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A hybrid inverse method for small scale parameter estimation of FG nanobeams
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 Title & Authors
A hybrid inverse method for small scale parameter estimation of FG nanobeams
Darabi, A.; Vosoughi, Ali R.;
 Abstract
As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen`s nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.
 Keywords
small scale parameter estimation;nanobeams;hybrid numerical method;
 Language
English
 Cited by
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Thermal Post-buckling Analysis of Moderately Thick Nanobeams, Iranian Journal of Science and Technology, Transactions of Civil Engineering, 2017  crossref(new windwow)
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A mixed finite element and improved genetic algorithm method for maximizing buckling load of stiffened laminated composite plates, Aerospace Science and Technology, 2017, 70, 378  crossref(new windwow)
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An approach for the Pasternak elastic foundation parameters estimation of beams using simulated frequencies, Inverse Problems in Science and Engineering, 2017, 1  crossref(new windwow)
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A new hybrid CG-GAs approach for high sensitive optimization problems: With application for parameters estimation of FG nanobeams, Applied Soft Computing, 2017, 52, 220  crossref(new windwow)
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Dynamic moving load identification of laminated composite beams using a hybrid FE-TMDQ-GAs method, Inverse Problems in Science and Engineering, 2017, 25, 11, 1639  crossref(new windwow)
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