Download or read book Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-09-27 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical simulation has now become an integral part of engineering design process. Critical design decisions are routinely made based on the simulation results and conclusions. Verification and validation of the reliability of the numerical simulation is therefore vitally important in the engineering design processes. We propose to develop theories and methodologies that can automatically provide quantitative information about the reliability of the numerical simulation by estimating numerical approximation error, computational model induced errors and the uncertainties contained in the mathematical models so that the reliability of the numerical simulation can be verified and validated. We also propose to develop and implement methodologies and techniques that can control the error and uncertainty during the numerical simulation so that the reliability of the numerical simulation can be improved. Zhu, J. Z. and He, Guowei and Bushnell, Dennis M. (Technical Monitor) Langley Research Center NASA/CR-2002-211744, NAS 1.26:211744, ICASE-IR-41

Download or read book Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics written by J. Z. Zhu and published by . This book was released on 2002 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Uncertainty Analysis for Fluid Mechanics with Applications written by Robert W. Walters and published by . This book was released on 2002 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper reviews uncertainty analysis methods and their application to fundamental problems in fluid dynamics. Probabilistic (Monte-Carlo, Moment methods, Polynomial Chaos) and non-probabilistic methods (Interval Analysis Propagation of error using sensitivity derivatives) are described and implemented. Results are presented for a model convection equation with a source term, a model non-linear convection-diffusion equation; supersonic flow over wedges, expansion corners, and an airfoil; and two-dimensional laminar boundary layer flow.

Download or read book Error Estimation and Adaptive Discretization Methods in Computational Fluid Dynamics written by Timothy J. Barth and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computational fluid dynamics (CFD) is applied to ever more demanding fluid flow problems, the ability to compute numerical fluid flow solutions to a user specified tolerance as well as the ability to quantify the accuracy of an existing numerical solution are seen as essential ingredients in robust numerical simulation. Although the task of accurate error estimation for the nonlinear equations of CFD seems a daunting problem, considerable effort has centered on this challenge in recent years with notable progress being made by the use of advanced error estimation techniques and adaptive discretization methods. To address this important topic, a special course wasjointly organized by the NATO Research and Technology Office (RTO), the von Karman Insti tute for Fluid Dynamics, and the NASA Ames Research Center. The NATO RTO sponsored course entitled "Error Estimation and Solution Adaptive Discretization in CFD" was held September 10-14, 2002 at the NASA Ames Research Center and October 15-19, 2002 at the von Karman Institute in Belgium. During the special course, a series of comprehensive lectures by leading experts discussed recent advances and technical progress in the area of numerical error estimation and adaptive discretization methods with spe cific emphasis on computational fluid dynamics. The lecture notes provided in this volume are derived from the special course material. The volume con sists of 6 articles prepared by the special course lecturers.

Download or read book Uncertainty Quantification in Computational Fluid Dynamics written by Hester Bijl and published by Springer Science & Business Media. This book was released on 2013-09-20 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. 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. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.

Download or read book Quantification of Uncertainty in Computational Fluid Dynamics written by and published by . This book was released on 1995 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation of Grid induced Errors in Computational Fluid Dynamics Solutions Using a Discrete Error Transport Equation written by Brandon Riley Williams and published by . This book was released on 2009 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines written by Francesco Montomoli and published by Springer. This book was released on 2018-06-21 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book On Goal oriented Error Estimation and Adaptivity for Nonlinear Systems with Uncertain Data and Application to Flow Problems written by Corey Michael Bryant and published by . This book was released on 2014 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this work is to develop a posteriori error estimates and adaptive strategies for the numerical solution to nonlinear systems of partial differential equations with uncertain data. Areas of application cover problems in fluid mechanics including a Bayesian model selection study of turbulence comparing different uncertainty models. Accounting for uncertainties in model parameters may significantly increase the computational time when simulating complex problems. The premise is that using error estimates and adaptively refining the solution process can reduce the cost of such simulations while preserving their accuracy within some tolerance. New insights for goal-oriented error estimation for deterministic nonlinear problems are first presented. Linearization of the adjoint problems and quantities of interest introduces higher-order terms in the error representation that are generally neglected. Their effects on goal-oriented adaptive strategies are investigated in detail here. Contributions on that subject include extensions of well-known theoretical results for linear problems to the nonlinear setting, computational studies in support of these results, and an extensive comparative study of goal-oriented adaptive schemes that do, and do not, include the higher-order terms. Approaches for goal-oriented error estimation for PDEs with uncertain coefficients have already been presented, but lack the capability of distinguishing between the different sources of error. A novel approach is proposed here, that decomposes the error estimate into contributions from the physical discretization and the uncertainty approximation. Theoretical bounds are proven and numerical examples are presented to verify that the approach identifies the predominant source of the error in a surrogate model. Adaptive strategies, that use this error decomposition and refine the approximation space accordingly, are designed and tested. All methodologies are demonstrated on benchmark flow problems: Stokes lid-driven cavity, 1D Burger's equation, 2D incompressible flows at low Reynolds numbers. The procedure is also applied to an uncertainty quantification study of RANS turbulence models in channel flows. Adaptive surrogate models are constructed to make parameter uncertainty propagation more efficient. Using surrogate models and adaptivity in a Bayesian model selection procedure, it is shown that significant computational savings can be gained over the full RANS model while maintaining similar accuracy in the predictions.

Download or read book Uncertainty Analysis for Engineers and Scientists written by Faith A. Morrison and published by Cambridge University Press. This book was released on 2021-01-07 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLAB®, making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.

Download or read book Error Estimation and Control in Computational Fluid Dynamics written by J. I. Oden and published by . This book was released on 1993 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Importance of Uncertainty Estimation in Computational Fluid Dynamics written by Raymond R. Cosner and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pade legendre Method for Uncertainty Quantification with Fluid Dynamics Applications written by Tonkid Chantrasmi and published by Stanford University. This book was released on 2011 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The Pade-Legendre (PL) method, a novel approach for uncertainty quantification is introduced. The proposed method uses a rational function expansion and is designed to effectively characterize uncertainties in strongly non-linear or discontinuous systems. The discontinuities can be either in the underlying functions (inherent discontinuities) or from lack of sufficient data resolution (multi-scale discontinuities). In the former case, PL method can produce an accurate response surface without spurious oscillations and does not require prior knowledge of the discontinuities. For the latter type of discontinuities, the PL method can help reduce the number of deterministic simulations required to accurately represent the response surface. If sufficient data resolution is achieved, the PL method degenerates to standard polynomial reconstruction. The present approach is illustrated in a number of applications as an uncertainty propagation technique. Moreover, the method is applied to an inference problem in which a sharp discontinuity in the system input is present. The PL method shows a considerable improvement over the traditional approach when discontinuities are present. In addition, an ongoing effort called the UQ Experiment in which we used the PL method to help design the experimental setup is discussed.

Download or read book Uncertainty Quantification In Computational Science Theory And Application In Fluids And Structural Mechanics written by Sunetra Sarkar and published by World Scientific. This book was released on 2016-08-18 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decade, research in Uncertainty Quantification (UC) has received a tremendous boost, in fluid engineering and coupled structural-fluids systems. New algorithms and adaptive variants have also emerged.This timely compendium overviews in detail the current state of the art of the field, including advances in structural engineering, along with the recent focus on fluids and coupled systems. Such a strong compilation of these vibrant research areas will certainly be an inspirational reference material for the scientific community.

Download or read book Applied and Computational Fluid Mechanics written by Scott Post and published by Jones & Bartlett Publishers. This book was released on 2010-01-30 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for the fluid mechanics course for mechanical, civil, and aerospace engineering students, or as a reference for professional engineers, this up to date text uses computer algorithms and applications to solve modern problems related to fluid flow, aerodynamics, and thermodynamics. Algorithms and codes for numerical solutions of fluid problems, which can be implemented in programming environments such as MATLAB, are used throughout the book. The author also uses non-language specific algorithms to force the students to think through the logic of the solution technique as they translate the algorithm into the software they are using. The text also includes an introduction to Computational Fluid Dynamics, a well-established method in the design of fluid machinery and heat transfer applications. A DVD accompanies every new printed copy of the book and contains the source code, MATLAB files, third-party simulations, color figures, and more.

Download or read book Uncertainty and Error in Computational Simulations written by and published by . This book was released on 1997 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present paper addresses the question: ''What are the general classes of uncertainty and error sources in complex, computational simulations?'' This is the first step of a two step process to develop a general methodology for quantitatively estimating the global modeling and simulation uncertainty in computational modeling and simulation. The second step is to develop a general mathematical procedure for representing, combining and propagating all of the individual sources through the simulation. The authors develop a comprehensive view of the general phases of modeling and simulation. The phases proposed are: conceptual modeling of the physical system, mathematical modeling of the system, discretization of the mathematical model, computer programming of the discrete model, numerical solution of the model, and interpretation of the results. This new view is built upon combining phases recognized in the disciplines of operations research and numerical solution methods for partial differential equations. The characteristics and activities of each of these phases is discussed in general, but examples are given for the fields of computational fluid dynamics and heat transfer. They argue that a clear distinction should be made between uncertainty and error that can arise in each of these phases. The present definitions for uncertainty and error are inadequate and. therefore, they propose comprehensive definitions for these terms. Specific classes of uncertainty and error sources are then defined that can occur in each phase of modeling and simulation. The numerical sources of error considered apply regardless of whether the discretization procedure is based on finite elements, finite volumes, or finite differences. To better explain the broad types of sources of uncertainty and error, and the utility of their categorization, they discuss a coupled-physics example simulation.

Download or read book Computational Fluid Dynamics written by Herbert Bishop Keller and published by American Mathematical Soc.. This book was released on 1978 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: