3D Visualization of the Results of Using Modern Ofa Technology on the Example of Real Boiler

The leading place in the world for environmental protection is currently occupied by the protection of the air basin. And the main sources of atmospheric pollution are industrial enterprises, motor transport and thermal power plants. Thus, there is an obvious need to increase attention to the problems of the innovation sector, mainly in the areas of technical improvement of heat and power industry enterprises. Therefore, the study of the problems of reducing the amount of harmful emissions into the atmosphere, control and regulation of its quality, as well as the study of new various methods of innovative development of thermal power is an urgent task at present, requiring a serious scientific approach. In the proposed work, computer experiments were carried out in the field of innovative energy production technologies (the use of modern "sharp blast" OFA technology) at a specific thermal power facility of the enterprise of the Republic of Kazakhstan. During the experiment, various ways of supplying additional air through OFA nozzles were investigated: OFA=0% (basic version without additional air supply), OFA=10% and OFA=18%. For these three modes, a comparative analysis of the aerodynamics of the furnace part of the boiler was performed according to the obtained distributions of the temperature and concentration fields of nitrogen oxide NO over the entire volume of the combustion chamber. The results obtained were compared with experimental data obtained during experiments conducted directly at the CHP.

System-dynamic model of power redistribution among several subjects

A simple model simulating the redistribution of decision-making functions between the state, business, bureaucracy and regional elites is presented. The methodological basis of the work is system-dynamic modeling. The model is implemented in the specialized program Powersim Studio 10. A diagram of stocks and flows is considered, all elements of which were compared with certain political science concepts. The mathematical apparatus of the model is described. Some results of computer experiments are presented: these results indicate the operability and interpretability of the model.

On the convergence of bumping routes to their limit shapes in the RSK algorithm: numerical experiments

Introduction: The Robinson — Schensted — Knuth (RSK) algorithm transforms a sequence of elements of a linearly ordered set into a pair of Young tableaux P, Q of the same shape. This transformation is based on the process of bumping and inserting elements in tableau P according to special rules. The trajectory formed by all the boxes of the tableau P shifted in the RSK algorithm is called the bumping route. D. Romik and P. Śniady in 2016 obtained an explicit formula for the limit shape of the bumping route, which is determined by its first element. However, the rate of convergence of the bumping routes to the limit shape has not been previously investigated either theoretically or by numerical experiments. Purpose: Carrying out computer experiments to study the dynamics of the bumping routes produced by the RSK algorithm on Young tableaux as their sizes increase. Calculation of statistical means and variances of deviations of bumping routes from their limit shapes in the L2 metric for various values fed to the input of the RSK algorithm. Results: A series of computer experiments have been carried out on Young tableaux, consisting of up to 10 million boxes. We used 300 tableaux of each size. Different input values (0.1, 0.3, 0.5, 0.7, 0.9) were added to each such tableau using the RSK algorithm, and the deviations of the bumping routes built from these values from the corresponding limit shapes were calculated. The graphs of the statistical mean values and variances of these deviations were produced. It is noticed that the deviations decrease in proportion to the fourth root of the tableau size n. An approximation of the dependence of the mean values of deviations on n was obtained using the least squares method.

Efficient collective search by BRT algorithm using fast rising threshold agent

The BRT algorithm is a method for the best-of-n problem that allows a group of distributed robots to find out the most appropriate collective option among many alternatives. Computer experiments show that the time required for finding out the best option is proportional to the number of options. In this paper, we aim to shorten this search time by introducing a few agents whose threshold increases faster than the normal one to achieve higher scalability of the BRT algorithm. The results show that the search time is reduced, and the variance is improved, especially under challenging problems where robots are required to make decisions out of a large number of options.

Investigation of the existence domain for Dyakonov surface waves in the Sage computer algebra system

Surface electromagnetic waves (Dyakonov waves) propagating along a plane interface between an isotropic substance with a constant dielectric constant and an anisotropic crystal, whose dielectric tensor has a symmetry axis directed along the interface, are considered. It is well known that the question of the existence of such surface waves is reduced to the question of the existence of a solution to a certain system of algebraic equations and inequalities. In the present work, this system is investigated in the Sage computer algebra system. The built-in technique of exceptional ideals in Sage made it possible to describe the solution of a system of algebraic equations parametrically using a single parameter, with all the original quantities expressed in terms of this parameter using radicals. The remaining inequalities were only partially investigated analytically. For a complete study of the solvability of the system of equations and inequalities, a symbolic-numerical algorithm is proposed and implemented in Sage, and the results of computer experiments are presented. Based on these results, conclusions were drawn that require further theoretical substantiation.

NUMERICAL PREDICTION OF VERTICAL SHIP MOTIONS AND ADDED RESISTANCE

Along with the development of computer technology, the capability of Computational Fluid Dynamics (CFD) to conduct ‘virtual computer experiments’ has increased. CFD tools have become the most important tools for researchers to deal with several complex problems. In this study, the viscous approach called URANS (Unsteady Reynolds Averaged Navier-Stokes) which has a fully non-linear base has been used to solve the vertical ship motions and added resistance problems in head waves. In the solution strategy, the FVM (Finite Volume Method) is used that enables numerical discretization. The ship model DTMB 5512 has been chosen for a series of computational studies at Fn=0.41 representing a high speed case. Firstly, by using CFD tools the TF (Transfer Function) graphs for the coupled heave- pitch motions in deep water have been generated and then comparisons have been made with IIHR (Iowa Institute of Hydraulic Research) experimental results and ordinary strip theory outputs. In the latter step, TF graphs of added resistance for deep water have been generated by using CFD and comparisons have been made only with strip theory.

Decision Rules Derived from Optimal Decision Trees with Hypotheses

Conventional decision trees use queries each of which is based on one attribute. In this study, we also examine decision trees that handle additional queries based on hypotheses. This kind of query is similar to the equivalence queries considered in exact learning. Earlier, we designed dynamic programming algorithms for the computation of the minimum depth and the minimum number of internal nodes in decision trees that have hypotheses. Modification of these algorithms considered in the present paper permits us to build decision trees with hypotheses that are optimal relative to the depth or relative to the number of the internal nodes. We compare the length and coverage of decision rules extracted from optimal decision trees with hypotheses and decision rules extracted from optimal conventional decision trees to choose the ones that are preferable as a tool for the representation of information. To this end, we conduct computer experiments on various decision tables from the UCI Machine Learning Repository. In addition, we also consider decision tables for randomly generated Boolean functions. The collected results show that the decision rules derived from decision trees with hypotheses in many cases are better than the rules extracted from conventional decision trees.