Buch, Englisch, Band 8, 457 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 703 g
Reihe: Space Technology Proceedings
Proceedings of the 2020 UQOP International Conference
Buch, Englisch, Band 8, 457 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 703 g
Reihe: Space Technology Proceedings
ISBN: 978-3-030-80544-9
Verlag: Springer International Publishing
The book contributions are organized under four major themes:
- Applications of Uncertainty in Aerospace & Engineering
- Imprecise Probability, Theory and Applications
- Robust and Reliability-Based Design Optimisation in Aerospace Engineering
- Uncertainty Quantification, Identification and Calibration in Aerospace Models
This proceedings volume is useful across disciplines, as it brings the expertise of theoretical and application researchers together in a unified framework.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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. Computingbounds 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.