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Open AccessArticle

Surrogate Aerodynamic Wing Modeling Based on a Multilayer Perceptron

by Oscar Ulises Espinosa Barcenas, Jose Gabriel Quijada Pioquinto, Ekaterina Kurkina and Oleg Lukyanov

Aerospace 2023, 10(2), 149; https://doi.org/10.3390/aerospace10020149 - 6 Feb 2023

Cited by 9 | Viewed by 3065

The aircraft conceptual design step requires a substantial number of aerodynamic configuration evaluations. Since the wing is the main aircraft lifting element, the focus is on solving direct and reverse design problems. The former could be solved using a low-cost computational model, but the latter is unlikely, even for these models. Surrogate modeling is a technique for simplifying complex models that reduces computational time. In this work, a surrogate aerodynamic model, based on the implementation of a multilayer perceptron (MLP), is presented. The input data consist of geometrical characteristics of the wing and airfoil and flight conditions. Some of the MLP hyperparameters are defined using evolutionary algorithms, learning curves, and cross-validation methods. The MLP predicts the aerodynamic coefficients (drag, lift, and pitching moment) with high agreement with the substituted aerodynamic model. The MLP can predict the aerodynamic characteristics of compressible flow up to 0.6 M. The developed MLP has achieved up to almost 800 times faster in computing time than the model on which it was trained. The application of the developed MLP will enable the rapid study of the effects of changes in various parameters and flight conditions on flight performance, related to the design and modernization of new vehicles. Full article

(This article belongs to the Section Aeronautics)

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34 pages, 13382 KiB

Open AccessFeature PaperArticle

Aerodynamic Design Optimization of a Morphing Leading Edge and Trailing Edge Airfoil–Application on the UAS-S45

by Musavir Bashir, Simon Longtin-Martel, Ruxandra Mihaela Botez and Tony Wong

Appl. Sci. 2021, 11(4), 1664; https://doi.org/10.3390/app11041664 - 12 Feb 2021

Cited by 47 | Viewed by 8072

Abstract

This work presents an aerodynamic optimization method for a Droop Nose Leading Edge (DNLE) and Morphing Trailing Edge (MTE) of a UAS-S45 root airfoil by using Bezier-PARSEC parameterization. The method is performed using a hybrid optimization technique based on a Particle Swarm Optimization (PSO) algorithm combined with a Pattern Search algorithm. This is needed to provide an efficient exploitation of the potential configurations obtained by the PSO algorithm. The drag minimization and the endurance maximization were investigated for these configurations individually as two single-objective optimization functions. The aerodynamic calculations in the optimization framework were performed using the XFOIL solver with flow transition estimation criteria, and these results were next validated with a Computational Fluid Dynamics solver using the Transition

(γ - R e_{θ})

Shear Stress Transport (SST) turbulence model. The optimization was conducted at different flight conditions. Both the DNLE and MTE optimized airfoils showed a significant improvement in the overall aerodynamic performance, and MTE airfoils increased the efficiency of C_L^3/2/C_D by 10.25%, indicating better endurance performance. Therefore, both DNLE and MTE configurations show promising results in enhancing the aerodynamic efficiency of the UAS-S45 airfoil. Full article

(This article belongs to the Special Issue Aircraft Modeling and Simulation)

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