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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.

A model of combustion of premixed mixture of gases with one global chemical reaction is considered, the model includes equations of the second order for temperature of mixture and concentrations of fuel and oxidizer, and the right-hand sides of these equations contain the reaction rate function. This function depends on five unknown parameters of the global reaction and serves as approximation to multistep reaction mechanism. The model is reduced, after replacement of variables, to one equation of the second order for temperature of mixture that transforms to a first-order equation for temperature derivative depending on temperature that contains a parameter of flame propagation velocity. Thus, for computing the parameter of burning velocity, one has to solve Dirichlet problem for first-order equation, and after that a model dependence of burning velocity on mixture equivalence ratio at specified reaction rate parameters will be obtained. Given the experimental data of dependence of burning velocity on mixture equivalence ratio, the problem of optimal selection of reaction rate parameters is stated, based on minimization of the mean square deviation of model values of burning velocity on experimental ones. The aim of our study is analysis of uniqueness of this problem solution. To this end, we apply computational experiment during which the problem of global search of optima is solved using multistart of gradient descent. The computational experiment clarifies that the inverse problem in this statement is underdetermined, and every time, when running gradient descent from a selected starting point, it converges to a new limit point. The structure of the set of limit points in the five-dimensional space is analyzed, and it is shown that this set can be described with three linear equations. Therefore, it might be incorrect to tabulate all five parameters of reaction rate based on just one match criterion between model and experimental data of flame propagation velocity. The conclusion of our study is that in order to tabulate reaction rate parameters correctly, it is necessary to specify the values of two of them, based on additional optimality criteria.

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.

This work focuses on the application of a method of construction and conversion of three-dimensional computer models for optimization of geometric parameters of simulated devices. The method is used in design of complex technical devices for control system components of an exhaust gas recirculation vehicle – electric EGR valve with magnetic and electric motor. Three-dimensional geometric computer models were created in KOMPAS-3D environment and converted to Maxwell-2D. In Maxwell-2D environment transient electromagnetic processes for further optimization of parameters of therecirculation system devicewere calculated using a criterion of reducing power loss of the automobile engine.

Optimization of hull lines for the minimum resistance to movement is a problem of current interest in ship hydrodynamics. In practice, lines design is still to some extent an art. The usual approaches to decrease the ship resistance are based on the model experiment and/or CFD simulation, following the trial and error method. The paper presents a new method of in-detail hull form design based on the wave-based optimization approach. The method provides systematic variation of the hull geometrical form, which corresponds to alteration of longitudinal distribution of the hull volume, while its vertical volume distribution is fixed or highly controlled. It’s well known from the theoretical studies that the vertical distribution can't be optimized by condition of minimum wave resistance, thus it can be neglected for the optimization procedures. The method efficiency was investigated by application to the foreship of KCS, the well-known test object from the workshop Gothenburg-2000. The variations of the longitudinal distribution of the volume were set on the sectional area curve as finite volume increments and then transferred to the lines plan with the help of special frame transformation methods. The CFD towing simulations were carried out for the initial hull form and the six modified variants. According to the simulation results, examined modifications caused the resistance increments in the range 1.3–6.5 %. Optimization process was underpinned with the respective data analysis based on the new hypothesis, according to which, the resistance increments caused by separate longitudinal segments of hull form meet the principle of superposition. The achieved results, which are presented as the optimum distribution of volume present in the optimized designed hull form, which shows the interesting characteristics that its resistance has decrease by 8.9 % in respect to initial KCS hull form. Visualization of the wave patterns showed an attenuation of the transversal wave components, and the intensification of the diverging wave components.

We study the influence of fishery on a structured fish population under random changes of habitat conditions. The population parameters correspond to dominant pelagic fish species of Far-Eastern seas of the northwestern part of the Pacific Ocean (pollack, herring, sardine). Similar species inhabit various parts of the Word Ocean. The species body size distribution was chosen as a main population feature. This characteristic is easy to measure and adequately defines main specimen qualities such as age, maturity and other morphological and physiological peculiarities. Environmental fluctuations have a great influence on the individuals in early stages of development and have little influence on the vital activity of mature individuals. The fishery revenue was chosen as an optimality criterion. The main control characteristic is fishing effort. We have chosen quadratic dependence of fishing revenue on the fishing effort according to accepted economic ideas stating that the expenses grow with the production volume. The model study shows that the population structure ensures the increased population stability. The growth and drop out of the individuals’ due to natural mortality smoothens the oscillations of population density arising from the strong influence of the fluctuations of environment on young individuals. The smoothing part is played by diffusion component of the growth processes. The fishery in its turn smooths the fluctuations (including random fluctuations) of the environment and has a substantial impact upon the abundance of fry and the subsequent population dynamics. The optimal time-dependent fishing effort strategy was compared to stationary fishing effort strategy. It is shown that in the case of quickly changing habitat conditions and stochastic dynamics of population replenishment there exists a stationary fishing effort having approximately the same efficiency as an optimal time-dependent fishing effort. This means that a constant or weakly varying fishing effort can be very efficient strategy in terms of revenue.

Numerical study of unsteady mixed convection in an open partially porous horizontal channel with a heatgenerating source was performed. The outer surfaces of horizontal walls of finite thickness were adiabatic. In the channel there was a Newtonian heat-conducting fluid with a temperature-dependent viscosity. The discrete heatconducting and heat-generating source is located inside the bottom wall. The temperature of the fluid phase was equal to the temperature of the porous medium, and calculations were performed using the local thermal equilibrium model. The porous insertion is isotropic, homogeneous and permeable to fluid. The Darcy–Brinkman model was used to simulate the transport process within the porous medium. Governing equations formulated in dimensionless variables “stream function – vorticity – temperature” using the Boussinesq approximation were solved numerically by the finite difference method. The vorticity dispersion equation and energy equation were solved using locally one-dimensional Samarskii scheme. The diffusive terms were approximated by central differences, while the convective terms were approximated using monotonic Samarskii scheme. The difference equations were solved by the Thomas algorithm. The approximated Poisson equation for the stream function was solved separately by successive over-relaxation method. Optimal value of the relaxation parameter was found on the basis of computational experiments. The developed computational code was tested using a set of uniform grids and verified by comparing the results obtained of other authors.

Numerical analysis of unsteady mixed convection of variable viscosity fluid in the horizontal channel with a heat-generating source was performed for the following parameters: $\mathrm{Pr} = 7.0$, $\varepsilon = 0.8$, $\mathrm{Gr} = 10^5$, $C = 0-1$, $10^{-5} < \mathrm{Da} < 10^{-1}$, $50 < \mathrm{Re} < 500$, $\delta = l/H = 0.6-3$. Distributions of the isolines of the stream function, temperature and the dependences of the average Nusselt number and the average temperature inside the heater were obtained in a steady-state regime, when the stationary picture of the flow and heat transfer is observed. As a result we showed that an addition of a porous insertion leads to an intensification of heat removal from the surface of the energy source. The increase in the porous insertion sizes and the use of working fluid with different thermal characteristics, lead to a decrease in temperature inside the source.

Ultrasound examination of material properties is a precision method for determining their elastic and strength properties in connection with the small wavelength formed in the material after impact of a laser beam. In this paper, the wave processes arising during these measurements are considered in detail. It is shown that full-wave numerical modeling allows us to study in detail the types of waves, topological characteristics of their profile, speed of arrival of waves at various points, identification the types of waves whose measurements are most optimal for examining a sample made of a specific material of a particular shape, and to develop measurement procedures.

To carry out full-wave modeling, a grid-characteristic method on structured grids was used in this work and a hyperbolic system of equations that describes the propagation of elastic waves in the material of the thin plate under consideration on a specific example of a ratio of thickness to width of 1:10 was solved.

To simulate an elastic front that arose in the plate due to a laser beam, a model of the corresponding initial conditions was proposed. A comparison of the wave effects that arise during its use in the case of a point source and with the data of physical experiments on the propagation of laser ultrasound in metal plates was made.

A study was made on the basis of which the characteristic topological features of the wave processes under consideration were identified and revealed. The main types of elastic waves arising due to a laser beam are investigated, the possibility of their use for studying the properties of materials is analyzed. A method based on the analysis of multiple waves is proposed. The proposed method for studying the properties of a plate with the help of multiple waves on synthetic data was tested, and it showed good results.

It should be noted that most of the studies of multiple waves are aimed at developing methods for their suppression. Multiple waves are not used to process the results of ultrasound studies due to the complexity of their detection in the recorded data of a physical experiment.

Due to the use of full wave modeling and analysis of spatial dynamic wave processes, multiple waves are considered in detail in this work and it is proposed to divide materials into three classes, which allows using multiple waves to obtain information about the material of the plate.

The main results of the work are the developed problem statements for the numerical simulation of the study of plates of a finite thickness by laser ultrasound; the revealed features of the wave phenomena arising in plates of a finite thickness; the developed method for studying the properties of the plate on the basis of multiple waves; the developed classification of materials.

The results of the studies presented in this paper may be of interest not only for developments in the field of ultrasonic non-destructive testing, but also in the field of seismic exploration of the earth's interior, since the proposed approach can be extended to more complex cases of heterogeneous media and applied in geophysics.

Inverse geophysical problems are difficult to solve due to their mathematically incorrect formulation and large computational complexity. Geophysical exploration in frontier areas is even more complicated due to the lack of reliable geological information. In this case, inversion methods that allow interpretation of several types of geophysical data together are recognized to be of major importance. This paper is dedicated to one of such inversion methods, which is based on minimization of the determinant of the Gram matrix for a set of model vectors. Within the framework of this approach, we minimize a nonlinear functional, which consists of squared norms of data residual of different types, the sum of stabilizing functionals and a term that measures the structural similarity between different model vectors. We apply this approach to seismic and electromagnetic synthetic data set. Specifically, we study joint inversion of acoustic pressure response together with controlled-source electrical field imposing structural constraints on resulting electrical conductivity and P-wave velocity distributions.

We start off this note with the problem formulation and present the numerical method for inverse problem. We implemented the conjugate-gradient algorithm for non-linear optimization. The efficiency of our approach is demonstrated in numerical experiments, in which the true 3D electrical conductivity model was assumed to be known, but the velocity model was constructed during inversion of seismic data. The true velocity model was based on a simplified geology structure of a marine prospect. Synthetic seismic data was used as an input for our minimization algorithm. The resulting velocity model not only fit to the data but also has structural similarity with the given conductivity model. Our tests have shown that optimally chosen weight of the Gramian term may improve resolution of the final models considerably.

We present a physico-mathematical statement of coupled geometrical and gas dynamics problem of intrachamber processes simulation and calculation of main internal ballistics characteristics of solid rocket motors in axisymmetric approximation. Method and numerical algorithm of solving the problem are described in this paper. We track the propellant burning surface using the level set method. This method allows us to implicitly represent the surface on a fixed Cartesian grid as zero-level of some function. Two-dimensional gas-dynamics equations describe a flow of combustion products in a solid rocket motor. Due to inconsistency of domain boundaries and nodes of computational grid, presence of ghost points lying outside the computational domain is taken into account. For setting the values of flow parameters in ghost points, we use the inverse Lax – Wendroff procedure. We discretize spatial derivatives of level set and gas-dynamics equations with standard WENO schemes of fifth and third-order respectively and time derivatives using total variation diminishing Runge –Kutta methods. We parallelize the presented numerical algorithm using CUDA technology and further optimize it with regard to peculiarities of graphics processors architecture.

Created software package is used for calculating internal ballistics characteristics of nozzleless solid rocket motor during main firing phase. On the base of obtained numerical results, we discuss efficiency of parallelization using CUDA technology and applying considered optimizations. It has been shown that implemented parallelization technique leads to a significant acceleration in comparison with central processes. Distributions of key parameters of combustion products flow in different periods of time have been presented in this paper. We make a comparison of obtained results between quasione-dimensional approach and developed numerical technique.