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Uncertainty quantification of vibro-acoustic coupling problems for robotic manta ray models based on deep learning
2 references·1 citing·12 second hop
Uncertainty quantification of vibro-acoustic coupling problems for robotic manta ray models based on deep learning (2024)Uncertainty quantification of vibro-acous…Recent Advances in Surrogate Modeling Methods for Uncertainty Quantification and Propagation (2022)Recent Advances in Surrogate …A sample-efficient deep learning method for multivariate uncertainty qualification of acoustic–vibration interaction problems (2022)A sample-efficient deep learn…Deep-neural-network-based framework for the accelerating uncertainty quantification of a structural–acoustic fully coupled system in a shallow sea (2025)Deep-neural-network-based fra…Stochastic Finite Elements: A Spectral Approach (1991)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Monte Carlo Based Isogeometric Stochastic Finite Element Method for Uncertainty Quantization in Vibration Analysis of Piezoelectric Materials (2022)Uncertainty quantification of mechanical property of piezoelectric materials based on isogeometric stochastic FEM with generalized nth-order perturbation (2023)Aleatory or epistemic? Does it matter? (2008)Simulation and the Monte Carlo Method (2016)Reliability-constrained optimal attitude-vibration control for rigid-flexible coupling satellite using interval dimension-wise analysis (2023)A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications (2024)Dimensional decomposition-aided metamodels for uncertainty quantification and optimization in engineering: A review (2024)Deep Neural Networks as Scientific Models (2019)Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey (2020)
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References

  • 2022Recent Advances in Surrogate Modeling Methods for Uncertainty Quantification and Propagation143 cited
  • 2022A sample-efficient deep learning method for multivariate uncertainty qualification of acoustic–vibration interaction problems82 cited

Cited by

  • 2025Deep-neural-network-based framework for the accelerating uncertainty quantification of a structural–acoustic fully coupled system in a shallow sea27 cited

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