individual experimental uncertainty. This approach draws on prior information to exploit the consistency requirement among the available experimental data sets and the simulations of these sets to quantify the uncertainty in model parameters, boundary conditions and experimental error and simulation outputs. The final result is a predictive capability for flare combustion efficiency where no experimental data are available but where the validation process produces error bars for the predicted combustion efficiency.
机译:我们的目的是通过使用大型涡流模拟(LES)来预测工业耀斑的燃烧效率。计算机仿真结果的实用实用性与模拟结果中的误差和不确定性的程度成正比,通过使用实验数据验证已经量化。来自耀斑实验的可用燃烧效率数据既昂贵又稀疏。国际耀斑财团最近发布了关于在Canmet风洞爆发设施的测试的实验数据。对于本文,我们使用了从4英寸的火光试验中使用实验数据,以获得测量的出口物种浓度,以获得作为横向速度的函数的燃烧效率。我们还包括桑迪亚国家实验室测量的浮标氦羽毛的数据。我们使用该验证过程来证明并倡导验证程序,这些程序是由科学方法的哲学影响,通过贝叶斯推理定量严格,但通过使用一致性约束使得简单实用。一致性约束需要所有实验和所有模拟都被其个人实验不确定性所界限。这种方法借鉴了现有信息,以利用可用的实验数据集之间的一致性要求和这些集合的模拟,以量化模型参数,边界条件和实验误差和仿真输出中的不确定性。最终结果是FLARE燃烧效率的预测能力,其中没有实验数据,但验证过程产生误差杆的预测燃烧效率。

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