1,721,021 research outputs found
Energy sharing between nonlinear structures by entropy modelling
No full textEntropy and therefore the second principal of thermodynamics has been proposed originally from the Sapienza group to complete energy methods in vibroacoustics. The idea is to add entropy beside energy in making models for complex mechanical systems, especially in the field of high frequency vibrations. In fact, energy is naturally involved in the first law of thermodynamics (the energy conservation principle), but it does not involve any flow directions and "energy flow speed" information, governed indeed by inequality principles. However, this information are crucial. The eminent fact emerging from this method is that it applies indifferently to linear as well as to nonlinear systems. This element is surprising, but inherent with the use of the entropy concept in tandem with energy. Based on this model, the authors consider applications to real complex structures. To this aim two structural systems are investigated: coupled nonlinear beams and plates. The new horizon opened by the entropy-energy method is emphasized by the presented results
Comparison of Input/Output and Output/Only modal parameter estimation techniques on a simple mechanical structure
No full textIn this paper the performance of several modal parameter estimation techniques is compared by considering simple mechanical structures as benchmarks. Specifically, among Input/Output techniques, a frequency domain poly-reference method is considered. Among Output/Only techniques, Frequency Domain Decomposition and poly-reference least square complex frequency-domain techniques are used. In order to characterise the performance of the examined methods, one of the important features of the benchmark structures is whether they present close and/or multiple mode
Thermodynamics of high frequency nonlinear vibrations
No full textIn the field of vibrations of complex structures, energy methods like SEA and a series of mid-frequency methods, represent an important resource for computational analysis. All these methods are based in general on a linear formulation of the elastic problem. However, when nonlinearities are present, for example related to clearance or stiffening of joints, these methods, in principle, cannot be applied. This paper, on the basis of a theory presented recently by one of the authors, proposes a foundation of a new energy method able to deal with nonlinearities when studying the energy exchange between subsystems. The idea relies on the concept of a thermodynamic vibroacoustic temperature, that can be directly defined when introducing the entropy of a vibrating structure. The theory is introduced in general, and examples of calculation of the power flow between nonlinear resonators are presented introducing stiffening and clearences for systems with many degrees of freedom
Uncertainty propagation in Statistical Energy Analysis using Design of Experiments
No full textA limit of Statistical Energy Analysis (SEA) is that of providing only the mean values of the mechanical energy of a vibrating system. Uncertainties of the SEA parameters (coupling loss factors, internal loss factors, and injected powers) depend on uncertainties in the physical properties of the considered mechanical system (Young modulus, material density, geometry). In this paper, uncertainty solution in SEA is investigated using a Design of Experiment (DoE) approach. Numerical results are derived using a benchmark structure made by interconnected aluminum plates. The effectiveness of the proposed approach is evaluated by comparing it with a Monte Carlo simulation
Modal identification of machines in operating conditions
No full textIn this paper the performance of several modal parameter estimation techniques is compared by considering a simple mechanical structure as test bed. Specifically, among Input/Output (I/O) techniques, a frequency domain poly-reference method is considered. Among Operational Modal Analysis (OMA), Frequency Domain Decomposition and poly-reference least square complex frequency-domain techniques are used. I/O technique and OMA are performed using the measurements due to a random shaker excitation. In the first case the responses and the input force are used to calculate the FRFs. On the contrary, OMA is performed by using only the set of measured responses, by supposing unknown the input force. Note that the OMA hypothesis of a random distributed force is not observed. In order to characterise the performance of the examined methods, the results obtained by the OMA are compared to the result of the I/O technique
Medium-high frequency optimization of a passenger cabin mock-up using response surface models of SEA coupling loss factors
No full textStatistical Energy Analysis (SEA)is the most suitable technique to solve medium-high frequency dynamic optimisation problems. The subsystem energies of a SEA model are controlled by (coupling) loss factors (CLF and ILF) that depend on physical parameters of the subsystems. If it is required to bring the energy of some subsystems under prescribed levels, it is proposed to proceed according to the following steps. (Here it is assumed to use commercial software for SEA: in this case explicit relations among CLFs and physical parameters are not available). In the first step, the sensitivity of subsystem energies to CLFs can be computed to recognize the most effective CLFs, i.e. those giving rise to the largest energy variations. Having selected a set of ”effective” CLFs, approximate relations between these CLFs and the relevant physical parameters can be determined after performing appropriate numerical experiments with the SEA software. In this phase Design of Experiment (DoE) can be fruifully used. Consequently an approximate relation between subsystems energies and physical parameters is available. This last relation can be used to formulate an optimisation problem in order to lower the energies of some subsystems. This technique is applied to medium-high frequency optimization of a passenger cabin mock-up
Damage diagnostic technique combining machine learning approach with a sensor swarm
Full text linkA Model-free approach is particularly valuable for Structural Health Monitoring because real structures are often too complex to be modelled accurately, requiring anyhow a large quantity of sensor data to be processed. In this context, this paper presents a machine learning technique that analyses data acquired by swarm of a sensor. The proposed algorithm uses unsupervised learning and is based on the use principal component analysis and symbolic data analysis: PCA extracts features from the acquired data and use them as a template for clustering. The algorithm is tested with numerical experiments. A truss bridge is modelled by a finite element model, and structural response is produced in healthy and several damaged scenarios. The present research shows also the importance of considering a sufficient number of measurements points along the structure, i.e. the swarm of sensors. This technology, which nowadays is easily attainable with the application of optical Fiber Bragg Grating strain sensors. The difficulties related to the early stage damage detection in complex structures can be skipped, especially when ambient, narrow band, moving loads are considered, enhancing the prediction capabilities of the proposed algorithm
Arrendament per la Setena de Culla a Pere Edo
No full text4 fl. 310 x 210 mm.Arrendament per la Setena de Culla a Pere Edo, moliner, de la sort dotzena a Benassal (Partida de la Font d´en Mas), per temps de 18 anys, a cens de 6 barcelles de blat anyals
Comparison of Statistical and Interval Analysis for the Energy Flow Uncertainties in Structural Vibrating Systems
No full textIn this paper the energy flow confidence between two structural multimodal systems coupled by a joint with uncertain parameters is computed by two different methods. The first one assumes that the joint parameters perturbed randomly: the statistical moments of the energy flow are calculated by an analytical procedure. The second one uses interval analysis. The joint parameters are considered interval variables and the interval of the energy flow is determined. The properties of the statistical and interval solution are investigated and compared
Application of DOE to estimate the variability of SEA solution
Full text linkStatistical Energy Analysis (SEA) is the most acknowledged method to predict the averaged sound and vibration levels in mechanical systems in the high frequency range. A limit of this analysis is that of providing only the mean value of the variables of interest. The mean value provided by SEA equations is the mean of the responses of a set of similar systems, averaged on frequency bands. Two systems are considered similar if their physical parameters are slightly different.
No information on the standard deviation is obtained by SEA as it would be expected by a true statistical approach.
In this paper, the variability of SEA parameters (coupling loss factors, internal loss factor and injected powers) to uncertainties in the physical properties of the considered mechanical system (Young modulus, material density, geometry, ...) is investigated using a Design of Experiment (DoE) approach. This is done in order to take into account the idea of similar systems. Subsequently, the variability of SEA solution to the uncertainties on SEA parameters found at the previous step is investigated by using again a DoE approach
- …
