Uncertainty quantification of thermo-acoustic instabilities in annular combustors
Uncertainty quantification of thermo-acoustic instabilities in annular combustors
复制标题
环形燃烧室热声不稳定性的不确定性量化
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
F. Nicoud
中科院分区：
文献类型：
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作者：
M. Bauerheim;A. Ndiaye;P. Constantine;G. Iaccarino;S. Moreau;F. Nicoud
基于主动子空间和低阶模型的不确定性量化（UQ）方法应用于简化的燃气轮机，以确定其模态风险因子：声模态不稳定的概率。该配置是一个简化的 19 个燃烧器环形燃烧器，在两种不同的状态下运行，称为弱耦合状态和强耦合状态。每个火焰均由两个不确定参数建模，从而导致涉及 38 个参数的大型 UQ 问题。燃烧室被建模为 4 × 19 1D 互连 1D 声学元件的网络，如 Bauerheim 等人最近提出的那样，可以有效地进行准分析求解 (ATACAMAC)。 （2014b）。这使我们能够执行蒙特卡罗分析（大约 10, 000 ATACAMAC 计算），假设输入的不确定性已知。然后将参考蒙特卡罗风险因子与通过要求较低的 UQ 方法获得的风险因子进行比较。首先，对于基于梯度相关的主动子空间方法所考虑的两种情况，问题的维数从 38 个减少到只有 3 个参数。然后，使用 100 次 ATACAMAC 模拟拟合基于三个主动变量的线性和二次分析模型。然后将这些低阶模型重放 100、000 次，以获得增长率的 PDF 以及风险因素估计。结果表明，对于这两种方案，UQ 方法都能够准确预测配置的风险因素。
An Uncertainty Quantification (UQ) method based on active subspace and low-order models is applied on a simplified gas turbine to determine its modal risk factor: the probability of an acoustic mode to be unstable. The configuration is a simplified 19-burner annular combustor which is operated in two different regimes, called weakly and strongly coupled regimes. Each flame is modeled by two uncertain parameters leading to a large UQ problem involving 38 parameters. The combustor is modeled as a network of 4 × 19 1D interconnected 1D acoustic elements which is efficiently solved quasi-analytically (ATACAMAC) as proposed recently by Bauerheim et al. (2014b). This allows us to perform a Monte Carlo analysis (approx. 10, 000 ATACAMAC calculations), assuming that the uncertainties on the inputs are known. The reference Monte Carlo risk factor is then compared with that obtained by a less demanding UQ method. First, the dimension of the problem is reduced from 38 to only 3 parameters for the two regimes considered by the active subspace approach based on gradient correlations. Then, linear and quadratic analytical models based on the three active variables are fit using 100 ATACAMAC simulations. These low-order models are then replayed 100, 000 times to obtain the PDF of the growth rate as well as the risk factor estimation. Results show that for both regimes, the UQ method is able to accurately predict the risk factor of the configuration.
DOI：
10.1016/j.proci.2012.05.061
发表时间：
2013
期刊：
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影响因子：
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作者：
N. Worth;J. Dawson
通讯作者：
N. Worth;J. Dawson