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Havacılık uygulamaları için açık kaynaklı parametrik bir aerodinamik şekil optimizasyon çerçevesinin geliştirilmesi

Yıl 2025, , 381 - 400, 16.08.2024
https://doi.org/10.17341/gazimmfd.1334282

Öz

Sürekli büyüyen havacılık sektöründe uçuş sayısının artması nedeniyle uçakların karbon ayak izi de artış göstermektedir. Uçakların aerodinamik performansının iyileştirilmesi kritik bir gereklilik haline gelmiştir. Bu nedenle, uçak bileşenlerinin tasarımında aerodinamik şekil optimizasyonu (ASO) büyük önem taşımaktadır. Bu çalışmada, transonik rejimde N2A-EXTE hava aracının geometrisi optimize etmek için açık kaynaklı araçlar kullanılarak hesaplamalı akışkanlar dinamiği (HAD) tabanlı parametrik bir ASO çerçevesi tasarlanmıştır. Sunulan ASO çerçevesi kullanılarak elde edilen sonuçlar, N2A-EXTE hava aracı için maksimum olarak %10’luk göreceli iyileştirme yaptığını göstermiştir. Optimize edilmiş aerodinamik yüzeylerin üzerindeki basınç dağılımı ve süpersonik bölgelerin başlangıç geometrisi ile kıyaslanması sonucunda yapılan göreceli iyileştirmenin nedenleri ortaya konmuştur. Ayrıca N2A-EXTE hava aracı için oluşturulan yeni tasarımlar için hacim, yüzey alanı ve boylamsal statik kararlılık karakteristiği açısından orijinal hava aracı geometrisi ile kıyaslanmıştır. Gerçek bir hava aracı üzerinde yapılan optimizasyon çalışmaları mevcut çalışmada önerilen ASO çerçevesinin yeterince kararlı olduğunu ve iyi çalıştığını ortaya koymuştur. Bu çalışmada tasarlanan ASO çerçevesinde yer alan açık kaynak yazılımlar başka tasarım araçları ile yer değiştirilebilir olup farklı havacılık uygulamalarında ve hava araçlarının ön tasarım aşamalarında kolaylıkla kullanılabilmektedir. Mevcut çalışmada sunulan ASO çerçevesi gelecekte yapılacak çok disiplinli ASO çalışmasının ilk adımı olarak düşünülebilir.

Kaynakça

  • 1. Liebeck R. H., Design of the blended wing body subsonic transport, Journal of Aircraft, 41 (1), 10-25, 2004.
  • 2. İnternet: Hicks, R. M., Murman, E. M., Vanderplaats, G. N. An assessment of airfoil design by numerical optimization. Technical Report NASA TM X-3092. https://ntrs.nasa.gov/citations/19740020369. Yayın tarihi Temmuz 1, 1974, Erişim Tarihi: Haziran 15, 2023.
  • 3. Hicks R. M., Henne P. A., Wing design by numerical optimization, Journal of Aircraft, 15 (7), 407-412, 1978.
  • 4. Jameson A., Aerodynamic design via control theory, Journal of Scientific Computing, 3, 233-260, 1988.
  • 5. Drela M., Pros and Cons of Airfoil Optimization, Frontiers of computational fluid dynamics, Editör: D. A. Caughey and M. M. Hafez, World scientific, Singapore, 363–381, 1998.
  • 6. Hicken J. E., Zingg D. W., Aerodynamic optimization algorithm with integrated geometry parameterization and mesh movement, The American Institute of Aeronautics and Astronautics Journal, 48 (2), 400-413, 2010.
  • 7. Hicken J. E., Zingg D. W., Induced-drag minimization of nonplanar geometries based on the Euler equations, the American Institute of Aeronautics and Astronautics Journal, 48 (11), 2564-2575, 2010.
  • 8. Gagnon H., Zingg D., Two-level free-form deformation for high-fidelity aerodynamic shape optimization, 12th the American Institute of Aeronautics and Astronautics Aviation Technology, Integration, and Operations Conference and 14th The American Institute of Aeronautics and Astronautics / The International Society for Structural and Multidisciplinary Optimization Multidisciplinary Analysis and Optimization Conference, Indiana-USA, 5447, 177-19 September, 2012.
  • 9. Nadarajah S.K., Tatossian C., Multi-objective aerodynamic shape optimization for unsteady viscous flows, Optimization and Engineering, 11 (1),67-106, 2010.
  • 10. Mader C. A., Martins J. R., Alonso J. J., Van Der Weide E., ADjoint: An approach for the rapid development of discrete adjoint solvers, The American Institute of Aeronautics and Astronautics Journal, 46 (4), 863-873, 2008.
  • 11. Lyu Z., Kenway G. K., Paige C., Martins J. R., Automatic differentiation adjoint of the Reynolds-averaged Navier-Stokes equations with a turbulence model, 21st The American Institute of Aeronautics and Astronautics Computational Fluid Dynamics Conference, California-USA, 2581, 24-27 June, 2013.
  • 12. Hascoët L., TAPENADE: A tool for automatic differentiation of programs, Proceedings of 4th European Congress on Computational Methods, Jyvaskyla-Finland, 1-14, 24-28 July, 2004.
  • 13. Lyu Z., Kenway G. K., Martins J. R., Aerodynamic shape optimization investigations of the common research model wing benchmark, The American Institute of Aeronautics and Astronautics Journal, 53 (4), 968-985, 2015.
  • 14. Mader C. A., Martins J. R., Stability-constrained aerodynamic shape optimization of flying wings, Journal of Aircraft, 50 (5), 1431-1449, 2013.
  • 15. Ning S. A., Kroo I., Multidisciplinary considerations in the design of wings and wing tip devices, Journal of Aircraft, 47 (2), 534-543, 2010.
  • 16. Bons N., Mader C. A., Martins J. R., Cuco, A., Odaguil, F., High-fidelity aerodynamic shape optimization of a full configuration regional jet, 2018 The American Institute of Aeronautics and Astronautics / The American Society of Civil Engineers / American Headache Sociey / American Society for Composites Structures, Structural Dynamics, and Materials Conference, Florida-USA, 106, 8–12 January, 2018.
  • 17. Göv İ., Doğru M. H., Korkmaz Ü., Improvement of the aerodynamic performance of NACA 4412 using the adjustable airfoil profile during the flight, Journal of the Faculty of Engineering and Architecture of Gazi University, 34 (2), 1109-1125, 2019.
  • 18. Çanlıoğlu İ. E., Kara E., Computational fluid dynamics study of lift enhancement on a NACA0012 airfoil using a synthetic jet actuator, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (3), 1821-1838, 2023.
  • 19. Yılmaz İ., Keiyinci S., Çam, Ö., Karcı, A., Experimental investigation of aerodynamic parameters on flapping wing, Journal of the Faculty of Engineering and Architecture of Gazi University, 32 (4), 1035-1050, 2017.
  • 20. Lyu Z., Martins J. R., Aerodynamic design optimization studies of a blended-wing-body aircraft, Journal of Aircraft, 51 (5), 1604-1617, 2014.
  • 21. Liou M. F., Kim H., Lee B., Liou M. S., Aerodynamic design of integrated propulsion–airframe configuration of a hybrid wing body aircraft, Shock Waves, 29 (8), 1043-1064, 2019.
  • 22. Zingg D. W., Nemec M., Pulliam T. H., A comparative evaluation of genetic and gradient-based algorithms applied to aerodynamic optimization, European Journal of Computational Mechanics/Revue Européenne de Mécanique Numérique, 17 (1-2), 103-126, 2008.
  • 23. Obayashi S., Oyama A., Nakamura T., Transonic wing shape optimization based on evolutionary algorithms, Editör: M. Valero, K. Joe, M. Kitsuregawa, and H. Tanaka, ISHPC 2000, Cilt: 1940, Berlin-Germany, Heidelberg: Springer, 178-181, 2000.
  • 24. Sasaki D., Obayashi S., Efficient search for trade-offs by adaptive range multi-objective genetic algorithms, Journal of Aerospace Computing, Information, and Communication, 2 (1), 44-64, 2005.
  • 25. Sasaki D., Morikawa M., Obayashi S., Nakahashi K., Aerodynamic shape optimization of supersonic wings by adaptive range multiobjective genetic algorithms, Evolutionary Multi-Criterion Optimization: First International Conference, Zurich-Switzerland, 639-652, 7-9 March, 2001.
  • 26. Hashimoto A., Jeong S., Obayashi S., Aerodynamic optimization of near-future high-wing aircraft, Transactions of the Japan Society for Aeronautical and Space Sciences, 58 (2), 73-82, 2015.
  • 27. Chiba K., Oyama A., Obayashi S., Nakahashi K., Morino H., Multidisciplinary design optimization and data mining for transonic regional-jet wing, Journal of Aircraft, 44 (4), 1100-1112, 2007.
  • 28. Peigin S., Epstein B., Computational fluid dynamics driven optimization of blended wing body aircraft, American Institute of Aeronautics and Astronautics Journal, 44 (11), 2736-2745, 2006.
  • 29. Li P., Zhang B., Chen Y., Yuan C., Lin Y., Aerodynamic design methodology for blended wing body transport, Chinese Journal of Aeronautics, 25 (4), 508-516, 2012.
  • 30. Giunta A., Wojtkiewicz S., Eldred M., Overview of modern design of experiments methods for computational simulations, 41st Aerospace Sciences Meeting and Exhibit, Nevada-USA, 649, 6-9 January, 2003.
  • 31. Ahn J., Yee K., Lee D. H., Two-point design optimization of transonic airfoil using response surface methodology, 37th Aerospace Sciences Meeting and Exhibit, Nevada-USA, 403, 11-14 January, 1999.
  • 32. Campbell R., Smith L., A hybrid algorithm for transonic airfoil and wing design, 5th Applied Aerodynamics Conference, Monterey, California-USA, 2552, 17-19 August, 1987.
  • 33. Yu N., Campbell R., Transonic airfoil and wing design using Navier-Stokes codes, In 10th Applied Aerodynamics Conference, California-USA, 2651, 22-24 June, 1992.
  • 34. Staub F. M., Morita N., Entzinger J. O., Tsuchiya T., Aerodynamic design trade study and optimization of a blended wing body airliner, The American Institute of Aeronautics and Astronautics Aviation 2019 Forum, Texas-USA, 3172, 17-21 June, 2019.
  • 35. McDonald R. A., Gloudemans J. R., Open vehicle sketch pad: An open source parametric geometry and analysis tool for conceptual aircraft design, The American Institute of Aeronautics and Astronautics Science and Technology Forum and Exposition, California-USA, 3-7 January, 2022.
  • 36. Tomac M., Eller D., Towards automated hybrid-prismatic mesh generation, Procedia Engineering, 82, 377-389, 2014.
  • 37. Hang S., TetGen, a delaunay-based quality tetrahedral mesh generator, Association for Computing Machinery Transactions on Mathematical Software, 41 (2), 1-56, 2015.
  • 38. H. G. Weller, G. Tabor, H. Jasak, C. Fureby, A tensorial approach to computational continuum mechanics using object-oriented techniques, Computers in Physics, 12, 620-631, 1998.
  • 39. High Speed Aerodynamic (HiSA) solver. https://hisa.gitlab.io/. Erişim Tarihi: 25.06.2023.
  • 40. Heyns J.A.; Oxtoby O.F.; Steenkamp A., Modelling high-speed viscous flow in OpenFOAM®, In Proceedings of the 9thOpenFOAM Workshop, Zagreb-Croatia, 23–26 June, 2014.
  • 41. Adams B.M., Bohnhoff W.J., Dalbey K.R., Ebeida M.S., Eddy J.P., Eldred M.S., Hooper R.W., Hough P.D., Hu K.T., Jakeman J.D., Khalil M., Maupin K.A., Monschke J.A., Ridgway E.M., Rushdi A.A., Seidl D.T., Stephens J.A., Swiler L.P., and Winokur J.G., Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.15 User’s Manual, Sandia Technical Report SAND2020-12495, November 2021.
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  • 44. Abuhanieh S., Akay H. U., Bicer B., A new strategy for solving store separation problems using OpenFOAM. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 236 (15), 3152-3166, 2022.
  • 45. Liou M. S., A sequel to AUSM, Part II: AUSM+-up for all speeds. Journal of Computational Physics, 214 (1), 137-170, 2006.
  • 46. OpenFOAM User Guide Numerical Schemes. https://www.openfoam.com/documentation/user-guide/6-solving/6.2-numerical-schemes. Erişim Tarihi: 28.06.2023.
  • 47. Fox R.W., Pritchard P.J. and McDonald A.T., Introduction to Fluid Mechanics, Hoboken, NJ: John Wiley & Sons, Inc, 294-440, 2011.
  • 48. Kawai R. T., Acoustic prediction methodology and test validation for an efficient low-noise hybrid wing body subsonic transport, Huntington Beach: Boeing Research and Technology, Report No: NNL07AA54C, California-USA, 68-86, 2011.
  • 49. Kuntawala N. B., Aerodynamic shape optimization of a blended-wing-body aircraft configuration, Master’s Thesis, University of Toronto Masters of Applied Science Graduate Department of Aerospace Engineering, Toronto, 1-33, 2010.
  • 50. Mangano M., Multi-point aerodynamic shape optimization for airfoils and wings at supersonic and subsonic regimes, Master’s Thesis, Delft University of Technology, Delft, 23-54, 2019.
  • 51. Versprille V. F. W., Aerodynamic shape optimization of a liquid-hydrogen-powered blended-wing-body, Master’s Thesis, Delft University of Technology, Delft, 1-9, 2022.
  • 52. Martins J. R., Ning A., Engineering design optimization. Cambridge: Cambridge University Press, 306-316, 2021.
  • 53. OpenFOAM User Guide Forces. https://www.openfoam.com/documentation/guides/latest/doc/guide-fos-forces-forces.html. Erişim Tarihi: 28.12.2023.
  • 54. Anderson J., Fundamentals of aerodynamics, 6th edition, New York: McGraw-Hill Education, 19-32, 2016.
  • 55. Demir G., Görgülüarslan R.M., Çelebioğlu S.A., Design of the ONERA M6 wing by shape optimization under luncertainty, Journal of the Faculty of Engineering and Architecture of Gazi University, 39 (2), 771-784, 2023.
  • 56. Pustina L., Cavallaro R. & Bernardini G., NERONE: An Open-Source Based Tool for Aerodynamic Transonic Optimization of Nonplanar Wings. Aerotec. Missili Spaz. 98, 85–104, 2019.
  • 57. Djeddi R. and Ekici K., Novel expression-template-based automatic differentiation of Fortran codes for aerodynamic optimization, AIAA Journal, 59 (1), 88–103, 2021.
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Development of an open-source parametric aerodynamic shape optimization framework for aerospace applications

Yıl 2025, , 381 - 400, 16.08.2024
https://doi.org/10.17341/gazimmfd.1334282

Öz

In the ever-growing aviation industry, the carbon footprint of airplanes is also increasing due to the increase in the number of flights. Improving the aerodynamic performance of aircraft has become a critical requirement. Therefore, aerodynamic shape optimization (ASO) is of great importance in the design of aircraft components. In this study, a computational fluid dynamics (CFD) based parametric ASO framework is designed using open-source tools to optimize the geometry of N2A-EXTE aircraft in the transonic regime. The results obtained using the presented ASO framework showed a maximum relative improvement of 10% for the N2A-EXTE aircraft. This relative improvement is explained by comparing the pressure distribution over the optimized aerodynamic surfaces and supersonic regions between optimized and the initial geometry. The new designs for the N2A-EXTE aircraft are also compared with the original aircraft geometry in terms of volume, surface area and longitudinal static stability characteristics. Optimization studies on a real aircraft revealed that the proposed ASO framework is sufficiently stable and works well. The open source software in the ASO framework designed in this study are interchangeable with other design tools and can be easily used in different aerospace applications in the preliminary design stages of aircraft. The ASO framework presented in the present study can be considered as the first step of a future multidisciplinary ASO framework.

Kaynakça

  • 1. Liebeck R. H., Design of the blended wing body subsonic transport, Journal of Aircraft, 41 (1), 10-25, 2004.
  • 2. İnternet: Hicks, R. M., Murman, E. M., Vanderplaats, G. N. An assessment of airfoil design by numerical optimization. Technical Report NASA TM X-3092. https://ntrs.nasa.gov/citations/19740020369. Yayın tarihi Temmuz 1, 1974, Erişim Tarihi: Haziran 15, 2023.
  • 3. Hicks R. M., Henne P. A., Wing design by numerical optimization, Journal of Aircraft, 15 (7), 407-412, 1978.
  • 4. Jameson A., Aerodynamic design via control theory, Journal of Scientific Computing, 3, 233-260, 1988.
  • 5. Drela M., Pros and Cons of Airfoil Optimization, Frontiers of computational fluid dynamics, Editör: D. A. Caughey and M. M. Hafez, World scientific, Singapore, 363–381, 1998.
  • 6. Hicken J. E., Zingg D. W., Aerodynamic optimization algorithm with integrated geometry parameterization and mesh movement, The American Institute of Aeronautics and Astronautics Journal, 48 (2), 400-413, 2010.
  • 7. Hicken J. E., Zingg D. W., Induced-drag minimization of nonplanar geometries based on the Euler equations, the American Institute of Aeronautics and Astronautics Journal, 48 (11), 2564-2575, 2010.
  • 8. Gagnon H., Zingg D., Two-level free-form deformation for high-fidelity aerodynamic shape optimization, 12th the American Institute of Aeronautics and Astronautics Aviation Technology, Integration, and Operations Conference and 14th The American Institute of Aeronautics and Astronautics / The International Society for Structural and Multidisciplinary Optimization Multidisciplinary Analysis and Optimization Conference, Indiana-USA, 5447, 177-19 September, 2012.
  • 9. Nadarajah S.K., Tatossian C., Multi-objective aerodynamic shape optimization for unsteady viscous flows, Optimization and Engineering, 11 (1),67-106, 2010.
  • 10. Mader C. A., Martins J. R., Alonso J. J., Van Der Weide E., ADjoint: An approach for the rapid development of discrete adjoint solvers, The American Institute of Aeronautics and Astronautics Journal, 46 (4), 863-873, 2008.
  • 11. Lyu Z., Kenway G. K., Paige C., Martins J. R., Automatic differentiation adjoint of the Reynolds-averaged Navier-Stokes equations with a turbulence model, 21st The American Institute of Aeronautics and Astronautics Computational Fluid Dynamics Conference, California-USA, 2581, 24-27 June, 2013.
  • 12. Hascoët L., TAPENADE: A tool for automatic differentiation of programs, Proceedings of 4th European Congress on Computational Methods, Jyvaskyla-Finland, 1-14, 24-28 July, 2004.
  • 13. Lyu Z., Kenway G. K., Martins J. R., Aerodynamic shape optimization investigations of the common research model wing benchmark, The American Institute of Aeronautics and Astronautics Journal, 53 (4), 968-985, 2015.
  • 14. Mader C. A., Martins J. R., Stability-constrained aerodynamic shape optimization of flying wings, Journal of Aircraft, 50 (5), 1431-1449, 2013.
  • 15. Ning S. A., Kroo I., Multidisciplinary considerations in the design of wings and wing tip devices, Journal of Aircraft, 47 (2), 534-543, 2010.
  • 16. Bons N., Mader C. A., Martins J. R., Cuco, A., Odaguil, F., High-fidelity aerodynamic shape optimization of a full configuration regional jet, 2018 The American Institute of Aeronautics and Astronautics / The American Society of Civil Engineers / American Headache Sociey / American Society for Composites Structures, Structural Dynamics, and Materials Conference, Florida-USA, 106, 8–12 January, 2018.
  • 17. Göv İ., Doğru M. H., Korkmaz Ü., Improvement of the aerodynamic performance of NACA 4412 using the adjustable airfoil profile during the flight, Journal of the Faculty of Engineering and Architecture of Gazi University, 34 (2), 1109-1125, 2019.
  • 18. Çanlıoğlu İ. E., Kara E., Computational fluid dynamics study of lift enhancement on a NACA0012 airfoil using a synthetic jet actuator, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (3), 1821-1838, 2023.
  • 19. Yılmaz İ., Keiyinci S., Çam, Ö., Karcı, A., Experimental investigation of aerodynamic parameters on flapping wing, Journal of the Faculty of Engineering and Architecture of Gazi University, 32 (4), 1035-1050, 2017.
  • 20. Lyu Z., Martins J. R., Aerodynamic design optimization studies of a blended-wing-body aircraft, Journal of Aircraft, 51 (5), 1604-1617, 2014.
  • 21. Liou M. F., Kim H., Lee B., Liou M. S., Aerodynamic design of integrated propulsion–airframe configuration of a hybrid wing body aircraft, Shock Waves, 29 (8), 1043-1064, 2019.
  • 22. Zingg D. W., Nemec M., Pulliam T. H., A comparative evaluation of genetic and gradient-based algorithms applied to aerodynamic optimization, European Journal of Computational Mechanics/Revue Européenne de Mécanique Numérique, 17 (1-2), 103-126, 2008.
  • 23. Obayashi S., Oyama A., Nakamura T., Transonic wing shape optimization based on evolutionary algorithms, Editör: M. Valero, K. Joe, M. Kitsuregawa, and H. Tanaka, ISHPC 2000, Cilt: 1940, Berlin-Germany, Heidelberg: Springer, 178-181, 2000.
  • 24. Sasaki D., Obayashi S., Efficient search for trade-offs by adaptive range multi-objective genetic algorithms, Journal of Aerospace Computing, Information, and Communication, 2 (1), 44-64, 2005.
  • 25. Sasaki D., Morikawa M., Obayashi S., Nakahashi K., Aerodynamic shape optimization of supersonic wings by adaptive range multiobjective genetic algorithms, Evolutionary Multi-Criterion Optimization: First International Conference, Zurich-Switzerland, 639-652, 7-9 March, 2001.
  • 26. Hashimoto A., Jeong S., Obayashi S., Aerodynamic optimization of near-future high-wing aircraft, Transactions of the Japan Society for Aeronautical and Space Sciences, 58 (2), 73-82, 2015.
  • 27. Chiba K., Oyama A., Obayashi S., Nakahashi K., Morino H., Multidisciplinary design optimization and data mining for transonic regional-jet wing, Journal of Aircraft, 44 (4), 1100-1112, 2007.
  • 28. Peigin S., Epstein B., Computational fluid dynamics driven optimization of blended wing body aircraft, American Institute of Aeronautics and Astronautics Journal, 44 (11), 2736-2745, 2006.
  • 29. Li P., Zhang B., Chen Y., Yuan C., Lin Y., Aerodynamic design methodology for blended wing body transport, Chinese Journal of Aeronautics, 25 (4), 508-516, 2012.
  • 30. Giunta A., Wojtkiewicz S., Eldred M., Overview of modern design of experiments methods for computational simulations, 41st Aerospace Sciences Meeting and Exhibit, Nevada-USA, 649, 6-9 January, 2003.
  • 31. Ahn J., Yee K., Lee D. H., Two-point design optimization of transonic airfoil using response surface methodology, 37th Aerospace Sciences Meeting and Exhibit, Nevada-USA, 403, 11-14 January, 1999.
  • 32. Campbell R., Smith L., A hybrid algorithm for transonic airfoil and wing design, 5th Applied Aerodynamics Conference, Monterey, California-USA, 2552, 17-19 August, 1987.
  • 33. Yu N., Campbell R., Transonic airfoil and wing design using Navier-Stokes codes, In 10th Applied Aerodynamics Conference, California-USA, 2651, 22-24 June, 1992.
  • 34. Staub F. M., Morita N., Entzinger J. O., Tsuchiya T., Aerodynamic design trade study and optimization of a blended wing body airliner, The American Institute of Aeronautics and Astronautics Aviation 2019 Forum, Texas-USA, 3172, 17-21 June, 2019.
  • 35. McDonald R. A., Gloudemans J. R., Open vehicle sketch pad: An open source parametric geometry and analysis tool for conceptual aircraft design, The American Institute of Aeronautics and Astronautics Science and Technology Forum and Exposition, California-USA, 3-7 January, 2022.
  • 36. Tomac M., Eller D., Towards automated hybrid-prismatic mesh generation, Procedia Engineering, 82, 377-389, 2014.
  • 37. Hang S., TetGen, a delaunay-based quality tetrahedral mesh generator, Association for Computing Machinery Transactions on Mathematical Software, 41 (2), 1-56, 2015.
  • 38. H. G. Weller, G. Tabor, H. Jasak, C. Fureby, A tensorial approach to computational continuum mechanics using object-oriented techniques, Computers in Physics, 12, 620-631, 1998.
  • 39. High Speed Aerodynamic (HiSA) solver. https://hisa.gitlab.io/. Erişim Tarihi: 25.06.2023.
  • 40. Heyns J.A.; Oxtoby O.F.; Steenkamp A., Modelling high-speed viscous flow in OpenFOAM®, In Proceedings of the 9thOpenFOAM Workshop, Zagreb-Croatia, 23–26 June, 2014.
  • 41. Adams B.M., Bohnhoff W.J., Dalbey K.R., Ebeida M.S., Eddy J.P., Eldred M.S., Hooper R.W., Hough P.D., Hu K.T., Jakeman J.D., Khalil M., Maupin K.A., Monschke J.A., Ridgway E.M., Rushdi A.A., Seidl D.T., Stephens J.A., Swiler L.P., and Winokur J.G., Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.15 User’s Manual, Sandia Technical Report SAND2020-12495, November 2021.
  • 42. Yiğit Ş., Abuhanieh S., Biçer B., An open-source aerodynamic shape optimization application for an unmanned aerial vehicle (UAV) propeller: an open-source aerodynamic shape optimization application, Journal of Aeronautics and Space Technologies, 15 (2), 1–12, 2022.
  • 43. Blazek J., Computational fluid dynamics: Principles and applications, 3rd edition, Amsterdam: Butterworth-Heinemann, 5-25, 2015.
  • 44. Abuhanieh S., Akay H. U., Bicer B., A new strategy for solving store separation problems using OpenFOAM. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 236 (15), 3152-3166, 2022.
  • 45. Liou M. S., A sequel to AUSM, Part II: AUSM+-up for all speeds. Journal of Computational Physics, 214 (1), 137-170, 2006.
  • 46. OpenFOAM User Guide Numerical Schemes. https://www.openfoam.com/documentation/user-guide/6-solving/6.2-numerical-schemes. Erişim Tarihi: 28.06.2023.
  • 47. Fox R.W., Pritchard P.J. and McDonald A.T., Introduction to Fluid Mechanics, Hoboken, NJ: John Wiley & Sons, Inc, 294-440, 2011.
  • 48. Kawai R. T., Acoustic prediction methodology and test validation for an efficient low-noise hybrid wing body subsonic transport, Huntington Beach: Boeing Research and Technology, Report No: NNL07AA54C, California-USA, 68-86, 2011.
  • 49. Kuntawala N. B., Aerodynamic shape optimization of a blended-wing-body aircraft configuration, Master’s Thesis, University of Toronto Masters of Applied Science Graduate Department of Aerospace Engineering, Toronto, 1-33, 2010.
  • 50. Mangano M., Multi-point aerodynamic shape optimization for airfoils and wings at supersonic and subsonic regimes, Master’s Thesis, Delft University of Technology, Delft, 23-54, 2019.
  • 51. Versprille V. F. W., Aerodynamic shape optimization of a liquid-hydrogen-powered blended-wing-body, Master’s Thesis, Delft University of Technology, Delft, 1-9, 2022.
  • 52. Martins J. R., Ning A., Engineering design optimization. Cambridge: Cambridge University Press, 306-316, 2021.
  • 53. OpenFOAM User Guide Forces. https://www.openfoam.com/documentation/guides/latest/doc/guide-fos-forces-forces.html. Erişim Tarihi: 28.12.2023.
  • 54. Anderson J., Fundamentals of aerodynamics, 6th edition, New York: McGraw-Hill Education, 19-32, 2016.
  • 55. Demir G., Görgülüarslan R.M., Çelebioğlu S.A., Design of the ONERA M6 wing by shape optimization under luncertainty, Journal of the Faculty of Engineering and Architecture of Gazi University, 39 (2), 771-784, 2023.
  • 56. Pustina L., Cavallaro R. & Bernardini G., NERONE: An Open-Source Based Tool for Aerodynamic Transonic Optimization of Nonplanar Wings. Aerotec. Missili Spaz. 98, 85–104, 2019.
  • 57. Djeddi R. and Ekici K., Novel expression-template-based automatic differentiation of Fortran codes for aerodynamic optimization, AIAA Journal, 59 (1), 88–103, 2021.
  • 58. Zhang X., Jesudasan R. and Müller J.-D., Adjoint-based aerodynamic optimisation of wing shape using non-uniform rational B-splines, Computational Methods in Applied Sciences, 143–158. 2018.
  • 59. Dam B., Pirasaci T. and Kaya M., Artificial neural network based wing planform aerodynamic optimization, Aircraft Engineering and Aerospace Technology, 94 (10), 1731-1747, 2022.
Toplam 59 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Makine Mühendisliğinde Optimizasyon Teknikleri, Makine Mühendisliğinde Sayısal Yöntemler
Bölüm Makaleler
Yazarlar

Buğra Batan 0000-0003-1248-9061

Saleh Abuhanieh Bu kişi benim 0000-0002-3620-8546

Tamer Çalışıır 0000-0002-0721-0444

Şahin Yiğit Bu kişi benim 0000-0001-8396-1867

Erken Görünüm Tarihi 1 Temmuz 2024
Yayımlanma Tarihi 16 Ağustos 2024
Gönderilme Tarihi 1 Ağustos 2023
Kabul Tarihi 6 Nisan 2024
Yayımlandığı Sayı Yıl 2025

Kaynak Göster

APA Batan, B., Abuhanieh, S., Çalışıır, T., Yiğit, Ş. (2024). Havacılık uygulamaları için açık kaynaklı parametrik bir aerodinamik şekil optimizasyon çerçevesinin geliştirilmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 40(1), 381-400. https://doi.org/10.17341/gazimmfd.1334282
AMA Batan B, Abuhanieh S, Çalışıır T, Yiğit Ş. Havacılık uygulamaları için açık kaynaklı parametrik bir aerodinamik şekil optimizasyon çerçevesinin geliştirilmesi. GUMMFD. Ağustos 2024;40(1):381-400. doi:10.17341/gazimmfd.1334282
Chicago Batan, Buğra, Saleh Abuhanieh, Tamer Çalışıır, ve Şahin Yiğit. “Havacılık Uygulamaları için açık Kaynaklı Parametrik Bir Aerodinamik şekil Optimizasyon çerçevesinin geliştirilmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40, sy. 1 (Ağustos 2024): 381-400. https://doi.org/10.17341/gazimmfd.1334282.
EndNote Batan B, Abuhanieh S, Çalışıır T, Yiğit Ş (01 Ağustos 2024) Havacılık uygulamaları için açık kaynaklı parametrik bir aerodinamik şekil optimizasyon çerçevesinin geliştirilmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40 1 381–400.
IEEE B. Batan, S. Abuhanieh, T. Çalışıır, ve Ş. Yiğit, “Havacılık uygulamaları için açık kaynaklı parametrik bir aerodinamik şekil optimizasyon çerçevesinin geliştirilmesi”, GUMMFD, c. 40, sy. 1, ss. 381–400, 2024, doi: 10.17341/gazimmfd.1334282.
ISNAD Batan, Buğra vd. “Havacılık Uygulamaları için açık Kaynaklı Parametrik Bir Aerodinamik şekil Optimizasyon çerçevesinin geliştirilmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40/1 (Ağustos 2024), 381-400. https://doi.org/10.17341/gazimmfd.1334282.
JAMA Batan B, Abuhanieh S, Çalışıır T, Yiğit Ş. Havacılık uygulamaları için açık kaynaklı parametrik bir aerodinamik şekil optimizasyon çerçevesinin geliştirilmesi. GUMMFD. 2024;40:381–400.
MLA Batan, Buğra vd. “Havacılık Uygulamaları için açık Kaynaklı Parametrik Bir Aerodinamik şekil Optimizasyon çerçevesinin geliştirilmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, c. 40, sy. 1, 2024, ss. 381-00, doi:10.17341/gazimmfd.1334282.
Vancouver Batan B, Abuhanieh S, Çalışıır T, Yiğit Ş. Havacılık uygulamaları için açık kaynaklı parametrik bir aerodinamik şekil optimizasyon çerçevesinin geliştirilmesi. GUMMFD. 2024;40(1):381-400.