The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Kun Xu - One of the best experts on this subject based on the ideXlab platform.
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Computational Fluid Dynamics Based on the Unified Coordinates
2020Co-Authors: Kun XuAbstract:"Computational Fluid Dynamics Based on the Unified Coordinates" reviews the relative advantages and drawbacks of Eulerian and Lagrangian coordinates as well as the Arbitrary Lagrangian-Eulerian (ALE) and various moving mesh methods in Computational Fluid Dynamics (CFD) for one- and multi-dimensional flows. It then systematically introduces the unified coordinate approach to CFD, illustrated with numerous examples and comparisons to clarify its relation with existing approaches. The book is intended for researchers, graduate students and practitioners in the field of Computational Fluid Dynamics. © Science Press Beijing and Springer-Verlag Berlin Heidelberg 2012. All rights are reserved
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Computational Fluid Dynamics Based on the Unified Coordinates
2012Co-Authors: Wai How Hui, Kun XuAbstract:"Computational Fluid Dynamics Based on the Unified Coordinates" reviews the relative advantages and drawbacks of Eulerian and Lagrangian coordinates as well as the Arbitrary Lagrangian-Eulerian (ALE) and various moving mesh methods in Computational Fluid Dynamics (CFD) for one- and multi-dimensional flows. It then systematically introduces the unified coordinate approach to CFD, illustrated with numerous examples and comparisons to clarify its relation with existing approaches. The book is intended for researchers, graduate students and practitioners in the field of Computational Fluid Dynamics. Emeritus Professor Wai-Hou Hui and Professor Kun Xu both work at the Department of Mathematics of the Hong Kong University of Science & Technology, Hong Kong, China.
Patrick J. Roache - One of the best experts on this subject based on the ideXlab platform.
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QUANTIFICATION OF UNCERTAINTY IN Computational Fluid Dynamics
Annual Review of Fluid Mechanics, 1997Co-Authors: Patrick J. RoacheAbstract:This review coversVerification,Validation, Confirmation and related subjects for Computational Fluid Dynamics (CFD), including error taxonomies, error estima- tion and banding, convergence rates, surrogate estimators, nonlinear Dynamics, and error estimation for grid adaptation vs Quantification of Uncertainty.
Julia S Kimbell - One of the best experts on this subject based on the ideXlab platform.
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aerodynamic effects of inferior turbinate reduction Computational Fluid Dynamics simulation
Archives of Otolaryngology-head & Neck Surgery, 2005Co-Authors: David Wexler, Rebecca Segal, Julia S KimbellAbstract:Objective To investigate the aerodynamic consequences of conservative unilateral inferior turbinate reduction using Computational Fluid Dynamics methods to accomplish detailed nasal airflow simulations. Design A high-resolution, finite-element mesh of the nasal airway was constructed from magnetic resonance imaging data of a healthy man. Steady-state, inspiratory airflow simulations were conducted at 15 L/min using the techniques of Computational Fluid Dynamics Intervention Circumferential removal of 2 mm of soft tissue bulk along the length of the left inferior turbinate was modeled. Main Outcome Measures Nasal airflow distribution and pressure profiles were computed before and after simulated left inferior turbinate reduction. Results Simulated inferior turbinate reduction resulted in a broad reduction of pressure along the nasal airway, including the regions distant from the inferior turbinate vicinity. In contrast, relative airflow changes were regional: airflow was minimally affected in the valve region, increased in the lower portion of the middle and posterior nose, and decreased dorsally. Conclusion Use of Computational Fluid Dynamics methods should help elucidate the aerodynamic significance of specific surgical interventions and refine surgical approaches to the nasal airway.
Wai How Hui - One of the best experts on this subject based on the ideXlab platform.
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Computational Fluid Dynamics Based on the Unified Coordinates
2012Co-Authors: Wai How Hui, Kun XuAbstract:"Computational Fluid Dynamics Based on the Unified Coordinates" reviews the relative advantages and drawbacks of Eulerian and Lagrangian coordinates as well as the Arbitrary Lagrangian-Eulerian (ALE) and various moving mesh methods in Computational Fluid Dynamics (CFD) for one- and multi-dimensional flows. It then systematically introduces the unified coordinate approach to CFD, illustrated with numerous examples and comparisons to clarify its relation with existing approaches. The book is intended for researchers, graduate students and practitioners in the field of Computational Fluid Dynamics. Emeritus Professor Wai-Hou Hui and Professor Kun Xu both work at the Department of Mathematics of the Hong Kong University of Science & Technology, Hong Kong, China.
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Role of coordinates in Computational Fluid Dynamics
International Journal of Computational Fluid Dynamics, 2008Co-Authors: Wai How Hui, J. J. Hu, Keh-ming ShyueAbstract:Computational Fluid Dynamics uses large scale numerical computation to solve problems of Fluid flow. It turns out that the numerical solution for a given flow depends on the coordinates (grid) used to compute the flow. The commonly used Eulerian and Lagrangian coordinate systems both have advantages and drawbacks. In this paper, we first discuss the role of coordinates in Computational Fluid Dynamics regarding the questions of: (a) conservation form partial differential equations; (b) numerical resolution of contact discontinuities; (c) grid generation; and (d) grid orthogonality. We then introduce a unified coordinate system which combines the advantages of both Eulerian and Lagrangian system and beyond, while avoiding their drawbacks. Examples include a transonic flow past an airfoil and a two-Fluids flow with shocks.
T. Tang - One of the best experts on this subject based on the ideXlab platform.
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Moving mesh methods for Computational Fluid Dynamics
Contemporary Mathematics, 2005Co-Authors: T. TangAbstract:In this paper we will discuss a class of adaptive grid methods called moving mesh method (MMM). Some recent progress of the moving mesh methods will be reviewed. In particular, we review their applications to Computational Fluid Dynamics.