1,720,965 research outputs found
Finite element structural updating using frequency response functions
No full textIn this paper, a sensitivity-based updating method is proposed to
reduce the discrepancies between the finite element (F.E.) model
representation of a structure and its experimental counterpart thus
allowing engineers the use of such numerical representation for
structural modification prediction, dynamic model synthesis,
aeroelastic analysis, and system qualification. The proposed method iteratively minimizes a residual vector of correlation functions, defined on the Frequency Response Functions (FRF), in order to find the missmodeled regions of the F.E. model through the identification of the unknown vector of the updating parameters. The approach provides an enhanced formulation of the Bayesian-based least-square solution technique and a proper numerical relaxation method allowing thus the updated F.E. model to go beyond the dynamic equivalence with the experimental findings, that is the increase in the correlation between the corresponding modal parameters, by identifying updating parameters that well represent the physical properties of the structure under investigation. A formulation of the weighting matrices that takes into account the uncertainty of the experimental data and the use of the L-curve criterion to numerically relax the solution are presented in the paper. Results
from both numerical analyses and experimental investigations are
reported to validate the proposed approach and show its robustness
Frequency-domain mathematical model of the smart spring device for vibration reduction
No full textIn this paper, the capability of a semi-active device for vibration control, named Smart Spring, is analytically investigated. Such a device allows to actively control vibration by modulating the structural properties, such as the mass, stiffness, or damping, of a system, through a piezoceramic actuator. The analytical study of the Smart Spring is performed by developing its mathematical model in the frequency domain, in order to evaluate the response of the system in terms of its harmonic components. Furthermore, an open-loop control law for the modulation of the system stiffness is introduced. It is shown that the displacement solution depends on three dimensionless parameters, representing both structural and control properties of the system, that can be opportunely chosen to reduce the response, then vibration
Finite element structural updating using FRFs
No full textIn the field of the structural dynamics the accuracy of the finite-element model of a structure can be verified via experimental modal analysis. The discrepancies between the two models can be reduced using structural updating techniques. In this paper a sensitivity-based updating method is considered. This method iteratively minimizes a residual vector of correlation functions, defined on the Frequency Response Functions (FRFs), in order to find the unknown vector of the updating parameters. The solution generally relies on a least-square Bayesian technique that, in turn, requires the use of weighting matrices to reduce the effects of noisy data. The aim of the paper is the enhancement of a solution technique by providing a formulation for the definition of the weighting matrices, thus improving the overall numerical efficiency and accuracy. Both numerical analyses and experimental investigations on simple structures are carried out to validate the proposed approach
Identification of the smart spring properties from FRFs measurements
No full textThe objective of this paper is the dynamic identification of a reduced-scale helicopter
blade system that incorporates an active pitch link or smart spring for vibration control.
The identification of the Smart Spring parameters, in terms of the masses and stiffnesses
associated to its components, is carried out in the frequency domain using a developed
sensitivity-based updating method. This method, called Predictor-Corrector, iteratively
minimizes a residual vector of correlation functions, defined on the Frequency Response
Functions (FRFs), in order to obtain the unknown values of the parameters that well rep-
resent the dynamic behavior of the smart spring. In the paper the accuracy of the solution
provided by the developed technique is assessed through several numerical analyses. For
this purpose, a lumped parameter numerical model of the Smart Spring was developed
and the effects of various mass and stiffness distribution scenarios on the modal properties
of the system are presented. Due to the nonlinear dynamic behavior of the smart spring
system, a linear approximation of the system around a prescribed operative working con-
dition is considered. Finally, the developed approach is applied for the identification of the
dynamic parameters of a real smart spring system. It is shown that acceptable values of
the equivalent lumped parameters were achieved also considering experimental data such
as those recorded during a test campaign carried out at the Smart Rotor Laboratory of
the Carleton University, thus validating the identification approach
Updating of an unmanned aerial vehicle finite element model using experimental data
No full textIn this paper the finite element model of an Unmanned Aerial Vehicle is updated by using experimental data coming from a standard ground vibration test in order to improve the numerical-experimental correlation. A sensitivity-based updating methodology that iteratively minimizes a residual vector, defined on the modal parameters (e.g. natural frequencies and mode shapes), is considered to identify the unknown values of the updating parameters. The structure under investigation is the Clarkson University Golden Eagle UAV. An initial numerical model of the structure is obtained by assembling the individual components previously updated which included wings, fuselage, horizontal tail, vertical tails and tail booms. As a result the identification procedure shifts its focus on the joints between UAV elements which could not be modeled accurately in earlier investigations
Validation of an UAV F.E. Model Using Operational Data
No full textIn this paper an approach that uses the modal signature of an Unmanned Aerial Vehicle (UAV) extracted directly from the operative conditions for the validation of a finite element model is proposed. Different operational conditions of the Clarkson University Golden Eagle UAV are considered, ranging from laboratory components and UAV assembly to on-ground taxiing performed on asphalt and grass. To properly model the UAV individual subcomponents (wing, fuselage, horizontal tail, vertical tails and tail booms) have been tested. Only selected components testing are presented in this paper, to illustrate the methodology proposed for testing and FE modeling. These initial investigations are instrumental toward developing a correlated nite element model representing the global dynamic behavior of the UAV structure
Correlation and updating of an unmanned aerial vehicle finite element model
No full textIn this paper the numerical models of the structural components of an UAV are separately correlated with their experimental counterparts and then updated, in order to
improve the correlation. A sensitivity-based updating method is considered and its capabilities to identify changes of the design parameters that are physically acceptable investigated. The method iteratively minimizes a residual vector defined on the dynamic properties of the considered structure, natural frequencies and mode shapes, in order to find the unknown vector of updating parameters. The structure under investigation is the Golden Eagle UAV, designed, manufactured and operated by Clarkson University to perform a variety of scientific research flight campaigns including air-quality and wind profiling measurements. Individual components (wings, fuselage, horizontal tail, vertical tails and tail booms) have been tested, correlated and updated
Validation of a virtual shaker testing approach for improving environmental testing performance
No full textIn the field of vibration testing, the interaction between the structure being tested and the instrumentation hardware used to perform the test is a critical issue. This is particularly true when testing massive structures (e.g. satellites), because due to physical design and manufacturing limits, the dynamics of the testing facility often couples with that of the test specimen in the frequency range of interest. Therefore it is of paramount importance to improve environmental testing performances by considering the dynamic coupling between the test specimen and the instrumentation hardware and take suitable countermeasures before running the actual program. In this context, a “Virtual Shaker Approach” is developed to run a multidisciplinary simulation which closely represents the real vibration test. For these reasons, models accurately replicating the behavior of the different hardware involved in the environmental test need to be
developed and validated. Starting from these models, the Virtual Shaker approach can then be used to optimize test execution, improving controller performance and develop new methods to exploit the available experimental data
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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