A Gaussian-process-based framework for high-dimensional uncertainty quantification analysis in thermoacoustic instability predictions

Keyphrases

• Gaussian Process 100%
• Uncertainty Quantification 100%
• Process-based 100%
• Thermoacoustic Instability 100%
• Instability Prediction 100%
• High-dimensional Uncertainty Quantification 100%
• System Parameters 80%
• Acoustic System 80%
• Finite Impulse Response 40%
• Impulse Response Model 40%
• Thermoacoustics 40%
• Flame Model 40%
• Flame Describing Function 40%
• Cycle Frequency 20%
• Highly Accurate 20%
• Machine Learning 20%
• Limit Cycle 20%
• Computational Cost 20%
• Acoustics 20%
• Training Model 20%
• Sensitivity Analysis 20%
• Monte Carlo Simulation 20%
• Variational 20%
• Linear Case 20%
• Learning Communities 20%
• Statistical Description 20%
• Active Learning Strategies 20%
• Parametric Investigation 20%
• Quantification Framework 20%
• Modal Frequency 20%
• Robust Design 20%
• Surrogate-based 20%
• Gaussian Process Model 20%
• Cycle Amplitude 20%
• Response Model 20%
• Flame Response 20%
• Gaussian Process Surrogate 20%
• Thermoacoustic Model 20%
• Nonlinear Thermoacoustics 20%
• Nonlinear Bifurcation 20%
• Bifurcation Study 20%
• Linear Growth Rate 20%
• Reliability Prediction 20%
• Calculation Results 20%

Engineering

• Uncertainty Quantification 100%
• Thermoacoustic Instability 100%
• Gaussians 100%
• System Parameter 80%
• Finite Impulse Response 40%
• Surrogate Model 20%
• Cycle Frequency 20%
• Model Response 20%
• Robust Design 20%
• Computational Cost 20%
• Limit Cycle 20%
• Learning System 20%