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In this paper, we investigate different alternative ideas for the design of digital predistortion models for radiofrequency power amplifiers. When compared to the greedy search algorithm, these algorithms allow a faster identification of the model parameters combination while still performing reasonably well. For the subsequent implementation, different metrics of model costs and score results in the process of optimization enable us to achieve sparse selections of the model, which balance the model accuracy and model resources (according to the complexity of implementation). The results achieved in the process of simulations show that combinations obtained with explored algorithms show the best performance after a lower number of simulations.

Based on the modeling method using a mesh system, an algorithm is implemented for solving a unsteady problem with moving bodies The algorithm takes into account the movement and rotation of bodies according to a given law of motion. The algorithm is applied to analysis the flow around an infinite composed of cylinders with an elliptical cross-section, which either move across the flow or rotate with a change in the angle of attack. To simulate the flow of bodies with a sharp edge, characteristic of the profiles of gas turbine machines, an algorithm for constructing a mesh of type C with the inclusion of a certain area behind the profile is implemented. The program for modeling the flow near the profile is implemented within the framework of models of Euler equations, Navier – Stokes equations in the approximation of a thin layer with laminar viscosity and turbulent viscosity in the framework of an algebraic viscosity model. The program has also been adapted to solve the problems of internal gas dynamics of turbomachines. For this purpose, the method of setting the boundary conditions at the entrance and exit from the calculated area from the velocity to the pressure drop, as well as at the lateral boundaries from the free flow to the periodicity, was changed. This made it possible to simulate the flow of gas in the inter-blade channels of compressors and turbines of gas turbine engines. To refine the algorithm, a series of calculations of the aerodynamic parameters of several turbine cascades in various subsonic and supersonic modes and their comparison with the experiment were carried out. Calculations of turbine grating parameters were carried out within the framework of the inviscid and viscous gas model. The calculation and experiment were compared by the distribution of gas parameters near the profile, as well as by the energy losses of the flow in the cascade. Calculations have shown the applicability and correctness of the program to solve this class of problems. To test the program on the problems of external subsonic aerodynamics, calculations of the aerodynamic characteristics of an isolated airfoil in an undisturbed flow were performed. The results obtained allow us to assert the applicability of the hybrid grid method to various classes of problems of applied gas dynamics.

The article presented the computational algorithm developed to study chemical processes in the internal flows of a multicomponent gas under the influence of laser radiation. The mathematical model is the gas dynamics’ equations with chemical reactions at low Mach numbers. It takes into account dissipative terms that describe the dynamics of a viscous heat-conducting medium with diffusion, chemical reactions and energy supply by laser radiation. This mathematical model is characterized by the presence of several very different time and spatial scales. The computational algorithm is based on a splitting scheme by physical processes. Each time integration step is divided into the following blocks: solving the equations of chemical kinetics, solving the equation for the radiation intensity, solving the convection-diffusion equations, calculating the dynamic component of pressure and calculating the correction of the velocity vector. The solution of a stiff system of chemical kinetics equations is carried out using a specialized explicit second-order accuracy scheme or a plug-in RADAU5 module. Numerical Rusanov flows and a WENO scheme of an increased order of approximation are used to find convective terms in the equations. The code based on the obtained algorithm has been developed using MPI parallel computing technology. The developed code is used to calculate the pyrolysis of ethane with radical reactions. The superequilibrium concentrations’ formation of radicals in the reactor volume is studied in detail. Numerical simulation of the reaction gas flow in a flat tube with laser radiation supply is carried out, which is in demand for the interpretation of experimental results. It is shown that laser radiation significantly increases the conversion of ethane and yields of target products at short lengths closer to the entrance to the reaction zone. Reducing the effective length of the reaction zone allows us to offer new solutions in the design of ethane conversion reactors into valuable hydrocarbons. The developed algorithm and program will find their application in the creation of new technologies of laser thermochemistry.

The paper presents various modifications of the Frank–Wolfe algorithm in the equilibrium traffic assignment problem. The Beckman model is used as a model for experiments. In this article, first of all, attention is paid to the choice of the direction of the basic step of the Frank–Wolfe algorithm. Algorithms will be presented: Conjugate Frank–Wolfe (CFW), Bi-conjugate Frank–Wolfe (BFW), Fukushima Frank –Wolfe (FFW). Each modification corresponds to different approaches to the choice of this direction. Some of these modifications are described in previous works of the authors. In this article, following algorithms will be proposed: N-conjugate Frank–Wolfe (NFW), Weighted Fukushima Frank–Wolfe (WFFW). These algorithms are some ideological continuation of the BFW and FFW algorithms. Thus, if the first algorithm used at each iteration the last two directions of the previous iterations to select the next direction conjugate to them, then the proposed algorithm NFW is using more than $N$ previous directions. In the case of Fukushima Frank–Wolfe, the average of several previous directions is taken as the next direction. According to this algorithm, a modification WFFW is proposed, which uses a exponential smoothing from previous directions. For comparative analysis, experiments with various modifications were carried out on several data sets representing urban structures and taken from publicly available sources. The relative gap value was taken as the quality metric. The experimental results showed the advantage of algorithms using the previous directions for step selection over the classic Frank–Wolfe algorithm. In addition, an improvement in efficiency was revealed when using more than two conjugate directions. For example, on various datasets, the modification 3FW showed the best convergence. In addition, the proposed modification WFFW often overtook FFW and CFW, although performed worse than NFW.

A review of the problems of preparing accurate geometric models of steel ropes based on mathematical models without significant simplifications, taking into account the intended purpose of the model, is carried out. Possible approaches to the generation of precise geometric models of steel ropes that have no fundamental limitations on their integration in computational domains and the subsequent construction of finite element models based on them are shown. A generalized parameterized geometric model of single and double twist ropes and its algorithmic implementation using the OpenCASCADE Core Technology geometric modeling kernel in the Gmsh environment (open source software) is considered. The problems of using generic tabular data from steel rope assortment standards as initial data for constructing geometric models are considered. Methods of preliminary verification of collisions of a geometric model based on the initial data of a geometric model are given. Post-verification methods based on Boolean operations over rope wire bodies are given to identify incorrect results of generating models of wire bodies with curvilinear side surfaces based on the algorithm of sequential hierarchical construction of individual wires of single strand and sequential copying of it. Various methods of the process of constructing geometric models of rope wires by extrusion are shown: through a sequence of generatrix with the formation of a body limited by curvilinear surfaces, through a sequence of generatrix with the formation of a body limited by linearly approximated surfaces, and extrusion of one generatrix along a single guideline. The computational complexity of the geometric model generation and the required volume of RAM for the two most universal methods of creating a body of wire are investigated. A method for estimating the value of the step of the arrangement of the generatrix of a single wire is shown, and the influence of its value on the computational complexity of the procedure of wire construction is investigated. Recommendations are given for choosing the value of the radial gap between the layers of wires. An algorithmic implementation of the method for searching for collisions of a geometric model of a steel rope in a non-interactive mode is shown. Approaches to the formation of procedures for processing collisions are proposed. Approaches presented in the article can be implemented in the form of software modules for execution in the Gmsh environment, as well as for another environment using the OpenCascade Core Technology geometric modeling kernel. Such modules allow automation of the construction of accurate geometric models of steel ropes in any configuration without fundamental restrictions on subsequent use, both stand-alone and in the form of objects (primitives) suitable for integration in a third-party model.

In traditional CNC systems, each segment of a piecewise linear trajectory is described by a separate block of the control program. In this case, a trapezoidal trajectory of movement is formed, and the stitching of individual sections is carried out at zero values of speed and acceleration. Increased productivity is associated with continuous processing, which in modern CNC systems is achieved through the use of spline interpolation. For a piecewise linear trajectory, which is basic for most products, the most appropriate is a first-degree spline. However, even in the simplest case of spline interpolation, the closed nature of the basic software from leading manufacturers of CNC systems limits the capabilities of not only developers, but also users. Taking this into account, the purpose of this work is a detailed study of the structural organization and operation algorithms of the simulation model of piecewise linear spline interpolation. Limitations on jerk and acceleration are considered as the main measure to reduce dynamic processing errors. In this case, special attention is paid to the S-shaped shape of the speed curve in the acceleration and deceleration sections. This is due to the conditions for the implementation of spline interpolation, one of which is the continuity of movement, which is ensured by the equality of the first and second derivatives when joining sections of the trajectory. Such a statement corresponds to the principles of implementing combined control systems of a servo electric drive, which provide partial invariance to control and disturbing effects. The reference model of a spline interpolator is adopted as the basis of the structural organization. The issues of processing scaling, which are based on a decrease in the vector speed in relation to the base value, are also considered. This allows increasing the accuracy of movements. It is shown that the range of changes in the speed of movements can be more than ten thousand, and is limited only by the speed control capabilities of the actuators.

The objective of this article is to develop a model for a realistic description of a mixed flow of two types of vehicles (cars and trucks) on multi-lane highways, taking into account differences not only in the technical characteristics of vehicles (dimensions, maximum speed), but also differences in driving strategies. The article includes a literature review, including publications of recent years, confirming the relevance of modeling heterogeneous traffic flows.

The new model takes into account that trucks have a lower maximum speed compared to cars and are slower to start. They are less maneuverable, so it is more difficult for them to change lanes. In addition, the movement of trucks can be regulated by some restrictive rules, for example, a ban on driving in left lanes.

The model is based on the cellular automata theory, which allows for a comprehensive description of the features of individual flow components. At each time step, the state of the automaton cells is updated in two stages — changing lanes and moving forward. The algorithms of both substeps for cars and trucks differ. Each vehicle is assigned a number of parameters: vehicle type, length, maximum speed, lane change strategy, in-lane movement strategy.

The model is implemented as a software package that allows simulating traffic on various sections of the road network — intersections, sections with narrowing and widening of the road, entrances and exits from the highway. In this work, a road section with a varying number of lanes and a straight multi-lane section with a virtual detector were selected for testing the model. The results are presented in the form of local speed-density and flow-density diagrams, as well as spatiotemporal speed diagrams.

To test the model, a number of problems with different percentages of passenger cars and trucks are solved, which allows demonstrating a drop in the capacity of elements of the road network with an increase in the share of trucks in the flow. The cases of uniform distribution by lanes and the restriction to the right lane for trucks are simulated. The positive effect of introducing a ban on the movement of trucks in left lanes on a multi-lane highway is illustrated.

Monte Carlo (MC) reinforcement learning suffers from high sample complexity, especially in environments with sparse rewards, large state spaces, and strongly correlated trajectories that reduce the statistical efficiency of return estimation. These well-known limitations often lead to slow convergence and unstable learning dynamics, particularly in settings where only a small fraction of collected trajectories is actually informative for policy improvement. A key challenge is therefore to identify a compact yet diverse subset of episodes that contributes most to the accuracy of value estimates while preserving sufficient exploration of the environment. To address this challenge, we reformulate episode selection as a Quadratic Unconstrained Binary Optimization (QUBO) problem and solve it using quantum-inspired sampling techniques. Our method, MC+ QUBO, inserts a combinatorial filtering step into the standard MC policy-evaluation pipeline: given a batch of trajectories, it selects a subset that maximizes cumulative reward and encourages broad state-space coverage. This selection procedure is expressed as a QUBO model, where linear terms favor high-return episodes, quadratic terms penalize redundancy between trajectories, and additional coupling terms can be used to enforce coverage-related constraints or promote structural diversity. Within this framework, we investigate two black-box QUBO solvers: Simulated Quantum Annealing (SQA), which emulates tunneling-based exploration of the search landscape, and Simulated Bifurcation (SB), a dynamical-systems-based iterative optimization method. Both solvers demonstrate the ability to efficiently navigate the combinatorial structure of the trajectory-selection problem and to handle batch sizes that are otherwise computationally expensive for exhaustive or deterministic search. Experiments in a finite-horizon GridWorld environment show that MC+QUBO consistently outperforms vanilla MC in convergence speed, stability of return estimates, and final policy quality. These results highlight the promise of quantum-inspired optimization as a practical decision-making subroutine within reinforcement-learning algorithms, offering a scalable way to improve sample efficiency without modifying the underlying learning paradigm.

We consider the two-dimensional mathematical model of wildfire. Numerical solution algorithm based on the method of large particles was developed for this model.

The purpose of this paper is to generalize the macroscopic hydrodynamic vehicular traffic models by using the algorithm for constructing the adequate state equation — dependence the pressure from traffic density by taking into account the real experimental data (possibly using the parametric solutions for model equations). It is proved that this kind of state equation which closed model equations system and obtained from the experimentally observed form of the fundamental diagram — dependence the traffic intensity from its density, completely determines the all properties of the used phenomenological model.