Airfoil Design Research Articles

Preliminary Study of Airfoil Design Synthesis Using a Conditional Diffusion Model and Smoothing Method

Generative models such as generative adversarial networks and variational autoencoders are widely used for design synthesis. A diffusion model is another generative model that outperforms GANs and VAEs in image processing. It has also been applied in design synthesis, but was limited to only shape generation. It is important in design synthesis to generate shapes that satisfy the required performance. For such aims, a conditional diffusion model has to be used, but has not been studied. In this study, we applied a conditional diffusion model to the design synthesis and showed that the output of this diffusion model contains noisy data caused by Gaussian noise. We show that we can conduct flow analysis on the generated data by using smoothing filters.

Influence of Airfoil Geometry on VTOL UAV Aerodynamics at Low Reynolds Numbers

This study examines the impact of airfoil geometry on the aerodynamic properties of a low Reynolds number flying wing unmanned aerial vehicle (UAV). The investigation was conducted at three Reynolds numbers (1×106, 2×106, and 5×106), all under a constant Mach number of 0.3 during subsonic flight. Four distinct airfoils from the NACA and Selig series were analyzed using XFLR5 v6.61, with the angle of attack varying from -5° to 15°. Among the airfoils, NACA 6409 consistently demonstrated superior aerodynamic performance across all Reynolds numbers. Notably, at a Reynolds number of 1×106, NACA 6409 achieved a peak lift coefficient (Cl) of 1.584 at an angle of attack of 11.1°, indicating high efficiency. Additionally, the study explored the angles of attack where the drag coefficient (Cd) increased sharply, as well as the lift-to-drag ratios (Cl/Cd), providing a comprehensive understanding of stalling behavior and the balance between lift and drag. These findings offer valuable insights into the aerodynamic efficiency of airfoils in the context of vertical takeoff and landing (VTOL) UAV design, underscoring the importance of further research to optimize airfoil designs for enhanced VTOL UAV performance.

Aerodynamic Optimization Method for Propeller Airfoil Based on DBO-BP and NSWOA

To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting Whale Optimization Algorithm). The NACA4412 airfoil is selected as the research subject, optimizing the original airfoil at three angles of attack (2°, 5° and 10°). The CST (Class Function/Shape Function Transformation) airfoil parametrization method is used to parameterize the original airfoil, and Latin hypercube sampling is employed to perturb the original airfoil within a certain range to generate a sample space. CFD (Computational Fluid Dynamics) software (2024.1) is used to perform aerodynamic analysis on the airfoil shapes within the sample space to construct a sample dataset. Subsequently, the DBO algorithm optimizes the initial weights and thresholds of the BP neural network surrogate model to establish the DBO-BP neural network surrogate model. Finally, the NSWOA algorithm is utilized for multi-objective optimization, and CFD software verifies and analyzes the optimization results. The results show that at the angles of attack of 2°, 5° and 10°, the test accuracy of the lift coefficient is increased by 45.35%, 13.4% and 49.3%, and the test accuracy of the drag coefficient is increased by 12.5%, 39.1% and 13.7%. This significantly enhances the prediction accuracy of the BP neural network surrogate model for aerodynamic analysis results, making the optimization outcomes more reliable. The lift coefficient of the airfoil is increased by 0.04342, 0.01156 and 0.03603, the drag coefficient is reduced by 0.00018, 0.00038 and 0.00027, respectively, and the lift-to-drag ratio is improved by 2.95892, 2.96548 and 2.55199, enhancing the convenience of airfoil aerodynamic optimization and improving the aerodynamic performance of the original airfoil.

How does turbulence intensity affect the fatigue life of composite airfoils based on existing CFD and experimental data?

This research investigates the effect of airflow turbulence intensity on the fatigue life of composite airfoil structures in aerospace engineering. Using advanced Computational Fluid Dynamics (CFD) simulations, this study provides a comprehensive analysis of how varying levels of turbulence intensity—ranging from mild (5%) to severe (30%)—impact the mechanical degradation and fatigue performance of carbon-fiber-reinforced polymers (CFRPs) used in airfoil designs. The research quantifies the relationship between turbulence levels and changes in stress distribution, highlighting critical points of fatigue crack initiation and subsequent propagation. The study includes detailed comparisons of CFD results to experimental data to validate the predictive models and discusses how localized stress fluctuations under high-intensity turbulence accelerate the onset of fatigue failure. We present significant findings that demonstrate a non-linear relationship between turbulence intensity and the reduction in fatigue life, suggesting optimal design modifications for enhanced durability. Furthermore, this paper explores current challenges in merging CFD data with real-world fatigue testing and proposes advanced techniques such as adaptive mesh refinement and hybrid simulation models to improve predictive accuracy and computational efficiency in future research.

CFD analysis of key factors impacting the aerodynamic performance of the S830 wind turbine airfoil

The Global Wind Energy Council (GWEC) reported that in 2021, global wind capacity increased by 93.6 GW (+12%), reaching a total of 837 GW, most of which was contributed by wind turbines. Improving wind turbine performance primarily hinges on advancements in blade technology and airfoil design. This study examines the effect of profile thickness on the aerodynamic performance of the S830 airfoil at a Reynolds number of 25,148, as part of the NREL airfoil's aerodynamic performance research. However, the impacts of additional variables—such as angle of attack, Reynolds number, speed range, and particularly ice accretion—have not been thoroughly investigated. This study utilized a 2D CFD model provided by the commercial software ANSYS Fluent and FENSAP-ICE. The lift-to-drag ratio of the S830 wind turbine airfoil was examined, considering the effects of angle of attack, wind speed, Reynolds number, airfoil thickness, and ice accretion. Additionally, design-related solutions will be suggested. The research indicates that the optimal angle of attack increases the lift-to-drag ratio by approximately 250% compared to a zero angle of attack. An increase in wind speed causes this coefficient to rise nonlinearly within the studied velocity range. The Reynolds number directly influences the optimal angle of attack. According to CFD results, the lift-to-drag ratio can be increased by 50% if the airfoil's thickness is reduced by 20% compared to the original profile. For the ice accretion simulation model, a case test of the NACA 0012 airfoil was conducted to verify the model's parameters. Subsequently, a survey of this phenomenon on the S830 airfoil revealed that the lift coefficient decreased by 5.25% after 90 minutes of ice accretion.

Improving transonic performance with adjoint-based NACA 0012 airfoil design optimization

This study delves into the discrete adjoint method, a powerful tool in high-fidelity aerodynamic shape optimization that efficiently computes derivatives of a target function for different design variables. It offers a theoretical exploration of its implementation as an innovative tool for calculating partial derivatives (sensitivities) related to objective functions and design variables. It is implemented to a NACA0012 airfoil at a transonic speed. This designated test case is qualitatively evaluated, considering specified Mach number and Reynolds number values of 0.7 and 15.96 million, respectively. The standard Spalart-Allmaras turbulence model is adapted to improve computational cost efficiency. The results validate the efficiency of Discrete Adjoint with OpenFOAM, showcasing its capability to generate optimal configurations. The achieved optimized performance is evidenced by minimizing the drag coefficient value (Cd) to an impressive value of 0.00871, 62.2 % lower than the previous studies, thus securing a novelty. While this research does not consider the post-processing of sensitivity calculations, it enables the potential for future research. The primary target of this paper is to assess the educational and training needs of researchers, engineers, and graduate students, offering a comprehensive introduction to discrete adjoint aerodynamic design optimization, presenting a novel methodology, and contributing to future advancements in the design optimization field.

Airfoil Shape Generation and Feature Extraction Using the Conditional VAE-WGAN-gp

A machine learning method was applied to solve an inverse airfoil design problem. A conditional VAE-WGAN-gp model, which couples the conditional variational autoencoder (VAE) and Wasserstein generative adversarial network with gradient penalty (WGAN-gp), is proposed for an airfoil generation method, and then, it is compared with the WGAN-gp and VAE models. The VAEGAN model couples the VAE and GAN models, which enables feature extraction in the GAN models. In airfoil generation tasks, to generate airfoil shapes that satisfy lift coefficient requirements, it is known that VAE outperforms WGAN-gp with respect to the accuracy of the reproduction of the lift coefficient, whereas GAN outperforms VAE with respect to the smoothness and variations of generated shapes. In this study, VAE-WGAN-gp demonstrated a good performance in all three aspects. Latent distribution was also studied to compare the feature extraction ability of the proposed method.

Aerodynamic performance characteristics of low Re airfoils: A parametric and multi criteria decision study

This research aims at investigating the aerodynamic performance of 51 low Re airfoils and applying a Multi Criteria Decision Making (MCDM) approach for selecting airfoils that align with the specific requirements of small wind turbines (SWTs). The study was carried out by varying the Re from 5 × 104 to 5 × 105; angle of attack (AOA) from −10° to 20°, thickness to chord ratio (0.1–0.9), camber ratio (0.1–0.9), and camber position (10 %–80 %) to evaluate the impact of these parameters on the airfoils’ performance. Furthermore, MCDM approach was applied to identify suitable airfoils optimized for their average lift to drag ratio, stall angle, operating range of AOA, strength, manufacturability, and material cost. The findings showed that of the teste parameters, the AOA and airfoil profile have the most pronounced effects on the airfoil performance. Among the tested airfoils, the E63 provided superior performance at 105 Re with LDR of 76.32, a 37.7 % improvement over that of NACA 4412 which is commonly used for wind turbine blade design. Furthermore, the MCDM results revealed that SG6043, FX63-137, E216 and E62 airfoils were the top-ranked airfoils suitable for SWTs application. These findings can help to produce optimized airfoil designs for increased performance and efficiency of SWTs.

Morphing flap driven by link with antagonistic shape memory alloy wires

Abstract This paper describes a study of a morphing flap using antagonistically arranged shape memory alloy (SMA) wires as actuators. The main focus of this study is to examine how existing aircraft structures and mechanisms can be modified to make the morphing airfoil more practical. The first step is to consider the drawbacks of existing morphing airfoils and then examine the advantages of the morphing airfoil proposed in this study. Then, a morphing airfoil is proposed to realize four significant technical issues: weight reduction, compatibility with existing structures, securing internal space, and seamless skin made with shape memory polymer (SMP) films. First, elemental experiments were conducted to examine the feasibility of the mechanical design, and the feasibility of the design of a large-morphing airfoil operating test model was confirmed. Next, aerodynamic and structural-mechanical analyses are conducted while designing the experimental operating model to verify whether it could operate up to the target flap angle under simulated flight conditions. After completing the experimental model, actuation tests are conducted as a morphing wing and confirm whether the wing could operate at the target flap angle in a realistic environment. As a result, the two-way morphing flap angle was experimentally observed. It is noted that only aerodynamic force was not considered in the experiment, which is further investigated in wind tunnel tests in future study. In addition, control rate of the proposed system seems improved than conventional model because of the reduction of the wire length of the actuation system. Thus, the results obtained in this study suggested the proposed link-driven SMA wire mechanism can be applied to make the morphing airfoil more practical.

Experimental Optimization of the SG6043 Airfoil for Horizontal Axis Wind Turbines Using Schmitz Equations

This study presents the experimental optimization of the SG6043 airfoil for horizontal axis wind turbines (HAWTs) using the Schmitz equation, focusing on enhancing power output and elucidating the surface flow structure. Two blade models, M1 (conventional) and M2 (optimized), were designed and tested at rotational speeds of 400 rpm and 600 rpm across a range of tip speed ratios (TSR). The M2 model, optimized using Schmitz equations, demonstrated significantly improved performance compared to the M1 model at both rotational speeds. At 400 rpm, the maximum power coefficient (CP) for M1 was 0.274, while M2 reached 0.419, indicating a 52.91% improvement. At 600 rpm, M1 achieved a maximum CP of 0.293, whereas M2 attained 0.458, representing a 56.31% enhancement. The M2 model also showed superior performance at higher TSRs, with the highest percentage increase in CP recorded at 4.9 TSR, reaching 574.54%. Additionally, dynamic surface oil-flow visualization experiments were conducted to examine flow behavior on the blade surfaces. Results indicated better flow attachment in the M2 blade due to its optimized twist angle and chord length, particularly in the mid-section, leading to delayed flow separation. The reattachment observed on the suction side of the M2 model, following the laminar separation bubble (LSB), which was absent in the M1, contributed to its higher aerodynamic efficiency and overall power performance. These findings confirm that the optimized SG6043 airfoil design, guided by Schmitz equations, offers significant improvements in HAWT performance, particularly under varying operational conditions.

Airfoil Design and Aerodynamics Characteristics of Energy-Efficient Race Car: CFD Analysis

The use of land transportation, primarily cars, is increasing annually. The energy required will increase along with the number of vehicles. Thus far, car manufacturers are required to improve car designs and propose fuel-efficient and environmentally friendly cars. The energy-efficient car competition, namely, Kontes Mobil Hemat Energi Indonesia, is organised for mechanical engineering students to contribute directly to research related to energy-efficient cars in Indonesia. One of the ways to save fuel is to reduce the aerodynamic force drag on the vehicle. This study aims to optimize the prototype vehicle airfoil design in producing the smallest possible coefficient of drag (Cd) and lift (Cl). A Taguchi design of experimental (DoE) is applied to set the 9 designs for this study, with three different values considered for each design parameters: Defiant Canard BL110, Clark YM15, Gottingen 256 for side airfoil shapes and Gottingen 410, Gottingen 460, and Boeing 737 Root for top airfoil shapes. This aerodynamic analysis uses the ANSYS 2020 R1 software, which is carried out at a speed of 30 km/h. Then the Cd and Cl values obtained will be analyzed. The results obtained for the optimal design of the Cd with variations in the side airfoil design Defiant Canard BL110 and top airfoil is Gottingen 410 with a Cd value of 0,1119. As for the optimal design of the Cl with variations in the side airfoil design Gottingen 256 and top airfoil is Gottingen 460 with a Cl value of 0,0250.

The future of flying: Explore more energy-efficient airplane wings

In recent years, there has been a substantial rise in the popularity of air travel, bringing with it a surge in the consumption of jet fuel, a nonrenewable resource responsible for 2.4% of global carbon emissions. As air travel continues to gain prevalence, the anticipation of a significant increase in carbon emissions and a subsequent surge in jet fuel costs looms large. Maintaining affordability in air travel while mitigating carbon emissions necessitates a focus on maximizing airfoil efficiency. This study investigates how airplane wing design affects the aerodynamic performance of aircraft, with a specific focus on the impact of wing angle of attack, wing length, and winglets. In this research, this study use Computational Fluid Dynamics software to simulate and analyze the aerodynamic forces acting upon an aircraft to deduce its drag and lift coefficients. Employing diverse fluid dynamics formulas, the research calculates the aerodynamic performance of various aircraft airfoil designs, aiming to identify the optimal design. The envisioned optimal configuration is likely to feature an elongated wing, a 20 angle of attack, and suitable winglets stalled, strategically incorporated to enhance overall efficiency in air travel.

Airfoil cross flow field to enhance mass transfer capacity and performance for PEMFC

Proper design of the flow field in bipolar plates is important for improving proton exchange membrane fuel cells in water transport, gas distribution and net power density enhancement. Inspired by the fact that the streamlined design of an airplane airfoil makes the flow resistance reduced, a new airfoil cross flow field is proposed. Airfoil cross flow field is composed of a regular pattern of airfoil pins which are categorized in pin-type flow fields. The effects of different airfoil-pin shapes and arrangements on cell performance were explored. The results showed that airfoil cross flow field improved water management by finely modulating the airflow significantly increasing the gas flow rate in the channel. In addition, the airfoil cross flow field design achieves higher and more uniform oxygen distribution at the interface between the gas diffusion layer and the catalyst layer. The proper shape and arrangement of the airfoil-pins can effectively increase the net power density of the cell by 10.65 % and 2.49 % compared to the conventional parallel flow field and the square-pin flow field. Due to the streamlined design of the airfoil cross flow field, the voltage drop is approximately 60 % of that of the conventional parallel flow field and even slightly lower than that of the square-pin flow field, which demonstrates its high practicality. In summary, the airfoil cross flow field well coordinates the high current density and low voltage drop requirements of proton exchange membrane fuel cells, and some new points of view on flow field design are presented.

Statistical Analysis of Airfoil Usage in Aircraft

The study aims to answer how frequently airfoils are used in fixed and rotary wing aerial vehicles produced both individually and based on airfoil families. Frequency distribution analysis of airfoil utilization in fixed-wing and rotary-wing aircraft helps in understanding design preferences and performance needs and constraints. The literature study provides the history of airfoils, the subjects mostly studied regarding airfoils and mentions the current state of the field. The study investigates the airfoil families to which the wing profiles of approximately 6,000 fixed-wing and approximately 450 rotary-wing aircraft belong through frequency distribution. The results indicate that in fixed-wing aircraft, NACA airfoils are used in 52.2%, Clark-Y airfoils in 8.2%, Goettingen airfoils in 5.9%, Wortman airfoils in 4.8%, and TsAGI airfoils in 3.1%. When considered as singular airfoil use rather than airfoil families, Clark-Y is the most widely used airfoil, followed by the NACA 23XXX series. In rotary-wing aircraft, NACA 0012 and NACA 0015 airfoils, both symmetrical profiles developed by NACA, are the most widely used. The study is valuable as it provides statistical data on the use of both airfoil families and singular airfoil design in fixed and rotary-wing aircraft. However, it is important to note that the airfoil data is incomplete, and the study aims to provide a general impression of the findings.

Multi-layer topology optimization of dual-fluid convective heat transfer in printed circuit heat exchangers

Optimizing channel configurations in printed circuit heat exchangers is essential for enhancing heat transfer and minimizing pumping power. The present study aims to optimize channel configurations by developing a multi-layer topology optimization (TO) model that simultaneously optimizes the fin structures in both the cold and hot fluid layers. The TO model directly integrates the heat transfer rate as the target function while using the pressure drop from an airfoil structure as the constraint. Counterintuitive channel configurations are generated by the TO model under various Reynolds numbers (Re). The evaluation under both laminar and turbulent conditions demonstrates that the TO-designed channel configuration outperforms conventional channel configurations including empty, airfoil, heatric, louver, modified louver, sine curve, and S-shaped designs. Compared with the airfoil structure, at Re = 300, the optimized structure can reduce pumping power by 17.0 % while increasing heat transfer by 10.8 %, and at Re = 20000 it reduces pumping power by 52.0 % and enhances heat transfer by 1.2 %. The present study introduces a promising method for designing novel printed circuit heat exchangers.

Surrogate based design space exploration and exploitation for an efficient airfoil optimization under uncertainties using transition models

The pursuit of sustainable, zero-emission air travel is heavily dependent on the creation of energy-efficient aircraft. Key strategies for achieving this sustainability in aviation include reducing fuel consumption through low-drag designs harnessing laminar flow. However, designing aircraft with laminar flow characteristics is complex due to their sensitivity to environmental and operational factors. This study tackles the challenge of developing energy-efficient aircraft by using computational fluid dynamics models and sophisticated optimization techniques that account for uncertainty. Our approach demonstrates the effectiveness of surrogate-based optimization and uncertainty quantification in optimizing airfoil drag for a natural laminar airfoil (NLF) design. We use surrogate models, trained with data from detailed airfoil simulations, which include a boundary layer code coupled with a linear stability method and a newly developed transition transport model. Transition location predicted using transition models facilitate an accurate drag prediction used in the optimization process. The accuracy of these surrogate models is enhanced through active sampling strategies. Our robust optimization method considers uncertainties in environmental and operational conditions, offering a deeper insight into their effects on crucial design parameters. Unlike traditional deterministic aerodynamic design optimization, our findings highlight the efficacy and precision of uncertainty-based optimization in achieving robust NLF airfoil designs over large (exploration mode) and small (exploitation mode) design spaces. Investigating design space parameterization based on the size of design variables reveals significant differences in optimal airfoil configurations. The optimized designs we propose favor delayed transition, in contrast to deterministic designs which often result in significant loss of laminarity when facing uncertainties. This study represents a significant advancement in aerospace engineering, providing a practical and effective methodology for creating energy-efficient airfoil designs. The application of these advanced optimization and uncertainty quantification techniques shows great potential for the wider field of aerospace engineering, paving the way for more resilient and robust aircraft designs.

Aerodynamic shape optimization using a physics-informed hot-start method combined with modified metric-based proper orthogonal decomposition

Aerodynamic shape optimization based on computational fluid dynamics still has a huge demand for improvement in the optimization effect and efficiency when optimizing the unstable flow of airfoils. This article presents a physics-informed hot-start method combined with modified metric-based proper orthogonal decomposition (MPOD-ML-Phys). The data-based filtering strategy is a core step in the original metric-based proper orthogonal decomposition method (MPOD), but existing filtering strategies generate a significant amount of additional computational consumption. Therefore, this article applies machine learning methods to data-based filtering strategy in MPOD and establishes a modified MPOD method (MPOD-ML). In addition, during the MPOD-ML process, a lot of hidden physical knowledge that is beneficial for optimization will also be generated. This article combines Bayesian optimization to construct an MPOD-ML-Phys method, which fully utilizes the flow physical knowledge in MPOD-ML. The efficiency and effect of MPOD-ML and MPOD-ML-Phys are validated by two typical cases: inverse and direct design for airfoils. The results indicate that both MPOD-ML and MPOD-ML-Phys methods can effectively improve the overall optimization efficiency. However, the intervention of machine learning models has significantly reduced the robustness of the MPOD-ML method, while the embedding of physical knowledge makes MPOD-ML-Phys more robust. Meanwhile, the optimized airfoil obtained by MPOD-ML-Phys has better drag divergence characteristics, a later flow separation point, and better flow stability.

Investigating Propellers for Drone Applications: Analyzing Varied Designs and Characteristics

The importance of drones has evidently increased in various aspects of daily life, such as defense, agriculture, disaster management, and more. Drone propellers are crucial for generating the lift and propulsion necessary for steady flight. Efficient propeller design is critical for maximizing flight time and maneuverability in drones. We are currently investigating the impact of different propeller designs on drone performance. Our research focuses on optimizing propeller characteristics to ensure optimal propulsion and overall functionality. By testing three airfoil designs and systematically varying the angle of attack and pitch, we aim to understand how these changes influence the propeller's efficiency and effectiveness. The CFD-based analysis primarily evaluates parameters such as the lift-to-drag ratio and RPM to determine the most suitable design for drone operations. Through extensive analysis and data collection, the study seeks to identify settings that balance performance metrics, ultimately enhancing the drone's functionality. Based on insights from the analysis, various iterations and refinements have been carried out to draw informed conclusions about the most effective propeller design for drone applications.

Airfoil Design Optimization of Blended Wing Body for Various Aerodynamic and Stealth Stations

The airfoil is the foundation of an aircraft, and its characteristics have a significant impact on those of the aircraft. Conventional airfoil design mainly focuses on improving aerodynamic performance, while flying wing airfoil designs should also consider layout stability and stealth performance. The design requirements for an airfoil vary with its position on the flying wing layout aircraft based on corresponding spanwise flow field characteristics. By analyzing the spanwise flow characteristics of the flying wing, partition design models for flying wing airfoils were established in this study, and a series of flying wing airfoil designs that consider aerodynamics and aerodynamic/stealth were implemented. Then, the designed airfoils were configured on a three-dimensional X-47B layout for testing and verification. The results showed that the aerodynamic design and the aerodynamic/stealth design exhibited significant improvements in terms for aerodynamic and longitudinal trimming characteristics. However, the cruise drag performance of the aerodynamic/stealth design was slightly worse than that of the aerodynamic design, although the longitudinal moment trimming characteristics were basically the same. The stealth characteristics of the aerodynamic/stealth design had significant advantages, indicating that there were weak contradictions between the aerodynamic, stealth, and trimming requirements in the design of the flying wing.

Parsimonious airfoil Parameterisation: A deep learning framework with Bidirectional LSTM and Gaussian Mixture models

The choice of airfoil parameterisation method significantly influences the overall wing optimisation performance by affecting the flexibility and computational efficiency of the process. Ideally, one should be able to intuitively constrain airfoil shape and structural characteristics as input to the optimisation process. Current parameterisation techniques lack the flexibility to generate airfoils efficiently by specifying parsimonious shape and structural features. To address this limitation, a deep learning framework is proposed, enabling conditional airfoil generation from an airfoil’s shape and structural feature definition.Specifically, we demonstrate the application of Bidirectional Long Short Term Memory models and Bayesian Gaussian Mixture models to derive airfoil coordinates from a compact set of shape and structural characteristics that we define. The proposed framework is shown to achieve favorable airfoil performance optimisation due to improved exploration and exploitation of the design space, compared to traditional approaches. Overall, the proposed optimisation framework is able to realise a 9.04% performance improvement over an airfoil design optimised with traditional parameterisation techniques.