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Author: Ramana V. Grandhi
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
Multiple configurations in various stages of aircraft design have to be experimentally tested and validated to study the performance of various systems subjected to non-deterministic design parameters. These tests are expensive and time consuming, increasing the acquisition cost and time for military aircraft/equipment. Therefore, analytical certification aims at reducing/eliminating the expensive prototype testing during these intermediate design stages by propagating the input variance through the design. Analytical certification involves modeling the variance/uncertainties in the design parameters and estimating the variance in the component/system performance. Based on the nature and extent of uncertainty existing in an engineering system, different approaches can be used for uncertainty propagation. If the uncertainty of the system is due to imprecise information and lack of statistical data, the Possibilistic theory can be used. During preliminary design, uncertainties need to be accounted for and due to lack of sufficient information assigning a probability distribution may not be possible. Moreover, the flight conditions (loads, control surface settings, etc.) during a mission could take values within certain bounds, which do not follow any particular pattern. The uncertain information in these cases is available as intervals with lower and upper limits. In this case, the fuzzy arithmetic based method is suitable to estimate the possibility of failure. The use of surrogate models to improve the efficiency of prediction is presented in this paper. Various numerical examples are presented to demonstrate the applicability of the method to practical problems.
Author: Ramana V. Grandhi
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
Multiple configurations in various stages of aircraft design have to be experimentally tested and validated to study the performance of various systems subjected to non-deterministic design parameters. These tests are expensive and time consuming, increasing the acquisition cost and time for military aircraft/equipment. Therefore, analytical certification aims at reducing/eliminating the expensive prototype testing during these intermediate design stages by propagating the input variance through the design. Analytical certification involves modeling the variance/uncertainties in the design parameters and estimating the variance in the component/system performance. Based on the nature and extent of uncertainty existing in an engineering system, different approaches can be used for uncertainty propagation. If the uncertainty of the system is due to imprecise information and lack of statistical data, the Possibilistic theory can be used. During preliminary design, uncertainties need to be accounted for and due to lack of sufficient information assigning a probability distribution may not be possible. Moreover, the flight conditions (loads, control surface settings, etc.) during a mission could take values within certain bounds, which do not follow any particular pattern. The uncertain information in these cases is available as intervals with lower and upper limits. In this case, the fuzzy arithmetic based method is suitable to estimate the possibility of failure. The use of surrogate models to improve the efficiency of prediction is presented in this paper. Various numerical examples are presented to demonstrate the applicability of the method to practical problems.
Author: Francesco Montomoli
Publisher: Springer
ISBN: 3319929437
Category : Technology & Engineering
Languages : en
Pages : 204
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Book Description
This book introduces design techniques developed to increase the safety of aircraft engines, and demonstrates how the application of stochastic methods can overcome problems in the accurate prediction of engine lift caused by manufacturing error. This in turn addresses the issue of achieving required safety margins when hampered by limits in current design and manufacturing methods. The authors show that avoiding the potential catastrophe generated by the failure of an aircraft engine relies on the prediction of the correct behaviour of microscopic imperfections. This book shows how to quantify the possibility of such failure, and that it is possible to design components that are inherently less risky and more reliable. This new, updated and significantly expanded edition gives an introduction to engine reliability and safety to contextualise this important issue, evaluates newly-proposed methods for uncertainty quantification as applied to jet engines. Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines will be of use to gas turbine manufacturers and designers as well as CFD practitioners, specialists and researchers. Graduate and final year undergraduate students in aerospace or mathematical engineering may also find it of interest.
Author: Francesco Montomoli
Publisher:
ISBN: 9783319146829
Category :
Languages : en
Pages :
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Book Description
This book introduces novel design techniques developed to increase the safety of aircraft engines. The authors demonstrate how the application of uncertainty methods can overcome problems in the accurate prediction of engine lift, caused by manufacturing error. This in turn ameliorates the difficulty of achieving required safety margins imposed by limits in current design and manufacturing methods. This text shows that even state-of-the-art computational fluid dynamics (CFD) are not able to predict the same performance measured in experiments; CFD methods assume idealised geometries but ideal geometries do not exist, cannot be manufactured and their performance differs from real-world ones. By applying geometrical variations of a few microns, the agreement with experiments improves dramatically, but unfortunately the manufacturing errors in engines or in experiments are unknown. In order to overcome this limitation, uncertainty quantification considers the probability density functions of manufacturing errors. It is then possible to predict the overall variation of the jet engine performance using stochastic techniques. Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines demonstrates that some geometries are not affected by manufacturing errors, meaning that it is possible to design safer engines. Instead of trying to improve the manufacturing accuracy, uncertainty quantification when applied to CFD is able to indicate an improved design direction. This book will be of interest to gas turbine manufacturers and designers as well as CFD practitioners, specialists and researchers. Graduate and final year undergraduate students may also find it of use.
Author: Xin Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Massimiliano Vasile
Publisher: Springer Nature
ISBN: 3030805425
Category : Technology & Engineering
Languages : en
Pages : 448
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Book Description
The 2020 International Conference on Uncertainty Quantification & Optimization gathered together internationally renowned researchers in the fields of optimization and uncertainty quantification. The resulting proceedings cover all related aspects of computational uncertainty management and optimization, with particular emphasis on aerospace engineering problems. 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.
Author: Charles Hirsch
Publisher: Springer
ISBN: 331977767X
Category : Technology & Engineering
Languages : en
Pages : 799
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Book Description
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.
Author:
Publisher:
ISBN:
Category : Space vehicles
Languages : en
Pages : 64
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Book Description
Author: Jonathan Koopman
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
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Book Description
"Abstract: The Federal Aviation Administration, Office of Environment and Energy (FAA-AEE) has developed the Aviation Environmental Design Tool (AEDT) version 2a software system with the support of the following development team: FAA, National Aeronautics and Space Administration (NASA), U.S. DOT Volpe National Transportation Systems Center (Volpe Center), ATAC Corporation, Metron Aviation, Wyle Laboratories, CSSI, Inc., Foliage, MIT, and Georgia Tech. AEDT 2a is designed to dynamically model aircraft performance in space and time to compute aircraft noise, emissions, and fuel burn. This document is the AEDT 2a Service Pack 2 Uncertainty Quantification Supplemental Report, which compares changes between AEDT 2a and Service Pack 2 based on verification and validation and capability demonstrations of the software's methodologies and performance in comparison with legacy models."--Technical report documentation page.
Author: Robert Barthorpe
Publisher: Springer
ISBN: 3319548581
Category : Technology & Engineering
Languages : en
Pages : 368
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Book Description
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty
Author: Sez Atamturktur
Publisher: Springer
ISBN: 3319297546
Category : Technology & Engineering
Languages : en
Pages : 366
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Book Description
Model Validation and Uncertainty Quantifi cation, Volume 3. Proceedings of the 34th IMAC, A Conference and Exposition on Dynamics of Multiphysical Systems: From Active Materials to Vibroacoustics, 2016, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. Th e collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: • Uncertainty Quantifi cation & Model Validation • Uncertainty Propagation in Structural Dynamics • Bayesian & Markov Chain Monte Carlo Methods • Practical Applications of MVUQ • Advances in MVUQ & Model Updating • Robustness in Design & Validation • Verifi cation & Validation Methods
