1,721,012 research outputs found
Identification of the modal masses of an UAV structure in operational environment
No full textIn the framework of Operational Modal Analysis, several methods have been developed to estimate the modal parameters, that is natural frequencies, damping ratios, and mode shapes of a structure in its operative conditions. However, it is not possible to directly estimate the modal masses associated to each mode shape due to the unknown excitation. The modal masses are usually evaluated from the analysis of the change of the modal parameters by testing the structure in correspondence of two mass configurations. In this paper the efficiency and the accuracy of two procedures for the estimate of the modal masses are assessed by performing laboratory vibration tests. Vibration response data recorded during flight tests of an unmanned aerial vehicle (UAV) are used for this purpose as well as a mass changing device was developed to produce the mass variation of the structure. Results from the traditional input/output experimental modal analysis and the operational modal analysis are compared in terms of modal parameters, modal masses, and synthesized frequency response functions
OMA analysis for the identification of the damping properties of a sloshing fluid
No full textIn this paper, the modal characteristics of a sloshing fluid at different operating conditions are estimated using Operational Modal Analysis (OMA) methods. The chosen system is characterized by a plexiglass tank filled with water mimicking the fuel tank inside an aircraft wing. Specifically, the considered tests are aimed at evaluating the sensitivity of the eigen-properties of the fluid to the random excitation levels and the liquid filling levels. Such experimental investigations are carried out at the environmental test facility available at the Department of Mechanical and Aerospace Engineering of the University of Rome “La Sapienza” which provided the closed-loop control vibrations at the base of the tank. Because the chosen tank system can be considered fully uncoupled with the dynamics of the sloshing fluid, these tests can be considered as a preliminary laboratory representation of the fluid sloshing inside an actual aircraft wing, thus contributing to the formation of the experimental database for the European funded project SLOshing Wing Dynamics (SLOWD)
A data-driven approach for rapid detection of aeroelastic modes from flutter flight test based on limited sensor measurements
No full textFlutter flight test involves the evaluation of the airframe’s aeroelastic stability by applying artificial excitation on the aircraft lifting surfaces. The subsequent responses are captured and analyzed to extract the frequencies and damping characteristics of the system. However, noise contamination, turbulence, non-optimal excitation of modes, and sensor malfunction in one or more sensors make it time-consuming and corrupt the extraction process. In order to expedite the process of identifying and analyzing aeroelastic modes, this study implements a time-delay embedded Dynamic Mode Decomposition technique. This approach is complemented by Robust Principal Component Analysis methodology, and a sparsity promoting criterion which enables the automatic and optimal selection of sparse modes. The anonymized flutter flight test data, provided by the fifth author of this research paper, is utilized in this implementation. The methodology assumes no knowledge of the input excitation, only deals with the responses captured by accelerometer channels, and rapidly identifies the aeroelastic modes. By incorporating a compressed sensing algorithm, the methodology gains the ability to identify aeroelastic modes, even when the number of available sensors is limited. This augmentation greatly enhances the methodology’s robustness and effectiveness, making it an excellent choice for real-time implementation during flutter test campaigns
Some results of GARTEUR Action Group HC-AG 19 on methods for improvement of structural dynamic finite element models
No full textThe issue of vibration in helicopters is of major concern to operators. This requires close attention to the vehicle dynamics. The ability to faithfully simulate and optimise vehicle response, structural modifications, vehicle updates, the addition of stores and equipment is the key to producing a low vibration helicopter. GARTEUR Action Group, HC-AG 14, concluded that helicopter dynamic models are still deficient in their capability to predict airframe vibration. The AG looked at the methods for improving the model correlation with modal test data along with the suitability of existing shake test methods. The helicopter structure tested in AG14 was suspended in the laboratory. However, this is not the operational environment where there are very significant mass, inertia and gyroscopic effects from the rotor systems. Nowadays, modal analysis consists of two principal approaches: experimental modal analysis (EMA) and operational modal analysis (OMA). The EMA evaluates the modal parameters by considering that the excitation and the response of the system are both measurable. The OMA evaluates the modal parameters using only the measured response. The lack of knowledge of the input is replaced by the assumption that the input is a distributed stochastic load, constant in a broad frequency band, e.g. white noise, and uncorrected in space. This hypothesis, nevertheless, is restrictive in rotorcraft applications, because in these cases the load is characterized by harmonic components, i.e. deterministic signals, originating from the rotating parts. A new action group HC-AG19 was formed to study the benefit of using in-flight dynamic data for improving finite element models. Methodologies were assessed to evaluate vibration measurements from flight tests. The objective is to extract modal parameters and demonstrate that the dynamic model can be updated using this data. This paper presents one of the approaches developed by the University of Rome "La Sapienza"
Using neural networks for F.E. model updating of structures in operational conditions
No full textIn this paper, a finite element model updating method based on neural networks is presented. The main objective of the paper is to identify the dynamic properties of a structure from response data recorded during operating conditions, extending the use of results from operational modal analysis to the neural networks-based updating methodologies. The neural networks used in this study have a feed-forward architecture and their inputs are the modal parameters, that is natural frequencies, damping ratios, and mode shapes of a structure in its operative conditions, whereas their outputs are the physical properties of the considered structure. Typically, the first step of neural networks is their training and it will be shown that trained neural networks are successful when simulated cases are considered but they have some limits when experimental data are used. For this reason an algorithm based on not-trained neural networks has been developed. Both numerical and experimental analyses carried out on simple structures will be presented to demonstrate the accuracy of the proposed updating approach
Closed-loop control of the smart spring. An analytical solution for the actuator model
No full textThe analytical modeling of the Smart Spring actuator for vibration reduction of periodically excited systems is performed. The mathematical model is developed in the frequency domain using the harmonic balance method, assuming that the solution is harmonic on the exciting frequency. Both the fixed-base and base-excited configurations are studied. It is shown that the Smart Spring transmissibility at the target frequency depends on only three dimensionless parameters associated with the stiffness modulation characteristics of the device for the fixed-base configuration and five dimensionless parameters for the base-excited configuration. The fundamental values for the Smart Spring closed-loop control are discussed
Free vibrations of ultrathin deployable booms fabricated with nano-modified epoxy matrix
No full textUltrathin deployable boom structures are investigated to increase the mission capacity of small spacecrafts within their limited package volume. The successful integration of boom technology would allow small satellites to perform missions that are commonly reserved for larger and more complex space platforms. The boom is directly exposed to the space environments, which produces detrimental effects of the overall properties of the composite structure. On the other hand, the dynamic characterization of boom structures during the deployment phase and in deployed configuration is of primary importance to understand the factors that influence the operative behavior of the entire satellite. Polymer-based composites are a class of materials that have gained more attention for damping applications. The introduction of nanoparticles to the polymer matrix can add large benefits. Recent studies showed that nanocomposites possess a high potential for damping applications. In addition, certain nanoparticles, such as nanosilica, can enhance the resistance of composite materials to the space environments. In this work, we aim to investigate the effects of nanoparticles on the free vibrations of boom structures. In the first part of this work, we fabricated prototypes of 1 m-long self-deployable ultrathin booms with V cross-section geometry using 1K carbon fiber reinforcement and epoxy resin modified with nanoparticles. In particular, we used nanosilica and graphene oxide at 1 wt% and 2 wt%. The manufacturing process was studied and optimized in order to fabricate reproducible and reliable structures. Then, in order to investigate the effects of the nanoparticles on the vibrational response of the nanocomposite booms, we performed modal testing by impulsive excitation method. Natural frequencies and modal shapes were determined for each nanocomposite boom and compared with those of the equivalent fiber reinforced composite boom with unmodified epoxy resin. Further, natural frequency analysis of the boom structures was performed by finite element method (FEM) in order to deep understand the role of nanoparticles on dynamic behavior. A multiscale approach was used to determine the mechanical properties of nano-modified epoxy matrix and those of the lamina. These data were applied as input for the structural analysis
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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