The contribution to aircraft design of research in fluid dynamics

2005 ◽  
pp. 106-148
Author(s):  
J. E. Green
Keyword(s):  
Fluid Dynamics ◽  
Aircraft Design

The application of computational fluid dynamics to aircraft design

1986 ◽  
Author(s):  
R. BUSCH, JR. ◽  
M. JAGER ◽  
B. BERGMAN
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Aircraft Design

scholarly journals High-order computational fluid dynamics tools for aircraft design

2014 ◽  
Vol 372 (2022) ◽  
pp. 20130318 ◽  
Author(s):  
Z. J. Wang
Keyword(s):  
Fluid Dynamics ◽  
Growth Rate ◽  
Computational Fluid Dynamics ◽  
Fuel Economy ◽  
Aircraft Design ◽  
Aircraft Engine ◽  
Foreseeable Future ◽  
Complex Flows ◽  
Environmental Goals ◽  
Set Up

Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items.

Rapid gust response simulation of large civil aircraft using computational fluid dynamics

2017 ◽  
Vol 121 (1246) ◽  
pp. 1795-1807 ◽  
Author(s):  
P. Bekemeyer ◽  
R. Thormann ◽  
S. Timme
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Stokes Equations ◽  
Lift Coefficient ◽  
Computational Cost ◽  
Aircraft Design ◽  
Navier Stokes ◽  
Surface Pressure Distribution ◽  
Wide Range ◽  
Civil Aircraft

ABSTRACTSeveral critical load cases during the aircraft design process result from atmospheric turbulence. Thus, rapidly performable and highly accurate dynamic response simulations are required to analyse a wide range of parameters. A method is proposed to predict dynamic loads on an elastically trimmed, large civil aircraft using computational fluid dynamics in conjunction with model reduction. A small-sized modal basis is computed by sampling the aerodynamic response at discrete frequencies and applying proper orthogonal decomposition. The linear operator of the Reynolds-averaged Navier-Stokes equations plus turbulence model is then projected onto the subspace spanned by this basis. The resulting reduced system is solved at an arbitrary number of frequencies to analyse responses to 1-cos gusts very efficiently. Lift coefficient and surface pressure distribution are compared with full-order, non-linear, unsteady time-marching simulations to verify the method. Overall, the reduced-order model predicts highly accurate global coefficients and surface loads at a fraction of the computational cost, which is an important step towards the aircraft loads process relying on computational fluid dynamics.

scholarly journals Fast identification of transonic buffet envelope using computational fluid dynamics

2019 ◽  
Vol 91 (2) ◽  
pp. 309-316 ◽  
Author(s):  
Jernej Drofelnik ◽  
Andrea Da Ronch ◽  
Matteo Franciolini ◽  
Andrea Crivellini
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Turbulent Flow ◽  
Stokes Equations ◽  
Aircraft Design ◽  
Navier Stokes ◽  
Swept Wing ◽  
Navier Stokes Equations ◽  
Content Type ◽  
Preliminary Aircraft Design

Purpose This paper aims to present a numerical method based on computational fluid dynamics that allows investigating the buffet envelope of reference equivalent wings at the equivalent cost of several two-dimensional, unsteady, turbulent flow analyses. The method bridges the gap between semi-empirical relations, generally dominant in the early phases of aircraft design, and three-dimensional turbulent flow analyses, characterised by high costs in analysis setups and prohibitive computing times. Design/methodology/approach Accuracy in the predictions and efficiency in the solution are two key aspects. Accuracy is maintained by solving a specialised form of the Reynolds-averaged Navier–Stokes equations valid for infinite-swept wing flows. Efficiency of the solution is reached by a novel implementation of the flow solver, as well as by combining solutions of different fidelity spatially. Findings Discovering the buffet envelope of a set of reference equivalent wings is accompanied with an estimate of the uncertainties in the numerical predictions. Just over 2,000 processor hours are needed if it is admissible to deal with an uncertainty of ±1.0° in the angle of attack at which buffet onset/offset occurs. Halving the uncertainty requires significantly more computing resources, close to a factor 200 compared with the larger uncertainty case. Practical implications To permit the use of the proposed method as a practical design tool in the conceptual/preliminary aircraft design phases, the method offers the designer with the ability to gauge the sensitivity of buffet on primary design variables, such as wing sweep angle and chord to thickness ratio. Originality/value The infinite-swept wing, unsteady Reynolds-averaged Navier–Stokes equations have been successfully applied, for the first time, to identify buffeting conditions. This demonstrates the adequateness of the proposed method in the conceptual/preliminary aircraft design phases.

Efficient reduced-order modeling of unsteady aerodynamics under light dynamic stall conditions

2018 ◽  
Vol 233 (6) ◽  
pp. 2141-2151
Author(s):  
Li Xiaohua ◽  
Zheng Guo ◽  
Grecov Dana ◽  
Zhongxi Hou
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Unsteady Aerodynamics ◽  
Time History ◽  
Aircraft Design ◽  
Reduced Order Modeling ◽  
Dynamic Stall ◽  
Reduced Order ◽  
Reduced Frequency ◽  
Static Conditions

In this research, a reduced-order modeling is developed to predict the unsteady aerodynamic forces under light dynamic stall conditions at low-speed regimes. The filtered white Gaussian noise is selected as input signals for computational fluid dynamics solver in order to generate training data, containing the information of reduced frequency and amplitude. Because of the time history influences, the reduced-order modeling combines the Kriging function and recurrence framework together in this approach. An airfoil NACA0012 undergoing pitching motions with different reduced frequency, amplitude, and mean angle of attack is designed to illustrate the methodology. The developed model can predict the lift, drag, and moment coefficients in seconds on a single-core computer processor. To reduce the prediction errors between reduced-order modeling predictions and computational fluid dynamics simulations, the aerodynamic loads in static conditions are applied as initial inputs. The predictions via the proposed approach are in agreement with the results using a high precision computational fluid dynamics solver over the designed ranges of amplitude and reduced frequency, which is suitable for engineering applications, such as fluid-structure interaction, and aircraft design optimizations.

Generalized Riemann Problems in Computational Fluid Dynamics

2003 ◽  
Author(s):  
Matania Ben-Artzi ◽  
Joseph Falcovitz
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Riemann Problems ◽  
Generalized Riemann Problems

Computational Fluid Dynamics

2002 ◽  
Author(s):  
T. J. Chung
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics

Partial Differential Equations in Fluid Dynamics

2008 ◽  
Author(s):  
Isom H. Herron ◽  
Michael R. Foster
Keyword(s):  
Fluid Dynamics ◽  
Partial Differential Equations ◽  
Differential Equations ◽  
Partial Differential

An Introduction to Fluid Dynamics

2000 ◽  
Author(s):  
G. K. Batchelor
Keyword(s):  
Fluid Dynamics
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