Download or read book Data driven Uncertainty Quantification for High dimensional Engineering Problems written by Christos Lataniotis and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Driven Uncertainty Quantification for Large Scale Simulations written by Fabian Franzelin and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Quantification of Uncertainty Improving Efficiency and Technology written by Marta D'Elia and published by Springer Nature. This book was released on 2020-07-30 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book’s content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors.

Download or read book Uncertainty Quantification in High Dimensional Problems written by Pamphile Roy and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainties are predominant in the world that we know. Referring therefore to a nominal value is too restrictive, especially when it comes to complex systems. Understanding the nature and the impact of these uncertainties has become an important aspect of engineering work. On a societal point of view, uncertainties play a role in terms of decision-making. From the European Commission through the Better Regulation Guideline, impact assessments are now advised to take uncertainties into account. In order to understand the uncertainties, the mathematical field of uncertainty quantification has been formed. UQ encompasses a large palette of statistical tools and it seeks to link a set of input perturbations on a system (design of experiments) towards a quantity of interest. The purpose of this work is to propose improvements on various methodological aspects of uncertainty quantification applied to costly numerical simulations. This is achieved by using existing methods with a multi-strategy approach but also by creating new methods. In this context, novel sampling and resampling approaches have been developed to better capture the variability of the physical phenomenon when dealing with a high number of perturbed inputs. These allow to reduce the number of simulation required to describe the system. Moreover, novel methods are proposed to visualize uncertainties when dealing with either a high dimensional input parameter space or a high dimensional quantity of interest. The developed methods can be used in various fields like hydraulic modelling and aerodynamic modelling. Their capabilities are demonstrated in realistic systems using well established computational fluid dynamics tools. Lastly, they are not limited to the use of numerical experiments and can be used equally for real experiments.

Download or read book Computational Fluid Flow and Heat Transfer written by Mukesh Kumar Awasthi and published by CRC Press. This book was released on 2024-04-25 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text provides insight into the different mathematical tools and techniques that can be applied to the analysis and numerical computations of flow models. It further discusses important topics such as the heat transfer effect on boundary layer flow, modeling of flows through porous media, anisotropic polytrophic gas model, and thermal instability in viscoelastic fluids. This book: Discusses modeling of Rayleigh-Taylor instability in nanofluid layer and thermal instability in viscoelastic fluids Covers open FOAM simulation of free surface problems, and anisotropic polytrophic gas model Highlights the Sensitivity Analysis in Aerospace Engineering, MHD Flow of a Micropolar Hybrid Nanofluid, and IoT-Enabled Monitoring for Natural Convection Presents thermal behavior of nanofluid in complex geometries and heat transfer effect on Boundary layer flow Explains natural convection heat transfer in non-Newtonian fluids and homotropy series solution of the boundary layer flow Illustrates modeling of flows through porous media and investigates Shock-driven Richtmyer-Meshkov instability It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of Applied Sciences, Mechanical Engineering, Manufacturing Engineering, Production Engineering, Industrial engineering, Automotive engineering, and Aerospace engineering.

Download or read book Trends in Renewable Energies Offshore written by C. Guedes Soares and published by CRC Press. This book was released on 2022-11-02 with total page 1920 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renewable energy resources offshore are a growing contributor to the total energy production in a growing number of countries. As a result the interest in the topic is increasing. Trends in Renewable Energies Offshore includes the papers presented at the 5th International Conference on Renewable Energies Offshore (RENEW 2022, Lisbon, Portugal, 8-10 November 2022), and covers recent developments and experiences gained in concept development, design and operation of such devices. The scope of the contributions is broad, covering all aspects of renewable energies offshore activities, including: • Resource assessment • Tidal Energy • Wave Energy • Wind Energy • Solar Energy • Renewable Energy Devices • Multiuse Platforms • Maintenance planning • Materials and structural design Trends in Renewable Energies Offshore will be of interest to academics and professionals involved or interested in applications of renewable energy resources offshore. The ‘Proceedings in Marine Technology and Ocean Engineering’ series is dedicated to the publication of proceedings of peer-reviewed international conferences dealing with various aspects of ‘Marine Technology and Ocean Engineering’. The Series includes the proceedings of the following conferences: the International Maritime Association of the Mediterranean (IMAM) conferences, the Marine Structures (MARSTRUCT) conferences, the Renewable Energies Offshore (RENEW) conferences and the Maritime Technology (MARTECH) conferences. The ‘Marine Technology and Ocean Engineering’ series is also open to new conferences that cover topics on the sustainable exploration and exploitation of marine resources in various fields, such as maritime transport and ports, usage of the ocean including coastal areas, nautical activities, the exploration and exploitation of mineral resources, the protection of the marine environment and its resources, and risk analysis, safety and reliability. The aim of the series is to stimulate advanced education and training through the wide dissemination of the results of scientific research.

Download or read book Uncertainty Quantification in Data Driven Simulation and Optimization written by Huajie Qian and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We demonstrate how our obtained solutions satisfy statistical feasibility guarantees with light dimension dependence, and how they are asymptotically optimal and thus regarded as the least conservative with respect to the considered reformulation classes.

Download or read book Dynamic Data Driven Environmental Systems Science written by Sai Ravela and published by Springer. This book was released on 2015-11-26 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Conference on Dynamic Data-Driven Environmental Systems Science, DyDESS 2014, held in Cambridge, MA, USA, in November 2014.The 24 revised full papers and 7 short papers were carefully reviewed and selected from 62 submissions and cover topics on sensing, imaging and retrieval for the oceans, atmosphere, space, land, earth and planets that is informed by the environmental context; algorithms for modeling and simulation, downscaling, model reduction, data assimilation, uncertainty quantification and statistical learning; methodologies for planning and control, sampling and adaptive observation, and efficient coupling of these algorithms into information-gathering and observing system designs; and applications of methodology to environmental estimation, analysis and prediction including climate, natural hazards, oceans, cryosphere, atmosphere, land, space, earth and planets.

Download or read book Bayesian Reinforcement Learning written by Mohammad Ghavamzadeh and published by . This book was released on 2015-11-18 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods for machine learning have been widely investigated, yielding principled methods for incorporating prior information into inference algorithms. This monograph provides the reader with an in-depth review of the role of Bayesian methods for the reinforcement learning (RL) paradigm. The major incentives for incorporating Bayesian reasoning in RL are that it provides an elegant approach to action-selection (exploration/exploitation) as a function of the uncertainty in learning, and it provides a machinery to incorporate prior knowledge into the algorithms. Bayesian Reinforcement Learning: A Survey first discusses models and methods for Bayesian inference in the simple single-step Bandit model. It then reviews the extensive recent literature on Bayesian methods for model-based RL, where prior information can be expressed on the parameters of the Markov model. It also presents Bayesian methods for model-free RL, where priors are expressed over the value function or policy class. Bayesian Reinforcement Learning: A Survey is a comprehensive reference for students and researchers with an interest in Bayesian RL algorithms and their theoretical and empirical properties.

Download or read book Uncertainty Quantification in Laminated Composites written by Sudip Dey and published by CRC Press. This book was released on 2018-09-19 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.

Download or read book Proceedings of the 2013 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics Vision and Fusion Laboratory written by Beyerer, Juergen and published by KIT Scientific Publishing. This book was released on 2014-07-23 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of 13 review technical reports summarizing the presentations at the 2013 Joint Workshop of Fraunhofer IOSB and the Vision and Fusion Laboratory at KIT Karlsruhe, made by the students of the both institutions. The topics include image processing, visual inspection, pattern recognition and classification, planning and decision-making, human-machine interaction, world modeling, and optical signal processing.

Download or read book Computational Uncertainty Quantification for Inverse Problems written by Johnathan M. Bardsley and published by SIAM. This book was released on 2018-08-01 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB® code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers. Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.

Download or read book High Dimensionality Challenges in Uncertainty Quantification written by and published by . This book was released on 2014 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data driven Uncertainty Quanification and Propagation in Structural Dynamics Inverse Problems written by Omid Sedehi and published by . This book was released on 2019 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Data driven Uncertainty Quantification Method for Scarce Data and Rare Events written by Richard Benedikt Heinrich Ahlfeld and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Scientific Computing in Electrical Engineering written by Martijn van Beurden and published by Springer Nature. This book was released on 2022-03-11 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference has an interdisciplinary focus and aims to bring together scientists – mathematicians, electrical engineers, computer scientists, and physicists, from universities and industry – to have in-depth discussions of the latest scientific results in Computational Science and Engineering relevant to Electrical Engineering and to stimulate and inspire active participation of young researchers.

Download or read book Uncertainty in Mechanical Engineering written by Peter F. Pelz and published by Springer Nature. This book was released on 2021-05-26 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book reports on methods and technologies to describe, evaluate and control uncertainty in mechanical engineering applications. It brings together contributions by engineers, mathematicians and legal experts, offering a multidisciplinary perspective on the main issues affecting uncertainty throughout the complete system lifetime, which includes process and product planning, development, production and usage. The book is based on the proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), organized by the Collaborative Research Center (CRC) 805 of the TU Darmstadt, and held online on June 7–8, 2021. All in all, it offers a timely resource for researchers, graduate students and practitioners in the field of mechanical engineering, production engineering and engineering optimization.