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Record W2273875263

Aero-servo-viscoelasticity theory: lifting surfaces, plates, velocity transients, flutter, and instability

2011· article· en· W2273875263 on OpenAlexfundno aff
Craig G. Merrett

Bibliographic record

VenueIllinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · 2011
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlutterViscoelasticityInstabilityControl theory (sociology)ServoMechanicsPhysicsStructural engineeringAcousticsMathematicsComputer scienceEngineeringMechanical engineeringAerodynamicsArtificial intelligenceThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

Modern flight vehicles are fabricated from composite materials resulting in flexible structures that behave differently from the more traditional elastic metal structures. Composite materials offer a number of advantages compared to metals, such as improved strength to mass ratio, and intentional material property anisotropy. Flexible aircraft structures date from the Wright brothers' first aircraft with fabric covered wooden frames. The flexibility of the structure was used to warp the lifting surface for flight control, a concept that has reappeared as aircraft morphing. These early structures occasionally exhibited undesirable characteristics during flight such as interactions between the empennage and the aft fuselage, or control problems with the elevators. The research to discover the cause and correction of these undesirable characteristics formed the first foray into the field of aeroelasticity.\n\nAeroelasticity is the intersection and interaction between aerodynamics, elasticity, and inertia or dynamics. Aeroelasticity is well suited for metal aircraft, but requires expansion to improve its applicability to composite vehicles. The first is a change from elasticity to viscoelasticity to more accurately capture the solid mechanics of the composite material. The second change is to include control systems. While the inclusion of control systems in aeroelasticity lead to aero-servo-elasticity, more control possibilities exist for a viscoelastic composite material. As an example, during the lay-up of carbon-epoxy plies, piezoelectric control patches are inserted between different plies to give a variety of control options. The expanded field is called aero-servo-viscoelasticity.\n\nThe phenomena of interest in aero-servo-viscoelasticity are best classified according to the type of structure considered, either a lifting surface or a panel, and the type of dynamic stability present. For both types of structures, the governing equations are integral-partial differential equations. The spatial component of the governing equations is eliminated using a series expansion of basis functions and by applying Galerkin's method. The number of terms in the series expansion affects the convergence of the spatial component, and convergence is best determined by the von Koch rules that previously appeared for column buckling problems. After elimination of the spatial component, an ordinary integral-differential equation in time remains.\n\nThe dynamic stability of elastic and viscoelastic problems is assessed using the determinant of the governing system of equations and the time component of the solution in the form exp (lambda t). The determinant is in terms of lambda where the values of lambda are the latent roots of the aero-servo-viscoelastic system. The real component of lambda dictates the stability of the system. If all the real components are negative, the system is stable. If at least one real component is zero and all others are negative, the system is neutrally stable. If one or more real components are positive, the system is unstable. In aero-servo-viscoelasticity, the neutrally stable condition is termed flutter. For an aero-servo-viscoelastic lifting surface, the unstable condition is historically termed torsional divergence.\n\nThe more general aero-servo-viscoelastic theory has produced a number of important results, enumerated in the following list:\n\n1. Subsonic panel flutter can occur before panel instability. This result overturned a long held assumption in aeroelasticity, and was produced by the novel application of the von Koch rules for convergence. Further, experimental results from the 1950s by the Air Force were retrieved to provide additional proof.\n2. An expanded definition for flutter of a lifting surface. The legacy definition is that flutter is the first occurrence of simple harmonic motion of a structure, and the flight velocity at which this motion occurs is taken as the flutter speed. The expanded definition indicates that the flutter condition should be taken when simple harmonic motion occurs and certain additional velocity derivatives are satisfied.\n3. The viscoelastic material behavior imposes a flutter time indicating that the presence of flutter should be verified for the entire life time of a flight vehicle.\n4. An expanded definition for instability of a lifting surface or panel. Traditionally, instability is treated as a static phenomenon. The static case is only a limiting case of dynamic instability for a viscoelastic structure. Instability occurs when a particular combination of flight velocity and time are reached leading to growing displacements of the structure.\n5. The inclusion of flight velocity transients that occur during maneuvers. Two- and three-dimensional unsteady incompressible and compressible aerodynamics were reformulated for a time dependent velocity. The inclusion of flight velocity transients does affect the flutter and instability conditions for a lifting surface and a panel.\n\nThe applications of aero-servo-viscoelasticity are to aircraft design, wind turbine blades, submarine's stealth coatings and hulls, and land transportation to name a few examples. One caveat regarding this field of research is that general predictions for an application are not always possible as the stability of a structure depends on the phase relations between the various parameters such as mass, stiffness, damping, and the aerodynamic loads. The viscoelastic material parameters in particular alter the system parameters in directions that are difficult to predict. The inclusion of servo controls permits an additional design factor and can improve the performance of a structure beyond the native performance; however over-control is possible so a maximum limit to useful control does exist. Lastly, the number of material and control parameters present in aero-servo-viscoelasticity are amenable to optimization protocols to produce the optimal structure for a given mission.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.186
Teacher spread0.168 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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
Published2011
Admission routes1
Has abstractyes

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