Gaussian Process Surrogate Models for Vibroacoustic Simulations

Keyphrases

• Vibro-acoustic Simulation 100%
• Gaussian Process Surrogate 100%
• Gaussian Process Regression 50%
• Kernel Function 50%
• Computational Cost 50%
• Finite Element Model 50%
• Surrogate Model 50%
• Gaussian Process 25%
• Machine Learning 25%
• Deep Learning 25%
• High-frequency Range 25%
• Damping System 25%
• Repeated Evaluation 25%
• Academic Model 25%
• Prediction Accuracy 25%
• Uncertainty Quantification 25%
• Detailed Model 25%
• Load Case 25%
• Computationally Intensive 25%
• System Complexity 25%
• Multiple Evaluation 25%
• Varying Parameters 25%
• Data Complexity 25%
• Noise Vibration Harshness 25%
• Body-in-white 25%
• System Load 25%
• Gaussian Process Model 25%
• Vehicle Noise 25%
• Learning Kernels 25%
• System Uncertainty 25%
• Number of Training Samples 25%
• White Model 25%
• Non-stationary Learning 25%
• Spectral Learning 25%
• Scale Variance 25%

Engineering

• Surrogate Model 100%
• Gaussians 100%
• Finite Element Modeling 40%
• Input Parameter 40%
• Computational Cost 40%
• Uncertainty Quantification 20%
• Load Case 20%
• Length Scale 20%
• Body in White 20%
• Learning System 20%
• Deep Learning Method 20%

Material Science

• Finite Element Modeling 100%