As a testbed for the proposed method, we consider the problem of optimal distributed reactive power compensation in smart microgrids.
To demonstrate the method, we consider the biologically important nonlinear reaction diffusion process of calcium wave propagation within living cells.
To evaluate the effectiveness of the proposed method, we consider different test scenarios considering the IEEE benchmark 24-bus, 30-bus and 118-bus test systems.
To illustrate the applicability of method, we consider a few vesicle-flow interaction problems: the sedimentation of a vesicle, interactions of one and three vesicles with a background Poiseuille flow.
To illustrate the potentials of the method, we consider the Stokes equations, describing slow flows of viscous incompressible fluids, as well as linearized equations corresponding to Maxwell's and some other viscoelastic models.
In order to use a reduced basis method, we consider an affine decomposition in terms of the parameter related to the friction coefficient and the wind measures at some given observation points.
To apply the convergent results about the approximation method, we consider a two-stage fuzzy facility location-allocation (FLA) problem with VaR objective, and solve the problem indirectly by solving its approximating problem.
Motivated by the problem of recovery of light oil by air injection, as an enhanced oil recovery method, we consider a liquid composed of light and medium pseudo-components.
The final method we consider is based on the polarizable continuum model, in which the free energy of transferring a molecule from an ideal gas to a liquid solution is computed, leading directly to values of activity coefficients and phase equilibrium calculations.
Finally, as a significant illustration of the method, we consider simple case studies: the paradigmatic examples of the Wide Mouthed Frog protocol [ACM Trans. Comput. Syst. 8 (1990) 18] and the Woo and Lam one-way authentication protocol [IEEE Comput. 25 (1992) 39].
To illustrate the basic idea of the method, we consider the general nonlinear system: (1.2).
