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The closely spaced modes exist in symmetric structures such as circular plates, gears or disks. Theoretically, closely spaced modes are known as two separated modes with the same amount but, these modes are often detected as only one mode in the classical modal methods. In this article, at the first, some classical modal method is introduced and the most important of their difficulties is considered then, Operational Modal Analysis (OMA) is applied to abate these problems. The Stochastic Subspace Identification based on covariance (SSI-COV) driven is used for this purpose. Different conditions for closely spaced modes is considered and simulated on a free-free steel plate using Matlab software. In order to consider the SSI-COV method in identification of closely spaced modes experimentally, classical and operational modal testing are done on a steel ring. The numerical and experimental results from simulations demonstrate the effectiveness of OMA for identifying and separating the close modes.

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Dynamic analysis of the civil structures such as bridges, towers and buildings is required for their design and maintenance. Modal analysis is a powerful tool to conduct some part of dynamic analysis in determination of the modal parameter in terms of natural frequencies, damping factors and mode shapes. However, excitation of these structures is usually difficult and sometimes impossible. As these structures are usually excited by ambient forces such as wind, this idea is suggested that the structure is modeled considering the natural forces as the inputs.However, the ambient forces are unknown and have a complicated nature to be measured. An alternative approach is using the operational modal analysis concepts in which only the responses are measured and the modal parameter are extracted. In this article Frequency Domain Decomposition (FDD) method is used for identification of the modal parameter of a clamped-clamped beam and the results are compared with those of the FEM. The operational modal analysis is conducted on a type of a bridge under ambient forces in a real test and the results are compared with those of the conventional Modal testing. The results confirm the method for engineering applications.

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Abstract- In this paper, it is shown how to use the recently developed Firefly Algorithm to optimize abrasive water-jet cutting as a nonlinear multi-parameter process. Back propagation neural network were developed to predict surface roughness in abrasive water-jet cutting (AWJ) process. In the development of predictive models, machining parameters of traverse speed, water-jet pressure, standoff distance and abrasive flow rate were considered as model variables. Firefly Algorithm by using back propagation neural network optimizes glass surface roughness in abrasive water-jet cutting and proposes appropriate parameters for minimum surface roughness. Testing results demonstrate that the model is suitable for predicting the response parameters. However this algorithm has not be tested for practical problems, the results showed this algorithm applicable for processes with complex nature.

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Conventional modal testing is a powerful tool for dynamic analysis of structures. One of the drawbacks of this technique is the problem of excitation of large structures such as: bridges, towers or trains. However, these structures are excited by ambient forces, such as wind, walking of people or passing the cars on bridges. Operational Modal Analysis (OMA) is the practical tool to overcome this problem. In OMA the structure is excited by ambient forces and only the responses are taken into account. In this article, the accuracy of one of OMA methods is investigated. The modal parameters of a cantilever beam are estimated both from Stochastic Subspace Identification–Covariance Driven (SSI-COV) method and Finite element method. The effect of noise and damping on the accuracy of modal parameters is investigated. Also, a crankshaft is considered for experimental investigation of the accuracy of SSI-COV method. The results show the applicability of SSI-COV method in practical cases.

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One of the drawbacks of the operational modal analysis techniques is that there is no possibility of measurement of the responses in all required points, which is attributed to the limitations of either the number of accelerometers or the number of measurement channels. To overcome this shortcoming, an experiment should be performed in different steps and relations between these steps of the experiment are determined by selection of some specific points as reference points. Existing techniques use the correlation between measurement points to determine the reference points in which an increase in the environmental noise leads to the incapability of the method. In this paper, a new index for selection of reference points is introduced which is more efficient in the noisy environments. To evaluate the proposed method numerically, a comparison has been drawn between the results of this method and correlation approaches using a FE model of a beam. To validate the method, an experiment has been conducted on a steel plate. Obtained results from numerical and experimental cases show that the proposed index is more capable in reference point selection and calculation of the modal parameters of the structures comparing to the results of correlation method.

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Conventional modal testing of large structures is always associated with difficulties in artificial excitation of the structure. Operational Modal Analysis (OMA) is one approach to overcome the excitation problem. In OMA only the responses are measured and the structure is excited by ambient forces. For large structures the simultaneous measurement of responses in all selected points is usually impossible due to not having enough available accelerometers or measurement channels. Therefore, the structure is tested in several steps. As a result, some reference points should be selected to correlate all of the measurements. In this article a new criterion is introduced for selection of reference points based on finite element model of structure. A beam is used for numerical validation of the method. A steel beam is also used for experimental case study. Both numerical and experimental results demonstrate the effectiveness of this criterion.

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In this paper, a new FRF-based model updating method is proposed based on the Structural Modification Using experimental frequency Response Functions (SMURF) method. The method deals with the complex Frequency Response Functions (FRFs) and aims to update the lumped parameters of system. The parameters of FE model are updated accurately using only a limited data. A twelve Degrees Of Freedom system is considered as a test case in a simulated experiment. The convergence of the method and the accuracy with which it corrects the FE model are studied. Moreover, the effects of the number of modes, the frequency range of interest, the coordinate incompleteness and noise on the quality of the updated model are investigated. Finally a cantilever beam was used as experimental case study. The results show that the updated FRFs are in good agreement with their experimental counterparts.

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Conventional modal testing is known as a powerful tool for dynamic analysis of structures. However, for some engineering structures, conventional modal testing is difficult or even impossible to conduct due to the problems associated with the artificial excitation of structure. Operational Modal Analysis (OMA) is one solution to deal with these cases. In OMA the structure is excited by ambient forces and only the responses are measured and taken into account. Accelerometers are the traditional tools for measuring the responses of structure. It is well khonwn that the measured responses are contaminated by bias errors corresponding to the mass-loading effect of accelerometers. This causes the natural frequencies of structure are measured lower than the real values. In this paper a new method is proposed for eliminating the mass-loading effects of accelerometers from measured responses in OMA. A numerical model of a mass-spring-damper system is used for validation of the method. Also a steel plate is used for experimental validation of the proposed approach. The results are confirmed by those of conventional modal testing. Both numerical and experimental results show that the proposed method can effectively eliminate the mass-loading effects of accelerometers from measured responses in OMA. Also, the method has the ability to correct the measured natural frequencies from OMA accurately.

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In the present paper, heat transfer and entropy generation in Rayleigh-Bَenard convection of nanofluids subjected to a magnetic field within an enclosed cavity is studied by adopting the lattice Boltzmann Model. The left and the right walls are smooth and insulated against heat and mass. The bottom wavy wall is heated, while the top flat wall is maintained at the cold temperature. The variation of density is slight thus; hydrodynamics and thermal fields equations are coupled using the Boussinesq approximation. The density and energy distribution are both solved by D2Q9 model. The study have been carried out for Rayleigh number 103, 104 and 105, Hartmann number 0, 30, 60 and 90 and volume fractions of 0 up to 0.04 for Cu, CuO and Al2O3 nanoparticles in base pure water fluid. Results show that the Nusselt number and entropy generation increase with the increment of Rayleigh number and nanoparticles volume fraction, but those decrease by the increment of the Hartmann number. The enhancement of magnetic field augments or plummets the effect produced by the presence of nanoparticles on heat transfer and entropy generation at different Rayleigh numbers. In addition, it is shown the greatest effect of nanoparticles on heat transfer and entropy generation is observed by addition of Cu nanoparticles and the least is function of Ra number. This study can, provide useful insight for enhancing the convection heat transfer performance by considering of energy losses within enclosed cavities with Rayleigh–Bَenard convection nanofluid under influence of magnetic field.