Computational Aerodynamic Modeling of Aerospace Vehicles

Currently, the use of computational fluid dynamics (CFD) solutions is considered as the state-of-the-art in the modeling of unsteady nonlinear flow physics and offers an early and improved understanding of air vehicle aerodynamics and stability and control characteristics. This Special Issue covers...

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Bibliographic Details
Main Author: Jenkins, Karl (auth)
Other Authors: Ghoreyshi, Mehdi (auth)
Format: Electronic Book Chapter
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2019
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245 1 0 |a Computational Aerodynamic Modeling of Aerospace Vehicles 
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520 |a Currently, the use of computational fluid dynamics (CFD) solutions is considered as the state-of-the-art in the modeling of unsteady nonlinear flow physics and offers an early and improved understanding of air vehicle aerodynamics and stability and control characteristics. This Special Issue covers recent computational efforts on simulation of aerospace vehicles including fighter aircraft, rotorcraft, propeller driven vehicles, unmanned vehicle, projectiles, and air drop configurations. The complex flow physics of these configurations pose significant challenges in CFD modeling. Some of these challenges include prediction of vortical flows and shock waves, rapid maneuvering aircraft with fast moving control surfaces, and interactions between propellers and wing, fluid and structure, boundary layer and shock waves. Additional topic of interest in this Special Issue is the use of CFD tools in aircraft design and flight mechanics. The problem with these applications is the computational cost involved, particularly if this is viewed as a brute-force calculation of vehicle's aerodynamics through its flight envelope. To make progress in routinely using of CFD in aircraft design, methods based on sampling, model updating and system identification should be considered. 
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650 7 |a History of engineering & technology  |2 bicssc 
653 |a numerical methods 
653 |a modeling 
653 |a aerodynamics 
653 |a Taylor-Green vortex 
653 |a slender-body 
653 |a neural networks 
653 |a shock-channel 
653 |a wind gust responses 
653 |a installed propeller 
653 |a bifurcation 
653 |a RANS 
653 |a wake 
653 |a multi-directional 
653 |a bluff body 
653 |a MDO 
653 |a variable fidelity 
653 |a computational fluid dynamics (CFD) 
653 |a high angles of attack 
653 |a aeroelasticity 
653 |a computational fluid dynamics 
653 |a wind tunnel 
653 |a Godunov method 
653 |a flow control 
653 |a unsteady aerodynamic characteristics 
653 |a overset grid approach 
653 |a convolution integral 
653 |a MUSCL 
653 |a DDES 
653 |a dynamic Smagorinsky subgrid-scale model 
653 |a CPACS 
653 |a flutter 
653 |a reduced-order model 
653 |a meshing 
653 |a vortex generators 
653 |a hybrid reduced-order model 
653 |a microfluidics 
653 |a Riemann solver 
653 |a characteristics-based scheme 
653 |a CFD 
653 |a wing-propeller aerodynamic interaction 
653 |a kinetic energy dissipation 
653 |a Euler 
653 |a formation 
653 |a square cylinder 
653 |a multi-fidelity 
653 |a turbulence model 
653 |a subsonic 
653 |a large eddy simulation 
653 |a after-body 
653 |a flow distortion 
653 |a VLM 
653 |a numerical dissipation 
653 |a hypersonic 
653 |a modified equation analysis 
653 |a fluid mechanics 
653 |a reduced order aerodynamic model 
653 |a p-factor 
653 |a URANS 
653 |a flexible wings 
653 |a chemistry 
653 |a detection 
653 |a microelectromechanical systems (MEMS) 
653 |a angle of attack 
653 |a sharp-edge gust 
653 |a truncation error 
653 |a aerodynamic performance 
653 |a quasi-analytical 
653 |a gasdynamics 
653 |a discontinuous Galerkin finite element method (DG-FEM) 
653 |a geometry 
653 |a S-duct diffuser 
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