Uncertainty Management for Robust Industrial Design in Aeronautics 1st edition by Charles Hirsch, Dirk Wunsch, Jacek Szumbarski, Łukasz Łaniewski Wołłk, Jordi Pons Prats 3319777672 9783319777672

Uncertainty Management for Robust Industrial Design in Aeronautics 1st edition by Charles Hirsch, Dirk Wunsch, Jacek Szumbarski, Łukasz Łaniewski-Wołłk, Jordi Pons-Prats – Ebook PDF Instant Download/DeliveryISBN:  3319777672, 9783319777672 

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ISBN-10 :  3319777672 

ISBN-13 :  9783319777672

Author:  Charles Hirsch, Dirk Wunsch, Jacek Szumbarski, Łukasz Łaniewski-Wołłk, Jordi Pons-Prats 

This book covers cutting-edge findings related to uncertainty quantification and optimization under uncertainties (i.e. robust and reliable optimization), with a special emphasis on aeronautics and turbomachinery, although not limited to these fields. It describes new methods for uncertainty quantification, such as non-intrusive polynomial chaos, collocation methods, perturbation methods, as well as adjoint based and multi-level Monte Carlo methods. It includes methods for characterization of most influential uncertainties, as well as formulations for robust and reliable design optimization. A distinctive element of the book is the unique collection of test cases with prescribed uncertainties, which are representative of the current engineering practice of the industrial consortium partners involved in UMRIDA, a level 1 collaborative project within the European Commission’s Seventh Framework Programme (FP7). All developed methods are benchmarked against these industrial challenges. Moreover, the book includes a section dedicated to Best Practice Guidelines for uncertainty quantification and robust design optimization, summarizing the findings obtained by the consortium members within the UMRIDA project. All in all, the book offers a authoritative guide to cutting-edge methodologies for uncertainty management in engineering design, covers a wide range of applications and discusses new ideas for future research and interdisciplinary collaborations.

Uncertainty Management for Robust Industrial Design in Aeronautics 1st table of contents:

Part I. The UMRIDA Project
Vision, Objectives and Research Activities
UMRIDA Test Case Database with Prescribed Uncertainties
Part II. Uncertainty Quantification (UQ) and Efficient Handling of a Large Number of Uncertainties
Uncertainties in Compressor and Aircraft Design
Estimation of Model Error Using Bayesian Model-Scenario Averaging with Maximum a Posterori-Estimates
Uncertainties for Thermoacoustics: A First Analysis
Numerical Uncertainties Estimation and Mitigation by Mesh Adaptation
General Introduction to Polynomial Chaos and Collocation Methods
Generalized Polynomial Chaos for Non-intrusive Uncertainty Quantification in Computational Fluid Dynamics
Non-intrusive Probabilistic Collocation Method for Operational, Geometrical, and Manufacturing Uncertainties in Engineering Practice
Non-intrusive Uncertainty Quantification by Combination of Reduced Basis Method and Regression-based Polynomial Chaos Expansion
Screening Analysis and Adaptive Sparse Collocation Method
General Introduction to Surrogate Model-Based Approaches to UQ
Comparing Surrogates for Estimating Aerodynamic Uncertainties of Airfoils
Ordinary Kriging Surrogates in Aerodynamics
Surrogates for Combustion Instabilities in Annular Combustors
General Introduction to Monte Carlo and Multi-level Monte Carlo Methods
Latin Hypercube Sampling-Based Monte Carlo Simulation: Extension of the Sample Size and Correlation Control
Multi-level Monte Carlo Method
Continuation Multi-level Monte Carlo
Introduction to Intrusive Perturbation Methods
Algorithmic Differentiation for Second Derivatives
Second-Order Derivatives for Geometrical Uncertainties
Part III. Application of Uncertainty Quantification to Industrial Challenges
Application of UQ for Turbine Blade CHT Computations
Application of Uncertainty Quantification Methodologies to Falcon
Application of UQ to Combustor Design
Manufacturing Uncertainties for Acoustic Liners
Manufacturing Uncertainties in High-Pressure Compressors
Part IV. Robust Design Optimization (RDO) and Applications
Formulations for Robust Design and Inverse Robust Design
Robust Design of Initial Boundary Value Problems
Robust Optimization with Gaussian Process Models
Robust Design in Turbomachinery Applications
Robust Design Measures for Airfoil Shape Optimization
Robust Design with MLMC
Value-at-Risk and Conditional Value-at-Risk in Optimization Under Uncertainty
Combination of Polynomial Chaos with Adjoint Formulations for Optimization Under Uncertainties
Robust Multiphysics Optimization of Fan Blade
UQ Sensitivity Analysis and Robust Design Optimization of a Supersonic Natural Laminar Flow Wing-Body
Robust Compressor Optimization by Evolutionary Algorithms
Robust Optimization of Acoustic Liners
Application of Robust Design Methodologies to Falcon
Part V. UMRIDA Best Practices: Methods for Uncertainty Quantification, RDO and Their Applicability Range
Uncertainties Identification and Quantification
Polynomial Chaos and Collocation Methods and Their Range of Applicability
Surrogate Model-Based Approaches to UQ and Their Range of Applicability
Monte Carlo-Based and Sampling-Based Methods and Their Range of Applicability
Introduction to Intrusive Perturbation Methods and Their Range of Applicability
Use of Open Source UQ Libraries
Uncertainty Quantification in an Engineering Design Software System
Use of Automatic Differentiation Tools at the Example of TAPENADE
Formulations for Robust Design and Inverse Robust Design
Use of RD in Multiphysics Applications
Geometrical Uncertainties—Accuracy of Parametrization and Its Influence on UQ and RDO Results
Analysis and Interpretation of Probabilistic Simulation Output
Summary of UMRIDA Best Practices
Part VI. Conclusions
Project Summary and Outlook

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Tags: Uncertainty, Management, Robust Industrial Design, Aeronautics, Charles Hirsch, Dirk Wunsch, Jacek Szumbarski, Łukasz Łaniewski Wołłk, Jordi Pons Prats