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Afterwards, the velocity is modelled through a surrogate modelling practice, and the model is validated both experimentally and statistically.
In one approach, experimentally obtained hysteresis loops are modelled through a suitable constitutive equation.
The hybrid LC-plasmonic tuning mechanism is modelled through a combination of finite element (FEM), Jones calculus and finite difference time domain (FDTD) simulation techniques.
The seasonality part is modelled through a combination of linear and sinusoidal functions with appropriate coefficients and arguments.
Uncertainty associated with demand is modelled through a set of discrete scenarios that illustrate future possible realizations.
The randomness in structural parameters is modelled through a vector of mutually correlated, non-Gaussian random variables.
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Adhesion is modelled through an adhesive zone model.
To address this task, the problem is handled through Reverse Logistics and is modelled through an Uncapacitated Facility Location Problem.
It is modeled through a continuous approach thanks to a neural network.
Fracture is modeled through a constitutive softening-fracture law at the boundary nodes.
The available observations are modeled through a numerical code based on the advection dispersion equation.
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