Neural-Network-Based Model for Trailing-Edge Flap Loads in Preliminary Aircraft Design

Accurately predicting the forces and moments acting on trailing-edge devices under different flight conditions is a critical aspect in the design of the kinematics and actuation for high-lift or variable-camber applications. However, accurate modeling without elaborated computational fluid dynamics (CFD) analyses in the subsonic and transonic regimes needs a sophisticated model. Thus, the objective of this paper is to create such a model that accurately predicts the forces and moments acting on flaps during different flight conditions while remaining applicable to the preliminary aircraft design. The target values in this model are the three-dimensional (3D) forces and moments on the flap, which were obtained through 3D CFD simulations. The chosen input values required for the model include two-dimensional airfoil data, and wing geometry data for three different aircraft types: short-, medium-, and longrange, including a high-aspect-ratio configuration. Among several potential approaches, a neural network was deemed to be the most promising for predicting the target values. The neural network was used as a regression tool to accelerate the model development process in the preliminary aircraft design. Consequently, multiple studies were conducted on how the setup of the neural network, including the number of neurons, activation functions, and initialization, influences the results. The results reveal that the developed neural network accurately predicts the flap forces and moments with a mean deviation of under 2% for the vertical force Fz and the lateral force Fx and under 4% for the moment My. © 2024 by Ralph Stephan, Cedric Heyen, Eike Stumpf (Institute of Aerospace Systems, RWTH Aachen University), and Johannes Ruhland, Christian Breitsamter (Chair of Aerodynamics and Fluid Mechanics, Technical University of Munich).     «

Accurately predicting the forces and moments acting on trailing-edge devices under different flight conditions is a critical aspect in the design of the kinematics and actuation for high-lift or variable-camber applications. However, accurate modeling without elaborated computational fluid dynamics (CFD) analyses in the subsonic and transonic regimes needs a sophisticated model. Thus, the objective of this paper is to create such a model that accurately predicts the forces and moments acting on...     »

Funding text The funding of this investigation within the LUFO VI-2 project H2Avia (FKZ: 20E2106B) by the German Federal Ministry for Economic Affairs and Climate Action (BMWK) is gratefully acknowledged. The data used in this publication was managed using the research data management platform Coscine with storage space granted by the Research Data Storage (RDS) of the DFG and Ministry of Culture and Science of the State of North Rhine-Westphalia (DFG: INST222/1261-1 and MWK: 214-4.06.05.08\u2014139057). The authors want to thank ANSYS for providing the flow simulation software. Moreover, the authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. for funding this project by providing computing time on the Gauss Centre of Supercomputing (GCS) Supercomputer SuperMUC-NG at Leibniz Supercomputing Center.     «

Funding text The funding of this investigation within the LUFO VI-2 project H2Avia (FKZ: 20E2106B) by the German Federal Ministry for Economic Affairs and Climate Action (BMWK) is gratefully acknowledged. The data used in this publication was managed using the research data management platform Coscine with storage space granted by the Research Data Storage (RDS) of the DFG and Ministry of Culture and Science of the State of North Rhine-Westphalia (DFG: INST222/1261-1 and MWK: 214-4.06.05.08\u20...     »