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Parametrization of an Aileron

CFD Parametric Study Machine Learning

Tools

SIMULIA, CFD, Statistical Analysis

Status

Completed

Overview

This project focuses on the parametric design and analysis of aileron geometry to achieve optimized aerodynamic performance. By defining key geometric parameters and studying their effects on lift, drag, and control authority, the project establishes a systematic approach to aileron design.

Objectives

Define a comprehensive set of geometric parameters for aileron design
Develop a parametric CAD model for rapid design iteration
Analyze the aerodynamic effects of parameter variations
Optimize aileron geometry for improved performance

Approach

The aileron geometry was parametrized using key variables including maximum camber, location of maxium camber, maxium thickness, chord length, angle of incidence, and spoiler length. A parametric CAD model was developed to enable rapid exploration of the design space and facilitate iterative analysis.

To determine the forces acting on the airfoil, a CFD analysis was conducted. The CFD analysis allowed for a clearer view of the fluid motion surrounding the airfoil. Additionally, it allowed for relationships to be made between the parameters and the outputs.

The first step was to choose a fluid domain that would serve as a region of airflow around the airfoil. This domain was specified under a bounding box at a specified dimension to avoid near wall effects. After defining the boundary box dimensions, the wall boundaries were given specific characteristics. One was designated as the pressure outlet while the other was designated as the velocity inlet with a value of 43 m/s. Figure 1 shows the fluid domain with the aileron in the center.

Boundary Box — Figure 1: Fluid domain with the aileron in the center

After confirming the dimensions of the fluid domain, the mesh was created. The mesh was created using various hexagonal pieces to form various points for the CFD sim to run simulations on. Figure 2 shows the hex mesh.

Hex Mesh — Figure 2: Hexagonal mesh for CFD simulation

After performing a CFD simulation, values for lift and drag were outputted. Lift values were in the negative region as the aileron's primary purpose is to generate downwards lift or downforce. Once these values were determined, 3DExperience's optimization software was used to optimize lift and drag in terms of the chord length and angle of incidence.

The optimization process was done using two methods: Optimal Latin Hypercube and Full Factorial. Latin Hypercube is a derivation of Latin Hypercube Sampling (LHS) that further optimizatizes the random sampling process. Figure 3 shows the data point distribution for LHS.

Figure 3: Data point distribution for LHS

Optimal Latin Hypercube Sampling (OLHS) optimizates the data points by generating new matrices of data points and evaluating the spaces between the data points. The goal is to design a matrix where the points are spread as evenly as possible. Figure 4 shows the sampling of a OLHS matrix.

Using this sampling technique, the parametric study was performed. Using Dassault Systemes' Design of Experiments (DOE) software, the parametric study was performed using the aforementioned sampling methods. Optimization charts were generated for the lift, drag, chord, and incidence and an optimal design point was determined. All optimization runs showed an anlysis of around 600 points before arriving at an optimal design point.Figure 5 shows the optimization chart for the lift.

Optimization Chart Lift — Figure 5: Optimization chart for lift

Figure 6 shows the optimization chart for the drag.

Optimization Chart Drag — Figure 6: Optimization chart for drag

Figure 7 shows the optimization chart for the chord.

Optimization Chart Chord — Figure 7: Optimization chart for chord

Figure 8 shows the optimization chart for the angle of incidence.

Optimization Chart Incidence — Figure 8: Optimization chart for angle of incidence

The optimal design was determined to be a chord length of 165 mm, a incidence of 11.9 degrees, a lift or downforce value of -179.44 N, and a drag value of 51.164 N.

The lift and drag values were plotted using response surface models (RSM), which map the relationship between multiple variables and the output. RSMs offer a 3-dimensional view of the data set. The RSMs produced using the Design of Experiments software display a heatmap of the data, allowing for easy identification of peaks and valleys.

Each RSM shows the design point stated earlier.Figure 9 shows the RSM for lift.

Figure 10 shows the RSM for drag.

Results

The parametric study revealed the relationships between geometric parameters and aerodynamic performance metrics. The findings provide valuable design guidelines for aileron configuration in various flight conditions.