More importantly, the physical configuration of the problem changed in the high interactivity condition: thus, participants' actions wrought changes in the physical configuration of the problem, changes that are contingent on the preceding state of the problem.
Thus, this approach is possible to obtain approximations consistent with the physical configuration of the problem even for high values of the Hartmann number.
Such a configuration limits the problem of too little steam fed to the low-pressure turbine at low loads of the unit.
An approximation of a two-dimensional time-dependent analytical solution for the temperature distribution was first developed and subsequently adapted to mimic the specific testing configuration characteristics; the problem was finally simplified to enable further inverse analysis.
Due to the axis-symmetric configuration of the problem, the domain can be expressed in terms of the radial distance (r=sqrt{x^{2}+y^{2}}) and the vertical variable z, as (Omega_{H} = { 0 leq r leq R, z_{mathrm{min}} leq z < f_{mathrm{TOP}}(r) }), where (f_{mathrm{TOP}}(r)) represents the topography function (see Figure 1).
It is plausible to conjecture that such yoked participants may benefit from the changes in the initial physical configuration of the problem, recognize some or all of the emerging groupings, and see how these groupings can be combined to arrive at the answer.
A self-consistent technique simplifies the search for the best configuration and avoids the problem of ending in local minima.
The control design procedure is implemented in two steps: Initially by locating opposing tugboats to specific configurations, the overall problem is transformed into a second order system with an uncertain non-symmetric input gain matrix.
We propose a decomposition model that relies on chaining and function placement configurations to solve the problem.
