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Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications: Proceedings of the 2020 Uqop International Conf

Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications: Proceedings of the 2020 Uqop International Conf (Hardcover, 2021)

Massimiliano Vasile, Domenico Quagliarella (엮은이)
Springer
551,690원

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Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications: Proceedings of the 2020 Uqop International Conf
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책 정보

· 제목 : Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications: Proceedings of the 2020 Uqop International Conf (Hardcover, 2021) 
· 분류 : 외국도서 > 기술공학 > 기술공학 > 우주공학
· ISBN : 9783030805418
· 쪽수 : 457쪽
· 출판일 : 2022-01-28

목차

Chapter 1. Cloud Uncertainty Quantification for Runback Ice Formations in Anti-Ice Electro-Thermal Ice Protection Systems.- Chapter 2. Multi-fidelity Surrogate Assisted Design Optimisation of an Airfoil under Uncertainty using Far-Field Drag Approximation.- Chapter 3. Scalable dynamic asynchronous Monte Carlo framework applied to wind engineering problems.- Chapter 4. Multi-Objective Optimal Design and Maintenance for Systems Based on Calendar Times Using MOEA/D-DE.- Chapter 5. From Uncertainty Quanti cation to Shape Optimization: Cross-Fertilization of Methods for Dimensionality Reduction.- Chapter 6. Multi-Objective Robustness Analysis of the Polymer Extrusion Process.- Chapter 7. Quantification of operational and geometrical uncertainties of a 1.5 stage axial compressor with cavity leakage flows.- Chapter 8. Can Uncertainty Propagation Solve the Mysterious Case of Snoopy ?.- Chapter 9. Robust Particle Filter for Space Navigation under Epistemic Uncertainty.- Chapter 10. Computing bounds for imprecise continuous-time Markov chains using normal cones.- Chapter 11. Simultaneous Sampling for Robust Markov Chain Monte Carlo Inference.- Chapter 12. Computing Expected Hitting Times for Imprecise Markov Chains.- Chapter 13. Multi-Objective Robust Trajectory Optimization of Multi Asteroid Fly-By Under Epistemic Uncertainty.- Chapter 14. Reliability-based Robust Design Optimization of a Jet Engine Nacelle.- Chapter 15. Bayesian Optimization for Robust Solutions under Uncertain Input.- Chapter 16. Optimization under Uncertainty of Shock Control Bumps for Transonic Wings.- Chapter 17. Multi-objective design optimisation of an airfoil with geometrical uncertainties leveraging multi- delity Gaussian process regression.- Chapter 18. High-Lift Devices Topology Robust Optimisation using Machine Learning Assisted Optimisation.- Chapter 19. Network Resilience Optimisation of Complex Systems.- Chapter 20. Gaussian Processes for CVaR approximation in Robust Aerodynamic Shape Design.- Chapter 21. Inference methods for gas/surface interaction models: from deterministic approaches to Bayesian techniques.- Chapter 22. Bayesian Adaptive Selection Under Prior Ignorance.- Chapter 23. A Machine-Learning Framework for Plasma-Assisted Combustion using Principal Component Analysis and Gaussian Process Regression.- Chapter 24. Estimating exposure fraction from radiation biomarkers: a comparison of frequentist and Bayesian approaches.- Chapter 25. A Review of some recent advancements in Non-Ideal Compressible Fluid Dynamics.- Chapter 26. Dealing with high dimensional inconsistent measurements in inverse problems using surrogate modeling: an approach based on sets and intervals.- Chapter 27. Stochastic Preconditioners for Domain Decomposition Methods.- Index.

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