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The performance of the designed polarization beam splitter is evaluated by utilizing optical properties of multi-walled carbon nanotubes, finite element modeling of wave propagation and transmission through periodic arrays.
The seismic performance of the new earthquake resistant abutment is evaluated by utilizing a benchmark bridge, whose design was based on Eurocodes, which has a relatively expensive isolation system with lead rubber bearings and dampers.
The sensitivity analysis invoking the CPU time-consuming finite element analyses is replaced with the genetic evolution and the fitness of each genome in the population is evaluated by utilizing the response surfaces of objective functions approximated by ANN.
The stiffness performance of the manipulator is evaluated by utilizing the extremum stiffness values, and the influences of design parameters on the stiffness properties are presented, which will be valuable for the architecture design of a 3-PUU PKM.
Furthermore, the stiffness performance of the manipulator is evaluated by utilizing the extremum stiffness values over the usable workspace, and the influences of design parameters on stiffness properties are presented, which will be helpful for the architecture design of the TPM.
However, every individual is evaluated by utilizing the constrained-based discrete-event simulation.
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The constructed intelligent models are evaluated by utilizing extensive experimental data reported in open literature.
Validity of the presented models has been evaluated by utilizing several statistical parameters.
The model parameters were evaluated by utilizing least square algorithm based on available experimental and first-principles data.
Airflow distribution, oxygen and hazardous gas dispersion as well as ambient temperature within the mining area are evaluated by utilizing the well-established computational fluid dynamics (CFD) approach.
The system poles are identified by employing the least-squares complex frequency-domain (LSCF) estimator, following which the mode shapes are evaluated by utilizing singular value decomposition (SVD) technique for PSDT matrix.
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