Research article

CFD investigation on the maximum lift coefficient degradation of rough airfoils

  • Received: 27 November 2020 Accepted: 07 February 2021 Published: 03 March 2021
  • Ice accretion can reduce the performance of aircraft's wings, which results in higher fuel consumption and risk of accidents. Experiments proved that even in its very earlier stages (increased roughness), icing could cause a reduction of 25% in the maximum lift, and an increase of 90% in drag of an aspect ratio 6 wing. In this work, we propose a correlation to predict the degradation of the maximum lift coefficient caused by roughness effects on flows over two airfoils, a NACA 0012 and a model 5–6. In addition, a second correlation is proposed to find the minimum Reynolds number that are useful for higher Reynolds number applications when roughness is considered. The SA roughness extension is implemented into an open-source code called SU2. The verification and validation of the implementation is performed in two steps. First, the behavior of the flow over a smooth NACA 0012 is investigated to confirm whether the implementation has no influence on the original model when roughness is not activated. Then, roughness is activated, and estimations of lift coefficients and velocity profiles inside the boundary layer are evaluated and compared to numerical and experimental results. Finally, investigations on the maximum lift coefficient reduction caused by different equivalent sand grain roughness heights and Reynolds numbers are performed. Our results demonstrated that, for the equivalent sand grain roughness heights investigated, the variation of sufficiently small heights has no significant influence on the maximum lift coefficient degradation. Moreover, when roughness is continuously increased, a saturation point seems to be approached, in which the variation of the maximum lift coefficient degradation is reduced. We noticed that although the reduction of the maximum lift coefficient caused by different equivalent sand-grain roughness heights and Reynolds number present similar behavior, they fall into different curve formats.

    Citation: Gitsuzo B.S. Tagawa, François Morency, Héloïse Beaugendre. CFD investigation on the maximum lift coefficient degradation of rough airfoils[J]. AIMS Energy, 2021, 9(2): 305-325. doi: 10.3934/energy.2021016

    Related Papers:

    [1] Ahmed A. Elgibaly, Mohamed Ghareeb, Said Kamel, Mohamed El-Sayed El-Bassiouny . Prediction of gas-lift performance using neural network analysis. AIMS Energy, 2021, 9(2): 355-378. doi: 10.3934/energy.2021019
    [2] Abdulrahman Th. Mohammad, Wisam A. M. Al-Shohani . Numerical and experimental investigation for analyzing the temperature influence on the performance of photovoltaic module. AIMS Energy, 2022, 10(5): 1026-1045. doi: 10.3934/energy.2022047
    [3] Nelson Batista, Rui Melicio, Victor Mendes . Darrieus-type vertical axis rotary-wings with a new design approach grounded in double-multiple streamtube performance prediction model. AIMS Energy, 2018, 6(5): 673-694. doi: 10.3934/energy.2018.5.673
    [4] Muluken Biadgelegn Wollele, Abdulkadir Aman Hassen . Design and experimental investigation of solar cooker with thermal energy storage. AIMS Energy, 2019, 7(6): 957-970. doi: 10.3934/energy.2019.6.957
    [5] Sri Kurniati, Sudirman Syam, Arifin Sanusi . Numerical investigation and improvement of the aerodynamic performance of a modified elliptical-bladed Savonius-style wind turbine. AIMS Energy, 2023, 11(6): 1211-1230. doi: 10.3934/energy.2023055
    [6] Joanna McFarlane, Jason Richard Bell, David K. Felde, Robert A. Joseph III, A. Lou Qualls, Samuel Paul Weaver . Performance and Thermal Stability of a Polyaromatic Hydrocarbon in a Simulated Concentrating Solar Power Loop. AIMS Energy, 2014, 2(1): 41-70. doi: 10.3934/energy.2014.1.41
    [7] Muzaffar Ali, Hafiz.M. Ali, Waqar Moazzam, M. Babar Saeed . Performance enhancement of PV cells through micro-channel cooling. AIMS Energy, 2015, 3(4): 699-710. doi: 10.3934/energy.2015.4.699
    [8] Honnurvali Mohamed Shaik, Adnan Kabbani, Abdul Manan Sheikh, Keng Goh, Naren Gupta, Tariq Umar . Measurement and validation of polysilicon photovoltaic module degradation rates over five years of field exposure in Oman. AIMS Energy, 2021, 9(6): 1192-1212. doi: 10.3934/energy.2021055
    [9] M. Boussaid, A. Belghachi, K. Agroui, N.Djarfour . Mathematical models of photovoltaic modules degradation in desert environment. AIMS Energy, 2019, 7(2): 127-140. doi: 10.3934/energy.2019.2.127
    [10] Saad S. Alrwashdeh . Investigation of the effect of the injection pressure on the direct-ignition diesel engine performance. AIMS Energy, 2022, 10(2): 340-355. doi: 10.3934/energy.2022018
  • Ice accretion can reduce the performance of aircraft's wings, which results in higher fuel consumption and risk of accidents. Experiments proved that even in its very earlier stages (increased roughness), icing could cause a reduction of 25% in the maximum lift, and an increase of 90% in drag of an aspect ratio 6 wing. In this work, we propose a correlation to predict the degradation of the maximum lift coefficient caused by roughness effects on flows over two airfoils, a NACA 0012 and a model 5–6. In addition, a second correlation is proposed to find the minimum Reynolds number that are useful for higher Reynolds number applications when roughness is considered. The SA roughness extension is implemented into an open-source code called SU2. The verification and validation of the implementation is performed in two steps. First, the behavior of the flow over a smooth NACA 0012 is investigated to confirm whether the implementation has no influence on the original model when roughness is not activated. Then, roughness is activated, and estimations of lift coefficients and velocity profiles inside the boundary layer are evaluated and compared to numerical and experimental results. Finally, investigations on the maximum lift coefficient reduction caused by different equivalent sand grain roughness heights and Reynolds numbers are performed. Our results demonstrated that, for the equivalent sand grain roughness heights investigated, the variation of sufficiently small heights has no significant influence on the maximum lift coefficient degradation. Moreover, when roughness is continuously increased, a saturation point seems to be approached, in which the variation of the maximum lift coefficient degradation is reduced. We noticed that although the reduction of the maximum lift coefficient caused by different equivalent sand-grain roughness heights and Reynolds number present similar behavior, they fall into different curve formats.



    The growing interest of philosophers to neuroscience has promoted the birth of a new discipline in the field of ethics called Neuroethics.

    The innovative side of this discipline is the adoption of neuroscientific methods to explain how, and which neural processes subserve ethical reasoning. However, it should be clarified that the mission of Neuroethics is not limited to the investigation of neurobiological correlates of moral behavior, but it also includes questions about the moral implications of neuroscientific methods. In this regard, it is useful the terminological distinction by Adina Roskies between “Neurosciences of Ethics” and “Ethics of Neurosciences[1].

    Regarding the “Neuroscience of Ethics”, some interesting insight can be derived from the study of clinical populations affected by neurological and/or psychiatric disorders. A paradigmatic case, which is probably the first one reported in the literature, was described by Harrlow [2] with the patient Phineas Gage. As result of a work accident, which made this patient victim of a severe brain injury involving the medial and orbital regions of the frontal lobe, Phineas Gage had become an impulsive, violent and profane man. Damasio [3] suggested that a lesion of the ventromedial prefrontal cortex (vmPFC) leads to the loss of the influence of ethics principles and the emotional appraisal ​​typically involved in the evaluation of moral outcome such as the discrimination of good from bad. Moreover, patients affected by a damage of the vmPFC, were unable to correct or control harmful behaviors and/or unusual reactions while facing moral outcomes, such as those provided through the “Iowa Gambling” Task [4], a psychological task developed to measure “real world” decision-making deficits in patients with damage to the prefrontal cortex [5]. According to Damasio [3], it is not the reasoning ability of these patients that is affected but their emotions, intended as somatic markers used by the brain to quickly and unconsciously filter options with important positive or negative emotional consequences.

    If the case of Phineas Gage highlights the importance of the frontal lobe in moral behavior, subsequent studies involving healthy participants through the use of neurophysiological techniques, such as functional magnetic resonance imaging and non-invasive brain stimulation methods, have revealed a wider and much more complex neural network. Among these regions it should be mentioned the cingulate cortex, a neural structure considered important in mediating the conflict between the emotional and rational component of moral reasoning [6]; the insula, a neural structure of central importance in the elaboration of interoceptive states (e.g. [7],[8]), which seems to be involved in the elaboration of the affective component of the sense of iniquity [6],[9]; and the basal ganglia such as the subthalamic nucleus, which is involved in the evaluation of morally related conflicting situations [10].

    Turning back to the relevance of clinical models in the field of Neuroethics, it should be mentioned the case of movement disorders such as Parkinson's syndrome, Huntington's chorea, and Tourette's syndrome, which are characterized by a reduced sensitivity towards ethical violations (for a review see [11],[12],[13]. Moreover, an important contribute comes from the examination of psychiatric syndromes such as obsessive-compulsive disorder (OCD) [11],[14] and Depression [15], which are characterized by a high sensitivity to ethical violations. It is interesting to note that all syndromes mentioned above are affected by similar anatomo-functional alteration of neural structures (Insula, Cingulate Cortex, Basal Ganglia) involved in moral processing (see [11] for a review). Furthermore, for all these syndromes it is documented an altered representation/perception of disgust (from core disgust to social disgust).

    Disgust can be explained as a negative emotion towards specific stimuli that leads to avoid them [16]. Since several years there is a debate about a possible relationship between disgust and morality. Pizarro and colleagues [17] developed three different principles to explain this relationship. In the first case, it is possible to speak about the experience of disgust as a consequence of moral disapproval (e.g., [18]). In the second case, disgust becomes an instrument to prime (amplify) moral rejection. For example, it was shown that inducing disgust leads people to have harsher moral judgments (e.g.,[19]). Moreover, the lower the disgust sensitivity the lower the disapproval of ethical violations (e.g., [20]). In the third case, disgust is understood as an engine to influence the judgment of morally neutral acts. According to the second principle, in Parkinson's Syndrome [21],[22] or Huntington's chorea [23],[24], the sensitivity to core disgust is reduced compared to controls. On the other hand, a higher sensitivity to disgust has been reported in patients affected by OCD [25] and depression (e.g.,[26]).

    In Tourette's syndrome, we recently documented higher disgust sensitivity compared to controls [13]. This contrasts the greater tolerance of unethical behaviors in TS adolescents compared to controls, as the general literature which documents higher moral disapproval in individuals with higher disgust sensitivity [20],[27]. However, the reduced moral disapproval of ethical violations in TS is consistent with prior evidence of increased impulsivity in this clinical population [28], which is associated with reduced moral disapproval in healthy humans [29].

    The evidence provided by the study of ethical behavior in clinical models supports the neo-sentimentalist perspective, which postulates a close relationship between disgust and morality (e.g.,[30]). However, it should be clarified that a distinction exists between “emotional appraisal” and “utilitarian appraisal” in the judgment of moral outcomes [31]. From a critical analysis [9] of the fMRI study by Hutcherson et al. [31], it was outlined that the neural circuits classically involved in the processing of disgust only overlap those involved in the “emotional appraisal” of moral outcomes. On the other hand, the neural circuit reported in response to “utilitarian appraisal” of moral topics is clearly independent from the one associated with disgust processing. This suggests that the influence of disgust on morality may be mainly involved in (if not limited to) the emotional evaluation of moral outcomes, instead of being considered the general root of morality.

    In summary, these results provide a contribute to the current debate between the neosentimentalist and rationalist perspective of morality by suggesting that the influence of disgust on ethics behavior is related with the affective appraisal of this human experience.

    In conclusion, the study of ethics through clinical models affected by neural disorders and, more generally, through the adoption of neuroscientific methods represents a valuable approach to learn more about the origin of the noblest faculty of the human being.



    [1] Gulick BG (1938) Effects of a simulated ice formation on the aerodynamic characteristics of an airfoil (NACA-WR-L-292). NTRS-NASA technical reports server. Available from: https://ntrs.nasa.gov/citations/19930093051.
    [2] Beierle MT (1999) Investigation of effects of surface roughness on symmetric airfoil lift and lift-to-drag ratio. University of maryland-college park, defense technical information center. Available from: http://www.dtic.mil/dtic/tr/fulltext/u2/a360065.pdf.
    [3] Cao Y, Wu Z, Su Y, et al. (2015) Aircraft flight characteristics in icing conditions. Prog Aerosp Sci 74: 62-80. doi: 10.1016/j.paerosci.2014.12.001
    [4] Beaugendre H, Morency F, Habashi WG, et al. (2003) Roughness implementation in FENSAP-ICE: Model calibration and influence on ice shapes. J Aircr 40: 1212-1215. doi: 10.2514/2.7214
    [5] deVelder NB (2020) Rough airfoil simulation for wind turbine applications. University of massachusetts amherst. Available from: https://scholarworks.umass.edu/dissertations_2/1820/.
    [6] Aupoix B (2015b) Roughness corrections for the k-ω shear stress transport model: Status and proposals. J Fluids Eng 137. Available from: https://doi.org/10.1115/1.4028122.
    [7] Schlichting H (1937) Experimental investigation of the problem of surface roughness (NACA-TM-823). Available from: https://ntrs.nasa.gov/citations/19930094593.
    [8] Dirling JR (1973) A method for computing roughwall heat transfer rates on reentry nosetips. Paper presented at the 8th thermophysics conference, fluid dynamics and co-located conferences, palm springs, CA, U.S.A. Available from: https://doi.org/10.2514/6.1973-763.
    [9] Liu S (2014) Simulation of transition and roughness effects on micro air vehicle aerodynamics. University of Sheffield. Available from: http://etheses.whiterose.ac.uk/id/eprint/7757.
    [10] Aupoix B, Spalart P (2003) Extensions of the spalart-allmaras turbulence model to account for wall roughness. Int J Heat Fluid Flow 24: 454-462. doi: 10.1016/S0142-727X(03)00043-2
    [11] Patel V (1998) Perspective: flow at high reynolds number and over rough surfaces-Achilles heel of CFD. Available from: https://doi.org/10.1115/1.2820682.
    [12] Lynch FT, Khodadoust A (2001) Effects of ice accretions on aircraft aerodynamics. Prog Aerosp Sci 37: 669-767. doi: 10.1016/S0376-0421(01)00018-5
    [13] Brumby RE (1979) Wing surface roughness: Cause and effect. DC Flight Approach 32: 2-7.
    [14] Jackson DG (1999) Effect of simulated ice and residual ice roughness on the performance of a natural laminar flow airfoil. University of illinois at urbana-champaign. Available from: http://icing.ae.illinois.edu/papers/00/darren%20jackson%20dissertation.html.
    [15] Pope SB (2000) Turbulent flows. Cambridge: Cambridge university press.
    [16] Blazek J (2015) Computational fluid dynamics: principles and applications (Third ed.): Elsevier Ltd.
    [17] Palacios F, Colonno MR, Aranake AC, et al. (2013). Stanford university unstructured (SU2): An open-source integrated computational environment for multi-physics simulation and design. Paper presented at the 51st AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition 2013, Grapevine, TX, United states. Available from: https://doi.org/10.2514/6.2013-287.
    [18] Spalart P, Allmaras S (1992) A one-equation turbulence model for aerodynamic flows. Paper presented at the 30th aerospace sciences meeting and exhibit. Available from: https://doi.org/10.2514/6.1992-439.
    [19] Nikuradse J (1933) Laws of flow in rough pipes. National advisory committee for aeronautics washington.
    [20] Molina E, Spode C, Annes da Silva RG, et al. (2017) Hybrid rans/les calculations in su2. Paper presented at the 23rd AIAA Computational Fluid Dynamics Conference. Available from: https://doi.org/10.2514/6.2017-4284.
    [21] White FM, Corfield I (2006) Viscous fluid flow (Vol. 3). McGraw-hill New York.
    [22] Jespersen DC, Pulliam TH, Childs ML (2016) Overflow turbulence modeling resource validation results (20190000252) NTRS-NASA technical reports server: NASA. Available from: https://ntrs.nasa.gov/citations/20190000252.
    [23] Langel CM, Chow R, Van Dam C, et al. (2017) RANS based methodology for predicting the influence of leading edge erosion on airfoil performance. Sandia national lab.(SNL-NM), Albuquerque, NM (United States). Available from: https://www.osti.gov/biblio/1404827-rans-based-methodology-predicting-influence-leading-edge-erosion-airfoil-performance.
    [24] Mendez B, Muñoz A, Munduate X (2015) Study of distributed roughness effect over wind turbine airfoils performance using CFD. Paper presented at the 33rd wind energy symposium, Kissimmee, Florida. Available from: https://doi.org/10.2514/6.2015-0994.
    [25] Gregory N, O'Reilly CL (1970) Low-speed aerodynamic characteristics of NACA0012 aerofoil section, including the effects of uppe-surface roughness simulating hoar frost. (3726). CiteSeerX. Available from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.227.696&rep=rep1&type=pdf.
    [26] Kerho MF, Bragg MB (1997) Airfoil boundary-layer development and transition with large leading-edge roughness. AIAA J 35: 75-84. doi: 10.2514/2.65
    [27] Ladson CL (1988) Effects of independent variation of mach and reynolds numbers on the low-speed aerodynamic characteristics of the NACA 0012 airfoil section (NASA-TM-4074). NTRS-NASA technical reports server. Available from: https://ntrs.nasa.gov/citations/19880019495.
    [28] Rumsey C, Smith B, Huang G (2018) Turbulence modeling resource website. Available from: http://turbmodels.larc.nasa.gov.
    [29] Abbott IH, Von Doenhoff AE, Stivers Jr L (1945) Summary of airfoil data (NACA-TR-824). Office of Aeronautical Intelligence, Washington, DC, United States. Available from: https://ntrs.nasa.gov/citations/19930090976.
    [30] Hellsten A, Laine S (1998) Extension of k-W shear-stress transport turbulence model for rough-wall flows. AIAA J 36: 1728-1729. doi: 10.2514/2.7543
    [31] Knopp T, Eisfeld B, Calvo JB (2009) A new extension for k-ω turbulence models to account for wall roughness. Int J Heat Fluid Flow 30: 54-65. doi: 10.1016/j.ijheatfluidflow.2008.09.009
    [32] Bragg MB, Broeren AP, Blumenthal LA (2005) Iced-airfoil aerodynamics. Progress Aerosp Sci 41: 323-362. doi: 10.1016/j.paerosci.2005.07.001
    [33] GARTEUR Action group AG-32 (2003) Prediction of performance degradation due to icing for 2D configurations. Final report of GARTEUR AG-32. July, 2003.
    [34] Tagawa GBS, Morency F, Beaugendre H (2018) CFD study of airfoil lift reduction caused by ice roughness. Paper presented at the 2018 applied aerodynamics conference. Available from: https://doi.org/10.2514/6.2018-3010.
    [35] Kays WM, Crawford ME (1980) Convective heat and mass transfer, 2nd ed., McGraw-Hill, New York.
  • This article has been cited by:

    1. Roland Fürbacher, Gerhard Liedl, Gabriel Grünsteidl, Andreas Otto, Icing Wind Tunnel and Erosion Field Tests of Superhydrophobic Surfaces Caused by Femtosecond Laser Processing, 2024, 4, 2674-032X, 155, 10.3390/wind4020008
    2. Xiaojing Tian, Weiqi Ye, Liang Xu, Anjian Yang, Langming Huang, Shenglong Jin, Optimization research on laminated cooling structure for gas turbines: A review, 2025, 13, 2333-8334, 354, 10.3934/energy.2025014
  • Reader Comments
  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3824) PDF downloads(216) Cited by(2)

Article outline

Figures and Tables

Figures(16)  /  Tables(2)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog