Material-dependent grain growth coefficients were simultaneously fitted by minimizing the difference between the simulated and experimental grain sizes.
In this paper, the structural nonlinear properties are simulated by using hysteresis material parameters of Bouc Wen model, and the optimal values of the hysteresis parameters are obtained by minimizing the objective function using the simulated annealing global optimization method.
The best-fitting dipole can be determined by minimizing the residual error between the simulated scalp EEG measurement and the forward-calculated measurement (2) Δ 2 = | M − L q | 2, where M denotes the simulated EEG measurement data, q is dipole component vector, and L is the lead field matrix which describes the transfer function from dipole components to the simulated scalp EEG measurements.
The MDSFR analysis algorithm estimates μ′ s (or a1 and a2 in case of a spectrally constrained fit) and γ by minimizing the weighted residual error between the simulated and the model estimated R SF o (λ, d fiber ) for all included fiber diameters (and all included wavelengths in case of a spectrally constrained fit) simultaneously.
Both the measured force displacement curves and the strain fields are used as input for an inverse FEM optimization algorithm that identifies suitable strain hardening model parameters by minimizing the differences between experimental and simulated results.
Numerical values of the model coefficients are determined by minimizing the difference between measured and simulated acoustic quantities, namely the insertion loss and wall pressure fluctuations at a few locations inside the duct.
The observed dependence of both Φ and η c on dimensionless scattering is presented in Section 3.1.2 and described in Section 4. The parameters [ ρ1, ρ2, ρ3] were fitted by minimizing the weighted residual error between the simulated (R SF MC ) and model-estimated (R SF Model ) reflectance intensities, with each point weighted by the inverse of the simulated data point.
Then, for evaluating its effect on the snap-through load, a snap-through process was simulated by minimizing the total potential energy of the bistable composites through the Rayleigh Ritz approximation method.
The adsorption parameters were estimated by minimizing the difference between the experimental flux and simulated flux.
In short, fluxes were estimated by minimizing the variance-weighted sum of squared residuals between the simulated and model-predicted MIDs using least-squares regression [ 41].
