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The article provides approaches to evolutionary modelling of synthesis of organised systems and analyses methodological problems of evolutionary computations of this kind. Based on the analysis of works on evolutionary cybernetics, evolutionary theory, systems theory and synergetics, we conclude that there are open problems in formalising the synthesis of organised systems and modelling their evolution. The article emphasises that the theoretical basis for the practice of evolutionary modelling is the principles of the modern synthetic theory of evolution. Our software project uses a virtual computing environment for machine synthesis of problem solving algorithms. In the process of modelling, we obtained the results on the basis of which we conclude that there are a number of conditions that fundamentally limit the applicability of genetic programming methods in the tasks of synthesis of functional structures. The main limitations are the need for the fitness function to track the step-by-step approach to the solution of the problem and the inapplicability of this approach to the problems of synthesis of hierarchically organised systems. We note that the results obtained in the practice of evolutionary modelling in general for the whole time of its existence, confirm the conclusion the possibilities of genetic programming are fundamentally limited in solving problems of synthesizing the structure of organized systems. As sources of fundamental difficulties for machine synthesis of system structures the article points out the absence of directions for gradient descent in structural synthesis and the absence of regularity of random appearance of new organised structures. The considered problems are relevant for the theory of biological evolution. The article substantiates the statement about the biological specificity of practically possible ways of synthesis of the structure of organised systems. As a theoretical interpretation of the discussed problem, we propose to consider the system-evolutionary concept of P.K.Anokhin. The process of synthesis of functional structures in this context is an adaptive response of organisms to external conditions based on their ability to integrative synthesis of memory, needs and information about current conditions. The results of actual studies are in favour of this interpretation. We note that the physical basis of biological integrativity may be related to the phenomena of non-locality and non-separability characteristic of quantum systems. The problems considered in this paper are closely related to the problem of creating strong artificial intelligence.

Computer-aided assembly planning for complex products is an important engineering and scientific problem. The assembly sequence and content of assembly operations largely depend on the mechanical structure and geometric properties of a product. An overview of geometric modeling methods that are used in modern computer-aided design systems is provided. Modeling geometric obstacles in assembly using collision detection, motion planning, and virtual reality is very computationally intensive. Combinatorial methods provide only weak necessary conditions for geometric reasoning. The important problem of minimizing the number of geometric tests during the synthesis of assembly operations and processes is considered. A formalization of this problem is based on a hypergraph model of the mechanical structure of the product. This model provides a correct mathematical description of coherent and sequential assembly operations. The key concept of the geometric situation is introduced. This is a configuration of product parts that requires analysis for freedom from obstacles and this analysis gives interpretable results. A mathematical description of geometric heredity during the assembly of complex products is proposed. Two axioms of heredity allow us to extend the results of testing one geometric situation to many other situations. The problem of minimizing the number of geometric tests is posed as a non-antagonistic game between decision maker and nature, in which it is required to color the vertices of an ordered set in two colors. The vertices represent geometric situations, and the color is a metaphor for the result of a collision-free test. The decision maker’s move is to select an uncolored vertex; nature’s answer is its color. The game requires you to color an ordered set in a minimum number of moves by decision maker. The project situation in which the decision maker makes a decision under risk conditions is discussed. A method for calculating the probabilities of coloring the vertices of an ordered set is proposed. The basic pure strategies of rational behavior in this game are described. An original synthetic criterion for making rational decisions under risk conditions has been developed. Two heuristics are proposed that can be used to color ordered sets of high cardinality and complex structure.

The paper considers the problem of parameter identification of discrete-time linear stochastic systems in the state space with additive and multiplicative noise. It is assumed that the state and measurements equations of a discrete-time linear stochastic system depend on an unknown parameter to be identified.

A new approach to the construction of gradient parameter identification methods in the class of discrete-time linear stochastic systems with additive and multiplicative noise is presented, based on the application of modified weighted Gram – Schmidt orthogonalization (MWGS) and the discrete-time information-type filtering algorithms.

The main theoretical results of this research include: 1) a new identification criterion in terms of an extended information filter; 2) a new algorithm for calculating derivatives with respect to an uncertainty parameter in a discrete-time linear stochastic system based on an extended information LD filter using the direct procedure of modified weighted Gram – Schmidt orthogonalization; and 3) a new method for calculating the gradient of identification criteria using a “differentiated” extended information LD filter.

The advantages of this approach are that it uses MWGS orthogonalization which is numerically stable against machine roundoff errors, and it forms the basis of all the developed methods and algorithms. The information LD-filter maintains the symmetry and positive definiteness of the information matrices. The algorithms have an array structure that is convenient for computer implementation.

All the developed algorithms were implemented in MATLAB. A series of numerical experiments were carried out. The results obtained demonstrated the operability of the proposed approach, using the example of solving the problem of parameter identification for a mathematical model of a complex mechanical system.

The results can be used to develop methods for identifying parameters in mathematical models that are represented in state space by discrete-time linear stochastic systems with additive and multiplicative noise.

Difference of software development for parallel computing technology from sequential programming is dicussed. Arguements for introduction of new phases into technology of software engineering are given. These phases are: decomposition of algorithms, assignment of jobs to performers, conducting and mapping of logical to physical performers. Issues of performance evaluation of algorithms are briefly discussed. Decomposition of algorithms and programs into parts that can be executed in parallel is dicussed.

We developed an algorithm for fast simulation of VLSI CMOS (Very Large Scale Integration with Complementary Metal-Oxide-Semiconductors) with an accuracy control. The algorithm provides an ability of parallel numerical experiments in multiprocessor computational environment. There is computation speed up by means of block-matrix and structural (DCCC) decompositions application. A feature of the approach is both in a choice of moments and ways of parameters synchronization and application of multi-rate integration methods. Due to this fact we have ability to estimate and control error of given characteristics.

The study of complex processes in various spheres of human activity is traditionally based on the use of mathematical models. In modern conditions, the development and application of such models is greatly simplified by the presence of high-speed computer equipment and specialized tools that allow, in fact, designing models from pre-prepared modules. Despite this, the known problems associated with ensuring the adequacy of the model, the reliability of the original data, the implementation in practice of the simulation results, the excessively large dimension of the original data, the joint application of sufficiency heterogeneous mathematical models in terms of complexity and integration of the simulated processes are becoming increasingly important. The more critical may be the external constraints imposed on the value of the optimized functional, and often unattainable within the framework of the constructed model. It is logical to assume that in order to fulfill these restrictions, a purposeful transformation of the original model is necessary, that is, the transition to a mathematical model with a deliberately improved solution. The new model will obviously have a different internal structure (a set of parameters and their interrelations), as well as other formats (areas of definition) of the source data. The possibilities of purposeful change of the initial model investigated by the authors are based on the realization of the idea of strategic reflection. The most difficult in mathematical terms practical implementation of the author's idea is the use of simulation models, for which the algorithms for finding optimal solutions have known limitations, and the study of sensitivity in most cases is very difficult. On the example of consideration of rather standard discrete- event simulation model the article presents typical methodological techniques that allow ranking variable parameters by sensitivity and, in the future, to expand the scope of definition of variable parameter to which the simulation model is most sensitive. In the transition to the “improved” model, it is also possible to simultaneously exclude parameters from it, the influence of which on the optimized functional is insignificant, and vice versa — the introduction of new parameters corresponding to real processes into the model.

The article presents the results of numerical modeling of the vortex spatial non-stationary motion of the medium arising near the lateral and bottom surfaces of the descent module during its movement in the atmosphere of Mars. The numerical study was performed for the high-speed streamline regime at various angles of attack. Mathematical modeling was carried out on the basis of the Navier – Stokes model and the model of equilibrium chemical reactions for the Martian atmosphere gas. The simulation results showed that under the considered conditions of the descent module motion, a non-stationary flow with a pronounced vortex character is realized near its lateral and bottom surfaces. Numerical calculations indicate that, depending on the angle of attack, the nonstationarity and vortex nature of the flow can manifest itself both on the entire lateral and bottom surfaces of the module, and, partially, on their leeward side. For various angles of attack, pictures of the vortex structure of the flow near the surface of the descent vehicle and in its near wake are presented, as well as pictures of the gas-dynamic parameters fields. The non-stationary nature of the flow is confirmed by the presented time dependences of the gas-dynamic parameters of the flow at various points on the module surface. The carried out parametric calculations made it possible to determine the dependence of the aerodynamic characteristics of the descent module on the angle of attack. Mathematical modeling is carried out on the basis of the conservative numerical method of fluxes, which is a finitevolume method based on a finite-difference writing of the conservation laws of additive characteristics of the medium using «upwind» approximations of stream variables. To simulate the complex vortex structure of the flow over descent module, the nonuniform computational grids are used, including up to 30 million finite volumes with exponential thickening to the surface, which made it possible to reveal small-scale vortex formations. Numerical investigations were carried out on the basis of the developed software package based on parallel algorithms of the used numerical method and implemented on modern multiprocessor computer systems. The results of numerical simulation presented in the article were obtained using up to two thousand computing cores of a multiprocessor complex.

Computer-aided assembly planning of complex products is an important area of modern information technology. The sequence of assembly and decomposition of the product into assembly units largely depend on the mechanical structure of a technical system (machine, mechanical device, etc.). In most modern research, the mechanical structure of products is modeled using a graph of connections and its various modifications. The coordination of parts during assembly can be achieved by implementing several connections at the same time. This generates a $k$-ary basing relation on a set of product parts, which cannot be correctly described by graph means. A hypergraph model of the mechanical structure of a product is proposed. Modern discrete manufacturing uses sequential coherent assembly operations. The mathematical description of such operations is the normal contraction of edges of the hypergraph model. The sequence of contractions that transform the hypergraph into a point is a description of the assembly plan. Hypergraphs for which such a transformation exists are called $s$-hypergraphs. $S$-hypergraphs are correct mathematical models of the mechanical structures of any assembled products. A theorem on necessary conditions for the contractibility of $s$-hypergraphs is given. It is shown that the necessary conditions are not sufficient. An example of a noncontractible hypergraph for which the necessary conditions are satisfied is given. This means that the design of a complex technical system may contain hidden structural errors that make assembly of the product impossible. Therefore, finding sufficient conditions for contractibility is an important task. Two theorems on sufficient conditions for contractibility are proved. They provide a theoretical basis for developing an efficient computational procedure for finding all $s$-subgraphs of an $s$-hypergraph. An $s$-subgraph is a model of any part of a product that can be assembled independently. These are, first of all, assembly units of various levels of hierarchy. The set of all $s$-subgraphs of an $s$-hypergraph, ordered by inclusion, is a lattice. This model can be used to synthesize all possible sequences of assembly and disassembly of a product and its components. The lattice model of the product allows you to analyze geometric obstacles during assembly using algebraic means.

This paper is devoted to the problem of edge criticality identification and ranking in complex networks, which is a part of a modern research direction in the novel network science. The diffusion importance belongs to the set of acknowledged methods that help to identify the significant connections in the graph that are critical to retaining structural integrity. In the present work, we develop the Iterative Diffusion Importance algorithm that is based on the re-estimation of critical topological features at each step of the graph deconstruction. The Iterative Diffusion Importance has been compared with methods such as diffusion importance and degree product, which are two very well-known benchmark algorithms. As for benchmark networks, we tested the Iterative Diffusion Importance on three standard networks, such as Zachary’s Karate Club, the American Football Network, and the Dolphins Network, which are often used for algorithm efficiency evaluation and are different in size and density. Also, we proposed a new benchmark network representing the airplane communication between Japan and the US. The numerical experiment on finding the ranking of critical edges and the following network decomposition demonstrated that the proposed Iterative Diffusion Importance exceeds the conventional diffusion importance by the efficiency for 2–35% depending on the network complexity, the number of nodes, and the number of edges. The only drawback of the Iterative Diffusion Importance is an increase in computation complexity and hencely in the runtime, but this drawback can be easily compensated for by the preliminary planning of the network deconstruction or protection and by reducing the re-evaluation frequency of the iterative process.

In this paper, we propose a new software for simulation of fluid-structure interaction. The software is designed for solving coupled problems and provides an interface for synchronization synchronisation and data exchange between existing fluid and structural solvers. Algorithms of coupling solvers and mesh deformation are discussed. The software can be used on hybrid CPU/GPU platforms.