Том 56, № 11 (2016)

A new efficient technique intended for the numerical solution of a broad class of optimal control problems for complicated dynamical systems described by ordinary and/or partial differential equations is investigated. In this approach, canonical formulas are derived to precisely calculate the objective function gradient for a chosen finite-dimensional approximation of the objective functional.

A multicriteria identification and prediction method for mathematical models of simulation type in the case of several identification criteria (error functions) is proposed. The necessity of the multicriteria formulation arises, for example, when one needs to take into account errors of completely different origins (not reducible to a single characteristic) or when there is no information on the class of noise in the data to be analyzed. An identification sets method is described based on the approximation and visualization of the multidimensional graph of the identification error function and sets of suboptimal parameters. This method allows for additional advantages of the multicriteria approach, namely, the construction and visual analysis of the frontier and the effective identification set (frontier and the Pareto set for identification criteria), various representations of the sets of Pareto effective and subeffective parameter combinations, and the corresponding predictive trajectory tubes. The approximation is based on the deep holes method, which yields metric ε-coverings with nearly optimal properties, and on multiphase approximation methods for the Edgeworth–Pareto hull. The visualization relies on the approach of interactive decision maps. With the use of the multicriteria method, multiple-choice solutions of identification and prediction problems can be produced and justified by analyzing the stability of the optimal solution not only with respect to the parameters (robustness with respect to data) but also with respect to the chosen set of identification criteria (robustness with respect to the given collection of functionals).

The Dirichlet problem for a Fujita-type equation, i.e., a second-order quasilinear uniformly elliptic equation is considered in domains Ω_ε with spherical or cylindrical cavities of characteristic size ε. The form of the function in the condition on the cavities’ boundaries depends on ε. For ε tending to zero and the number of cavities increasing simultaneously, sufficient conditions are established for the convergence of the family of solutions {u_ε(x)} of this problem to the solution u(х) of a similar problem in the domain Ω with no cavities with the same boundary conditions imposed on the common part of the boundaries ∂Ω and ∂Ω_ε. Convergence rate estimates are given.

A two-level OpenMP + MPI parallel implementation is used to numerically solve a model kinetic equation for problems with complex three-dimensional geometry. The scalability and robustness of the method are demonstrated by computing the classical gas flow through a circular pipe of finite length and the flow past a reentry vehicle model. It is shown that the two-level model significantly speeds up the computations and improves the scalability of the method.

The Boltzmann kinetic equation is used to numerically study the evolution of separated flows over a backward-facing step at low Knudsen numbers. The Boltzmann equation is solved by applying an explicit–implicit scheme. To improve the efficiency of the solution algorithm, it is parallelized with the help of MPI. The solution obtained with the kinetic equation is compared with those based on continuous medium equations. It is shown that the kinetic approach makes it possible to reproduce the distributions of surface pressure, friction coefficient, and heat transfer, as well as to obtain a flow structure close to experimental data.