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Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications: Proceedings of the 2020 Uqop International Conf, Vasile Massimiliano, Quagliarella Domenico


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Автор: Vasile Massimiliano, Quagliarella Domenico
Название:  Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications: Proceedings of the 2020 Uqop International Conf
ISBN: 9783030805418
Издательство: Springer
Классификация:



ISBN-10: 3030805417
Обложка/Формат: Hardcover
Страницы: 490
Вес: 0.82 кг.
Дата издания: 20.10.2021
Серия: Space technology proceedings
Язык: English
Издание: 1st ed. 2021
Иллюстрации: 131 tables, color; 137 illustrations, color; 35 illustrations, black and white; ix, 457 p. 172 illus., 137 illus. in color.
Размер: 23.39 x 15.60 x 2.54 cm
Читательская аудитория: Professional & vocational
Подзаголовок: Proceedings of the 2020 uqop international conference
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: The 2020 International Conference on Uncertainty Quantification & Optimization gathered together internationally renowned researchers in the fields of optimization and uncertainty quantification.


Model Validation and Uncertainty Quantification, Volume 3

Автор: H. Sezer Atamturktur; Babak Moaveni; Costas Papadi
Название: Model Validation and Uncertainty Quantification, Volume 3
ISBN: 3319353101 ISBN-13(EAN): 9783319353104
Издательство: Springer
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Цена: 26216.00 р.
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Описание:

Calibration of System Parameters Under Model Uncertainty.- On the Aggregation and Extrapolation of Uncertainty From Component to System Level Models.- Validation of Strongly Coupled Models: A Framework for Resource Allocation.- Fatigue Monitoring in Metallic Structures Using Vibration Measurements.- Uncertainty Propagation in Experimental Modal Analysis.- Quantification of Prediction Bounds Caused by Model Form Uncertainty.- Composite Fuselage Impact Testing and Simulation: A Model Calibration Exercise.- Noise Sensitivity Evaluation of Autoregressive Features Extracted From Structure Vibration.- Uncertainty Quantification and Integration in Multi-level Problems.- Reliability Quantification of High-speed Naval Vessels Based on SHM Data.- Structural Identification Using Response Measurements Under Base Excitation.- Bayesian FE Model Updating in the Presence of Modeling Errors.- Maintenance Planning Under Uncertainties Using a Continuous-state POMDP Framework.- Achieving Robust Design through Statistical Effect Screening.- Automated Modal Parameter Extraction and Statistical Analysis of the New Carquinez Bridge Response to Ambient Excitations.- Evaluation of a Time Reversal Method with Dynamic Time Warping matching function for human Fall Detection Using Structural Vibrations.- Uncertainty Quantification of Identified Modal Parameters Using the Fisher Information Criterion.- Excitation Related Uncertainty in Ambient Vibration Testing of Bridges.- Experiment-based Validation and Uncertainty Quantification of Coupled Multi-scale Plasticity Models.- Model Calibration and Uncertainty Quantification of A600 Blades.- Validation Assessment for Joint Problem Using an Energy Dissipation Model.- A Bayesian Damage Prognosis Approach Applied to Bearing Failure.- Sensitivity Analysis of Beams Controlled by Shunted Piezoelectric Transducers.- A Principal Component Analysis (PCA) Decomposition Based Validation Metric for use with Full Field Measurement Situations.- FEM Calibration With FRF Damping Equalization.- Evaluating Initial Model for Dynamic Model Updating: Criteria and Application.- Evaluating Convergence of Reduced Order Models Using Nonlinear Normal Modes.- Approximate Bayesian Computation for Finite Element Model Updating.- An Efficient Method for the Quantification of the Frequency Domain Statistical Properties of Short Response Time Series of Dynamic Systems.- Quantifying Uncertainty in Modal Parameters Estimated Using Higher Order Time Domain Algorithms.- Detection of Stress-stiffening Effect on Automotive Components.- Approach to Evaluate Uncertainty in Passive and Active Vibration Reduction.- Project-oriented Validation on a Cantilever Beam Under Vibration Active Control.- Inferring structural variability using modal analysis in a Bayesian framework.- Including SN-Curve Uncertainty in Fatigue Reliability Analyses of Wind Turbines.- Robust Design of Notching Profile under Epistemic Model Uncertainties.- Optimal Selection of Calibration and Validation Test Samples Under Uncertainty.- Uncertainty Quantification in Experimental Structural Dynamics Identification of Composite Material Structures.- Analysis of Numerical Errors in Strongly Coupled Numerical Models.- Robust Expansion of Experimental Mode Shapes Under Epistemic Uncertainties.

Uncertainty Quantification in Computational Fluid Dynamics

Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri
Название: Uncertainty Quantification in Computational Fluid Dynamics
ISBN: 3319346660 ISBN-13(EAN): 9783319346663
Издательство: Springer
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Цена: 13415.00 р.
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Описание: It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space.

Topics in Model Validation and Uncertainty Quantification, Volume 5

Автор: Todd Simmermacher; Scott Cogan; Babak Moaveni; Cos
Название: Topics in Model Validation and Uncertainty Quantification, Volume 5
ISBN: 1489996044 ISBN-13(EAN): 9781489996046
Издательство: Springer
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Цена: 25075.00 р.
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Описание: Topics in Model Validation and Uncertainty Quantification, Volume : Proceedings of the 31st IMAC, A Conference and Exposition on Structural Dynamics, 2013, the fifth volume of seven from the Conference, brings together contributions to this important area of research and engineering.

Introduction to Uncertainty Quantification

Автор: Sullivan, T.J.
Название: Introduction to Uncertainty Quantification
ISBN: 3319233947 ISBN-13(EAN): 9783319233949
Издательство: Springer
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Цена: 7317.00 р.
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Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study. Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field.

Topics in Model Validation and Uncertainty Quantification, Volume 4

Автор: T. Simmermacher; Scott Cogan; L.G. Horta; R. Barth
Название: Topics in Model Validation and Uncertainty Quantification, Volume 4
ISBN: 1489998667 ISBN-13(EAN): 9781489998668
Издательство: Springer
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Цена: 22796.00 р.
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Описание: Topics in Model Validation and Uncertainty Quantification, Volume 4, Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, the fourth volume of six from the Conference, brings together 19 contributions to this important area of research and engineering.

Introduction to uncertainty quantification

Автор: Sullivan, T.j.
Название: Introduction to uncertainty quantification
ISBN: 3319794787 ISBN-13(EAN): 9783319794785
Издательство: Springer
Рейтинг:
Цена: 7317.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved.

Uncertainty Quantification in Computational Fluid Dynamics

Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri
Название: Uncertainty Quantification in Computational Fluid Dynamics
ISBN: 3319008846 ISBN-13(EAN): 9783319008844
Издательство: Springer
Рейтинг:
Цена: 12196.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space.

Uncertainty Quantification and Stochastic Modelling with Excel

Автор: Souza De Cursi Eduardo
Название: Uncertainty Quantification and Stochastic Modelling with Excel
ISBN: 3030777561 ISBN-13(EAN): 9783030777562
Издательство: Springer
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Цена: 14635.00 р.
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Описание: This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool.

Optimization Under Uncertainty with Applications to Aerospace Engineering

Автор: Vasile Massimiliano
Название: Optimization Under Uncertainty with Applications to Aerospace Engineering
ISBN: 3030601684 ISBN-13(EAN): 9783030601683
Издательство: Springer
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Цена: 19514.00 р.
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Описание: In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.

Optimization Under Uncertainty with Applications to Aerospace Engineering

Автор: Vasile Massimiliano
Название: Optimization Under Uncertainty with Applications to Aerospace Engineering
ISBN: 303060165X ISBN-13(EAN): 9783030601652
Издательство: Springer
Цена: 19514.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: - Introduction to Spectral Methods for Uncertainty Quantification. - Introduction to Imprecise Probabilities. - Uncertainty Quantification in Lasso-Type Regularization Problems. - Reliability Theory. - An Introduction to Imprecise Markov Chains. - Fundamentals of Filtering. - Introduction to Optimisation. - An Introduction to Many-Objective Evolutionary Optimization. - Multilevel Optimisation. - Sequential Parameter Optimization for Mixed-Discrete Problems. - Parameter Control in Evolutionary Optimisation. - Response Surface Methodology. - Risk Measures in the Context of Robust and Reliability Based Optimization. - Best Practices for Surrogate Based Uncertainty Quantification in Aerodynamics and Application to Robust Shape Optimization. - In-flight Icing: Modeling, Prediction, and Uncertainty. - Uncertainty Treatment Applications: High-Enthalpy Flow Ground Testing. - Introduction to Evidence-Based Robust Optimisation.

Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications

Автор: Pratiksha Saxena, Dipti Singh, Millie Pant
Название: Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications
ISBN: 1466698853 ISBN-13(EAN): 9781466698857
Издательство: Mare Nostrum (Eurospan)
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Цена: 32848.00 р.
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Описание: Presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference source for engineers, managers, researchers, and post-graduate students.

Aerospace System Analysis and Optimization in Uncertainty

Автор: Brevault Loпc, Balesdent Mathieu, Morio Jйrфme
Название: Aerospace System Analysis and Optimization in Uncertainty
ISBN: 3030391280 ISBN-13(EAN): 9783030391287
Издательство: Springer
Цена: 17074.00 р.
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Описание: Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties.


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