Stability and Control Investigations in Early Stages of Aircraft Design

This paper provides an overview of current activities of DLR (German Aerospace Center) with respect to stability and control investigations in the context of early stages of aircraft design. For this purpose, DLR follows an interdisciplinary and multi-level design approach. Using an integration framework in combination with a central data exchange format, largely automated process chains are set up that combine calculation and simulation capabilities of the multitude of disciplines required in early aircraft design. Rather than using empirical relations and assumptions based on experience, the underlying methods applied by the tools are mainly based on physical model representations. The major aim of this design approach is to generate all relevant data needed for stability and control investigations, including aerodynamic damping derivatives and to assemble them within a flight dynamics model. Not only does this approach allow for an early consideration of stability and control characteristics, but it also respects interdisciplinary effects and enables automated design changes. This paper describes the infrastructure used for setting up the described process. It presents disciplinary tools used to calculate engine performance maps, calculate aerodynamic performance maps and structural properties, generate flight dynamics models with associated control laws and to assess aircraft handling qualities. Furthermore, this paper provides application examples of early stability and control considerations, using integrated interdisciplinary process chains. This comprises a handling qualities assessment under uncertainty considerations and vertical tailplane sizing for a blended wing body. In addition, engine and split flap sizing processes for an unmanned combat aerial vehicle are shown. The interdisciplinary design approach presented here, serves to find a well justified early configuration and reduces the risk of later design changes.

[1]  Richard Becker,et al.  Preliminary Engine Design for the MULDICON Configuration , 2018 .

[2]  Jan Albert Mulder,et al.  Robust Flight Control Using Incremental Nonlinear Dynamic Inversion and Angular Acceleration Prediction , 2010 .

[3]  Gertjan Looye An Integrated Approach to Aircraft Modelling and Flight Control Law Design , 2008 .

[4]  Christian Willberg,et al.  Automated model generation and sizing of aircraft structures , 2016 .

[5]  Gabriel Pinho Chiozzotto,et al.  Wing weight estimation in conceptual design: a method for strut-braced wings considering static aeroelastic effects , 2016 .

[6]  Stefan Görtz,et al.  Hierarchical Kriging Model for Variable-Fidelity Surrogate Modeling , 2012 .

[7]  Carsten M. Liersch,et al.  Conceptual Design of a 53deg Swept Flying Wing UCAV Configuration , 2018 .

[8]  Gertjan Looye,et al.  Integration and application of a tool chain for environmental analysis of aircraft flight trajectories , 2009 .

[9]  Ilan Kroo,et al.  Aircraft design optimization with dynamic performance constraints , 1990 .

[10]  Gertjan Looye,et al.  Design and Flight Testing of Incremental Nonlinear Dynamic Inversion-based Control Laws for a Passenger Aircraft , 2018 .

[11]  Carsten M. Liersch,et al.  A Fast Aerodynamic Tool for Preliminary Aircraft Design , 2008 .

[12]  Gabriel Pinho Chiozzotto,et al.  Initial Weight Estimate of Advanced Transport Aircraft Concepts Considering Aeroelastic Effects , 2017 .

[13]  Alexander I. J. Forrester,et al.  Multi-fidelity optimization via surrogate modelling , 2007, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[14]  Stephen Morris Integrated aerodynamics and control system design for tailless aircraft , 1992 .

[15]  Carsten M. Liersch,et al.  On the Design of a Strut-Braced Wing Configuration in a Collaborative Design Environment , 2017 .

[16]  Christian B Allen,et al.  Comparison of Adaptive Sampling Methods for Generation of Surrogate Aerodynamic Models , 2013 .

[17]  Sebastien Guerin,et al.  The Parametric Aircraft Noise Analysis Module - status overview and recent applications , 2011 .

[18]  David J. J. Toal,et al.  Some considerations regarding the use of multi-fidelity Kriging in the construction of surrogate models , 2015 .

[19]  Gertjan Looye,et al.  Flyover Noise Measurements of a Spiraling Noise Abatement Approach Procedure , 2011 .

[20]  Kerstin Claudie Huber,et al.  Conceptual Design and Aerodynamic Analyses of a Generic UCAV Configuration , 2014 .

[21]  Kenji Takeda,et al.  Multifidelity surrogate modeling of experimental and computational aerodynamic data sets , 2011 .

[22]  P. Sagaut,et al.  Building Efficient Response Surfaces of Aerodynamic Functions with Kriging and Cokriging , 2008 .

[23]  Carl H. Gerhold,et al.  Inlet Noise Reduction by Shielding for the Blended-Wing-Body Airplane , 1999 .

[24]  Antonius A. Lambregts TECS Generalized Airplane Control System Design – An Update , 2013 .

[25]  Jana Ehlers Flying Qualities Analysis of CPACS Based Aircraft Models- HAREM V2.0 - , 2013 .

[26]  J. Preissner,et al.  Special problems in applying the physical optics method for backscatter computations of complicated objects , 1988 .

[27]  Gertjan Looye,et al.  Design, Implementation and Flight-Tests of Incremental Nonlinear Flight Control Methods , 2018 .

[28]  William H. Mason,et al.  Analytic models for technology integration in aircraft design , 1990 .

[29]  Wr Graham,et al.  The potential of future aircraft technology for noise and pollutant emissions reduction , 2014 .