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Record W7038488016

INVESTIGATION ON SMART SENSORS TO PREDICT FLUTTER AND AEROLASTIC RESPONSE

2009· other· en· W7038488016 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2009
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAeroelasticityFlutterAerodynamicsAirfoilTransonicWind tunnelVibrationSupersonic speed
DOInot available

Abstract

fetched live from OpenAlex

This research is devoted to the identification of non-linear aeroelastic systems in real time. The proposed studies will be related to develop new sensory techniques to identify aeroelastic modes and unsteady aerodynamics in fixed and rotary wings. These studies are important because the interaction of the vibration natural modes of the aircraft structure with the unsteady aerodynamic loading may become unstable under certain flight conditions, leading to the flutter phenomenon. Moreover, in a less severe scenario, these loads generate high levels of aircraft forced vibration that cause passenger discomfort and lead to structural fatigue and even failure. All these studies, although ultimately directed to helicopter blades, will be initially conducted with fixed-wing configurations, and will include both numerical simulations and experimental work conducted in still air and wind tunnel. From the project originality point-of-view, it is well known that the main line of research on aeroelasticity today is associated with non-linear phenomena. In the low speed range, the non-linearity is often associated with the structure alone (free play of control surfaces in most cases). However, in the high-speed transonic regime, non-linearities are also generated from the aerodynamics unsteadiness, and these are normally associated with localized shocks on supercritical airfoil configurations. There is no efficient method that can be used in the industry today to deal analytically with non-linear phenomena. The development of reliable and computationally efficient analytical methods is of fundamental importance for the industry. However, this development can only be done with the existence of carefully controlled wind tunnel tests to serve as a source of comparison data. As wind tunnel tests are very expensive, reliable experimental data must be acquired in the shortest period of time. The objective of this research is, therefore, to develop new sensory techniques based on smart materials to maximize the efficiency of wind tunnel tests to produce accurate data pertinent to aeroelasticity. In fact, Carleton University is engaged to pursue with several international partners a collaborative project on an experimental investigation to determine the aeroelastic flutter and forced vibration characteristics of a model of a typical commuter aircraft configuration using the National Research Council Canada (NRCC) Institute for Aerospace Research 5-foot square test section of their blow-down wind tunnel facility. The main investigation will be performed in the high-speed transonic regime where non-linear aerodynamic behavior occurs. Notwithstanding the panned NRCC tests, this research will be complemented with low-speed wind tunnel tests on a full-aircraft configuration to be carried out by partners at CTA (Centro Tecnico Aeroespacial) in Brazil to investigate the effect of structural non-linearities on flutter characteristics. This collaborative project is seen of strategic interest in terms of advancing the general knowledge as well as the partners' expertise in a research area that is of great and timely interest for the aerospace industry. It is further proposed that "La Sapienza" becomes a partner in this international research effort. One of the proposed wind tunnel models is a reflection plane wing-body model where a fairing allows a smooth transition between the wing and the fuselage. The model includes a swept-tapered wing, which supports a nacelle and a jet engine modeled as a hollow cylinder. Under terms of this collaboration, the wind tunnel model will be designed and fabricated at Carleton University. The model will be tested for flutter in the NRCC blow-down wind tunnel in the transonic regime for different pitch angles, Reynolds and Mach numbers. A mass damper ("flutter stopper") will be incorporated inside the wing structure to prevent flutter bifurcation and model accidental destruction. This is usually achieved using a mechanical device that is traditionally a small weight that is suddenly moved inside the structure by the release of a spring. The change in the wing mass distribution provided by the device stabilizes the onset of flutter. The wing structure deformation is traditionally measured using two mini-accelerometers mounted near the wing tip in the chord-wise direction. The accelerometers pick up the bending and torsion deformations of the wing, as the sum and difference of the individual signals. However, accelerometers are localized sensors that do not bring enough information to a generalized structural phenomenon such as flutter and aeroelastic response. Hence, piezoelectric fiber (Active Fiber Composite - AFC) sensors will be suitably embedded in the wing to measure its generalized modal deformations as well. This will be one of the main and novel aspects of this research project. These embedded geometric sensors are expected to allow for the first time a better determination of the flutter characteristics, as (distributed) modal sensors can identify the aeroelastic phenomena much more precisely in terms of the "modal participation". This work will be an extension of the studies on AFC-related geometric modal sensors developed in a present collaboration involving EMPA, ETH in Switzerland and Carleton University. It is suggested that Prof. Nitzsche and Prof. Coppotelli will join research efforts during Prof. Nitzsche's proposed tenure at "La Sapienza" to perform feasibility studies aiming to develop advanced smart sensors using AFC-related techniques for aeroelastic modal identification in the transonic regime for immediate application in the programmed wind tunnel tests, including the feasibility of measuring unsteady aerodynamic loads at certain wing cross-sections. In summary, the objective of the planned research is the development of analytical techniques to identify fundamental aspects of aeroelastic phenomena from AFC-generated signals. In this context, advanced studies, performed at "La Sapienza", on the identification of dynamic systems vibrating in the actual operating conditions represent an excellent starting point for the proposed project. This research is seen of great value for the organizations involved, not only for its novelty that will surely allow the publication of a number of joint papers, but also for its special and timely relevance in face of the planned wind tunnel tests, the potential industrial applications, and the basis of a established long-term collaboration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.292
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2009
Admission routes1
Has abstractyes

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Same venueIRIS Research product catalog (Sapienza University of Rome)French-language works237,207