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Special attention is given to the effects of GPL distribution pattern, weight fraction, geometry and dimension on the dynamic instability behaviour.
A detailed parametric study is carried out to examine the effects of the distribution pattern, weight fraction, geometry and size of GPL nanofillers, foundation stiffness parameters, slenderness ratio and boundary conditions on the buckling and postbuckling behaviours.
Numerical results show that GPL distribution pattern, weight fraction, and geometry and size have significant influences on the bending and buckling behaviors of the functionally graded GPL reinforced nanocomposite plate.
The influences of the distribution pattern, weight fraction, geometry and size of GPL nanofillers, the total number of layers together with the vibration amplitude and boundary conditions on the nonlinear free vibration behavior are investigated.
Numerical problems are given to reveal the influences of GPL distribution pattern, weight fraction, geometry of GPL nanofillers, length-to-thickness and edge conditions on nonlinear bending responses of the GPL-RPC plates.
Results are plotted in the form of frequency-response and force-response curves to indicate the effect of various parameters such as GPL distribution pattern, weight fraction, geometry of GPL nanofillers and boundary constraints of FG-GPLRC plates.
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The pattern weights were uncorrelated with each other, r=−0.04.
The pattern weights are iteratively bipartitioned into subsets based upon the size of the weights; each successive partition isolates the subset with the largest pattern weights.
Once the optimal set size is reached, this final set of patterns represents the decoding model with the greatest evidence for the pattern weights.
Step 8: Normalised trimmed weight: Second weighting procedure: To take into account the random skips in the Composite International Diagnostic Interview questionnaire applied to define the long path we calculated the skip pattern weights.
Associations of functional gene sets with mark levels and basis pattern weights were done using the random-set method [ 65]. (an implementation of the random-set method is included in the source-code distribution of epicode).
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