LMS Test.Lab contributes to improved flutter analysis

  • 15-Sep-2010 06:36 EDT

A380 MSN001 was equipped with more than100 measurement points uniformly distributed all over the primary aircraft structure.

Aeroelasticity, the interaction between inertial, elastic, and aerodynamic forces, plays a vital role in aircraft design. And as soon as you add four enormous engines and a significant increase in size and flexibility, it is not surprising that aeroelastic behavior evolves, becoming more and more complex.

Along with the aircraft characteristics, modal identification methods used during flutter testing have evolved to ensure correct parameter identification. Frequencies and damping value estimations have to be as accurate as possible to define the aircraft fluttering margins used during those first mission-critical in-flight test campaigns.

Flutter testing can be broken into three segments: real time, near real time, and offline. In-flight real-time test campaigns acquire live data during the test flight mostly as a safety check to continue the flight envelope. Near real-time testing focuses on rapid modal estimation to determine the overall safety of the flight and the flutter test program. Offline deals with the finer analysis of the recorded flight data and final report production.

The Airbus flutter team in Toulouse, France, faced challenges working on the Airbus A380 campaign, but there were issues it had faced before with the Airbus A340 flutter campaign: high modal density and similar mode shapes, both placed in a low narrow frequency band.

In terms of modal identification, these new precise requirements called for a better-defined and better-equipped testing installation. This meant digging a bit to find the right kind of process. Measured data needed to be recorded at enough locations with high enough quality to improve power spectra and transfer function estimates and avoid spatial aliasing when working out aircraft deformed shapes. This required some innovative thinking and process validation in regard to current techniques.

Since 2001, Airbus France and LMS International have been cooperating in regard to several EUREKA projects called “FLITE” (Flight Test Easy). An intergovernmental initiative to support market-oriented European R&D, the EUREKA FLITE projects focus on bringing new and powerful tools to structural engineers and aircraft designers, improving the quality and usefulness of data gathered during flight testing.

In late 2007, LMS and Airbus agreed to start a project to evaluate LMS PolyMAX, an integrated part of the LMS Test.Lab Structures suite as a key solution to achieve high-quality offline in-flight data processing for flutter testing.

In the past, the Flight Test Departments of Airbus France performed data analysis using its in-house near real-time analysis package and transferred the results together with the raw data to Airbus Germany where the numerical flutter predictions were correlated with actual flight tests. However, Airbus France felt the need to carry out some more in-depth data processing, so that it could transfer more complete results to Germany.

“Clearly, we needed a solution that would improve the alignment between online in-flight analysis occurring in Toulouse and the post-processing completed in the design center in Airbus Germany. At this stage, we are very pleased with the results. LMS Test.Lab is able to provide us with the right type of results,” said Jean Roubertier, flight test department aeroelasticity expert at Airbus.

Considering that the 525-seat Airbus A380 is the largest commercial passenger aircraft in the skies today, it is not surprising that simply due to its sheer size, the acquired in-flight testing data is record-breaking as well.

“With more than 100 sensors, this was one of the largest setups for an in-flight flutter test campaign I have ever seen. Also the amount of tests under different flight conditions is impressive. The resulting database is immense, and efficient processing and report generation capabilities are required,” said Bart Peeters, LMS Research Project Manager.

The Airbus Flutter team in Toulouse performed a variety of excitations including control surfaces sine sweeps and pulses. Pulses are currently used to ensure crew and aircraft safety, whereas sweeps are used to work out more accurate results allowing to update theoretical FE models. By integrating pulses into the process, flutter flights duration time has been considerably reduced.

The basic concept behind the project was to compare classical experimental modal analysis (EMA) with LMS Test.Lab’s Operational Modal Analysis (OMA) technique. In classical EMA, the control surface excitation and aircraft response signals are converted to Frequency Response Functions (FRFs). During the actual flight, other excitation sources, such as turbulence are present. Sometimes, this results in noisy FRFs. For example, an aircraft tail response sensor receives a rather limited contribution from the wing excitation. Therefore, the idea arose to neglect the excitation signal and apply OMA to the aircraft acceleration signals.

“We actually achieved better results using OMA than with classical EMA. We found more modes. The synthesis was better with higher correlation and fewer errors. And the in-flight mode shapes looked much nicer,” said Miquel Angel Oliver Escandell. “This was thanks to the amount of sensors we used and the OMA capabilities of LMS Test.Lab.”

During the comparison testing, the flutter team at Airbus used LMS PolyMAX during sweep excitations of the aircraft. Results, using an exponential window of 5% appear to be good, supplying high synthesis correlations (98% using just two references) and clear stabilization diagrams. “We’ve been extremely impressed by the flutter analysis results and the way that the LMS Test.Lab software can handle the challenges of processing the immense amount of Airbus A380 in-flight data during the off-line analysis,” said Jean Roubertier.

Jennifer Schlegel, Senior Editor, LMS International, Leuven, Belgium, wrote this article for Aerospace Engineering & Manufacturing.

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