Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 11, 17 November 2023


Open Access | Article

Airfoil design with computational fluid dynamics

Henry Bao * 1
1 Walter Payton College Prep High School

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 11, 8-18
Published 17 November 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Henry Bao. Airfoil design with computational fluid dynamics. TNS (2023) Vol. 11: 8-18. DOI: 10.54254/2753-8818/11/20230368.

Abstract

In many industries, there is a need to model the flow of air over structural components. With sufficient information from these models, engineers can better implement these parts into a complete design. The purpose of this paper is to provide a model of specific airfoils using computational fluid dynamics (CFD). With computational fluid dynamics, the characteristics of air around an airfoil can be modeled, providing useful data to engineers who could be designing an airfoil or airplane. The CFD calculations are performed using Python, along with the two packages Numpy and Matplotlib. The governing equations of CFD, including Newton's Second Law, small disturbance equation (SDE), wave propagation, etc. are discretized and transformed into partial differentiation equations (PDE). Using the second order derivative of the wave propagation PDE, the SDE can be solved in iterations and plotted on a graph showing the velocity distributions for a particular airfoil. The results from the CFD calculations show general trends in velocity distributions, regardless of airfoil shape. These include a decrease in x-direction velocity at the ends of an airfoil with an increase at the midsection of the airfoil. Also, y-direction velocity is generally positive and increasing at the front of the airfoil, but negative and decreasing at the end of the airfoil. What is important to understand is how different airfoil shapes can change velocity distributions, moving to using 3D CFD calculations, and the possibility of using CFD for modeling airflow over a multitude of objects.[ Henry Bao, the first author, participated in the Illinois junior academy of science state fair, and abstracts of the regional winners' presentations were posted online. (ilacadofsci.com)]

Keywords

CFD, Fast Design Of Airfoils, Python.

References

1. Hoffmann, K. A., & Chiang, S. T. (2000). Computational fluid dynamics volume I. Engineering education system.

2. Kuzmin, D. (2004). Introduction to computational fluid dynamics. University of Dortmund, Dortmund.

3. Hess, J. L. (1990). Panel methods in computational fluid dynamics. Annual Review of Fluid Mechanics, 22(1), 255-274.

4. Roache, P. J. (1997). Quantification of uncertainty in computational fluid dynamics. Annual Review of Fluid Mechanics, 29(1), 123-160.

5. Versteeg, H. K., & Malalasekera, W. (1995). Computational fluid dynamics. The Finite Volume Method, 1-26.

6. Lin, C. L., Tawhai, M. H., Mclennan, G., & Hoffman, E. A. (2009). Computational fluid dynamics. IEEE Engineering in Medicine and Biology Magazine, 28(3), 25-33.

7. Ochieng, A., Onyango, M., & Kiriamiti, K. (2009). Experimental measurement and computational fluid dynamics simulation of mixing in a stirred tank: a review. South African Journal of Science, 105(11), 421-426.

8. Wexler, D., Segal, R., & Kimbell, J. (2005). Aerodynamic effects of inferior turbinate reduction: computational fluid dynamics simulation. Archives of Otolaryngology–Head & Neck Surgery, 131(12), 1102-1107.

9. Kaya, M. N., Kok, A. R., & Kurt, H. (2021). Comparison of aerodynamic performances of various airfoils from different airfoil families using CFD. Wind and Structures, 32(3), 239-248.

10. Koziel, S., & Leifsson, L. (2013). Multi-level CFD-based airfoil shape optimization with automated low-fidelity model selection. Procedia Computer Science, 18, 889-898.

11. Langtry, R., Gola, J., & Menter, F. (2006, January). Predicting 2D airfoil and 3D wind turbine rotor performance using a transition model for general CFD codes. In 44th AIAA aerospace sciences meeting and exhibit (p. 395).

12. Klausmeyer, S. M., & Lin, J. C. (1997). Comparative results from a CFD challenge over a 2D three-element high-lift airfoil (No. NAS 1.15: 112858). National Aeronautics and Space Administration, Langley Research Center.

13. McLaren, K., Tullis, S., & Ziada, S. (2012). Computational fluid dynamics simulation of the aerodynamics of a high solidity, small‐scale vertical axis wind turbine. Wind Energy, 15(3), 349-361.

14. Piperas, A. T. (2010). Investigation of boundary layer suction on a wind turbine airfoil using CFD. Technical University of Denmark.

15. Wolfe, W. P., & Ochs, S. S. (1997). Predicting aerodynamic characteristic of typical wind turbine airfoils using CFD (No. SAND-96-2345). Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 2023 International Conference on Mathematical Physics and Computational Simulation
ISBN (Print)
978-1-83558-133-9
ISBN (Online)
978-1-83558-134-6
Published Date
17 November 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/11/20230368
Copyright
17 November 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated