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==Motivation== |
==Motivation== |
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− | Computing responses to discrete gusts are sizing steps when designing and optimizing a new aircraft structure and geometry. Indeed, this is part of the imposed clearance certifications requested by the flight authorities. During the aircraft preliminary design phase, this clearance is done by intensive simulations, however, due to the involved |
+ | Computing responses to discrete gusts are sizing steps when designing and optimizing a new aircraft structure and geometry. Indeed, this is part of the imposed clearance certifications requested by the flight authorities. During the aircraft preliminary design phase, this clearance is done by intensive simulations, however, due to the involved model's complexity, these latter are time-consuming and imply an important computational burden. Moreover, these simulations are involved at different steps of the aircraft optimization process, e.g., by aeroelastic, flight and control engineers. In <ref name=PousstVassal2018>C. Poussot-Vassal, D. Quero, and P. Vuillemin, "Data-driven approximation of a high fidelity gust-oriented flexible aircraft dynamical model", in Proceedings of the 9th Vienna International Conference on Mathematical Modelling (MATHMOD), Vienna, Austria, 2018.</ref>, a systematic way to fasten the gust simulation step and simplify the analysis by mean of data-driven model approximation in the Loewner framework is proposed, as well as a description of this model. |
− | Flexible aircraft models are very challenging the civil aeronautics due to their lighter structure. Models are largely used to optimize and analyze critical phenomena in the pre-design phase. Such model can e.g. be used to monitor some dimensioning critical stress of the aircraft in response to discrete and continuous gust situations. |
+ | Flexible aircraft models are very challenging the civil aeronautics due to their lighter structure. Models are largely used to optimize and analyze critical phenomena in the pre-design phase. Such model can, e.g., be used to monitor some dimensioning critical stress of the aircraft in response to discrete and continuous gust situations. |
==Origin== |
==Origin== |
Revision as of 21:26, 17 March 2018
Note: This page has not been verified by our editors.
Description
This benchmark contains a set of frequency-domain data
representing the output responses (accelerations and moments at different coordinates of a flexible aircraft wings and tail) in response to an input signal (gust disturbance) , evaluated at varying frequencies
[rad/s], for
.
Motivation
Computing responses to discrete gusts are sizing steps when designing and optimizing a new aircraft structure and geometry. Indeed, this is part of the imposed clearance certifications requested by the flight authorities. During the aircraft preliminary design phase, this clearance is done by intensive simulations, however, due to the involved model's complexity, these latter are time-consuming and imply an important computational burden. Moreover, these simulations are involved at different steps of the aircraft optimization process, e.g., by aeroelastic, flight and control engineers. In [1], a systematic way to fasten the gust simulation step and simplify the analysis by mean of data-driven model approximation in the Loewner framework is proposed, as well as a description of this model.
Flexible aircraft models are very challenging the civil aeronautics due to their lighter structure. Models are largely used to optimize and analyze critical phenomena in the pre-design phase. Such model can, e.g., be used to monitor some dimensioning critical stress of the aircraft in response to discrete and continuous gust situations.
Origin
ONERA - The French Aerospace Lab.
Data
The data is contained in the FlexibleAircraft.zip (585KB) which holds two files.
The data.mat files contains :
- W : the frequency values in rad/s (real
vector).
- H : transfer function matrix evaluation at different output measurements points of the aircraft (complex
matrix).
The transfer function matrix H represents the transfer from the
- gust input
to the 92 measurements gathering from
- 1--44: the local aerodynamic lift on the aerodynamic strips.
- 45--88: the local aerodynamic pitch moment on the aerodynamic strips.
- 89--92: the four generalized coordinates derivative (heave and pitch derivatives) and the first two flexible modes.
The startData.m file loads and plots the data for illustration.
References
- ↑ C. Poussot-Vassal, D. Quero, and P. Vuillemin, "Data-driven approximation of a high fidelity gust-oriented flexible aircraft dynamical model", in Proceedings of the 9th Vienna International Conference on Mathematical Modelling (MATHMOD), Vienna, Austria, 2018.