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Accepted papers
Method of Searching Optimal Nodes Arrangement of Continuous Function Approximation with Consideration of Space Nonlinearity
E.V. Konopatskiy, D.I. Kislitsyn, A.V. Stepura, O.V. Kotova
Accepted: 2025-07-28
Abstract
A method of searching optimal nodes of approximation realized on the example of Runge function is proposed. The method is based on the use of interpolation algebraic curves in point calculus and is reduced to minimization of the target function of many variables, which provides minimum deviations of the approximating function from the original one. Traditionally, in the process of interpolation, the coefficients of the interpolating function are determined on the basis of the initial points, which does not make it possible to ensure the search for the optimal location of interpolation nodes, since the coordinates of the node points are necessary to determine the coefficients of the interpolating function. The peculiarity of interpolation curves realized in point calculation is that they are obtained by uniform distribution of the parameter along the numerical axis and keep the coordinates of interpolation nodes in the point equation, which makes it possible to set and solve the problem of their optimal location by minimizing the target function. After the realization of the coordinate calculation of the point equation of the interpolation curve, the final result of the approximation of the original function is an algebraic curve given in parametric form, which allows us to use the nonlinearity of space to significantly reduce the degree of the approximating polynomial function. For example, when using Chebyshev nodes, which are considered optimal for approximating the Runge function, at least 20 nodes are needed to achieve a high-quality approximation, which leads to the need to use a polynomial of degree 19. In this case, the MSE is 0.000111. Whereas for the Runge function approximation based on the optimized arrangement of approximation nodes, even when using 6 node points, the MSE is only 0.0000284, which is an order of magnitude lower compared to Chebyshev nodes and allows using two polynomials of degree 5 on each of the coordinate axes instead of one polynomial of degree 19.
COMPARATIVE ANALYSIS OF THE ACCURACY OF OPENFOAM SOLVERS IN SIMULATING SUPERSONIC FLOW OVER A DOUBLE WEDGE
A.E. Bondarev, A.E. Kuvshinnikov, S.V. Andreev , I.G. Ryzhova
Accepted: 2025-07-28
Abstract
This study presents a comparative analysis of the accuracy of different solvers within the OpenFOAM software package for the numerical simulation of supersonic inviscid gas flow over a double wedge. A two-dimensional steady problem of the flow formation with intersecting oblique compression shocks is considered. The comparison involves the standard solvers rhoCentralFoam and sonicFoam as well as the third-party solvers pisoCentralFoam and QGDFoam. The results, presented in tabular form, are visualised as error surfaces. The analysis showed that the rhoCentralFoam solver has the best accuracy, especially at high Mach numbers and large wedge angles. The obtained results can be used in both fundamental research and engineering calculations that require high fidelity in modelling complex flows.
Visualization of Parameters and Results of Modeling Optimal Cargo Transportation Planning Tasks in Unmanned Aircraft Transport Systems
A.G. Podvesovskii, A.A. Filonov, A.A. Zakharova
Accepted: 2025-07-28
Abstract
The peculiarities of unmanned vehicle application in the field of cargo transportation lead to the formulation of new problems for optimising cargo transportation plans, where several types of additional constraints and conditions must be taken into consideration simultaneously. The process of solving such problems requires considering and analysing numerous heterogeneous parameters, which is most effective when done interactively using visualisation techniques. We consider a problem involving the formation of heterogeneous cargo transportation plans using unmanned aerial vehicles, and propose an approach for constructing a visual model to support the interactive setting of problem parameters and to display optimisation results via a visual interface. This approach is based on the concept of visualisation metaphors, including spatial and representational metaphors. The structure and features of the metaphorical representation for different problem formulations and modelling stages are discussed.
Development of a Methodology for the Application of Generative Neural Networks in Creating 3d Models
N.A. Bondareva, A.E. Bondarev, S.V. Andreev, I.G. Ryzhova
Accepted: 2025-07-28
Abstract
The article considers the current scientific and technical problem of integrating generative neural network architectures into the process of automated 3D modeling. Despite significant progress in this area, existing solutions are often characterized by insufficient transparency and limited capabilities of deterministic control by design engineers. In this regard, the concept of an innovative hybrid methodological approach based on the synergistic interaction of intelligent natural language processing systems and verified engineering software packages is proposed. The purpose of the proposed approach is to significantly increase the efficiency and accuracy of the design process by minimizing the likelihood of errors and ensuring the possibility of prompt adjustment at all stages of creating 3D models. The methodology is based on the integration of AI capabilities in the field of semantic analysis and generation of variable design solutions with existing CAD modeling algorithms. The results of experimental verification of the proposed concept are presented, demonstrating a significant reduction in the time spent on creating 3D models compared to traditional methods, which indicates the promise of the developed approach for practical application in engineering activities.
A Hybrid Approach to Color Matching for Metallic Automotive Paint
A.G. Voloboy, S.V. Ershov, V.V. Lyoushkin, A.I. Kuznetsov, V.A. Galaktionov
Accepted: 2025-07-28
Abstract
Accurate color matching for metallic automotive paints is a complex challenge because the paint appearance depends on lighting conditions, viewing angles and the spatial texture created by reflective flakes and pigments. This paper presents a hybrid approach that integrates AI technique with physics-based modeling to address this challenge. The AI component utilizes a multilayer perceptron trained on a proprietary database of real-world automotive refinishing cases. This database, continuously updated through operational deployments, captures practical variables such as pigment batch differences and application techniques, and allows achieving an 85% success rate for standardized pigments and controlled environment. However, for novel or insufficiently characterized pigments, the physics-based component of the hybrid approach becomes critical. Here, the bidirectional reflectance distribution function (BRDF) of metallic paints is calculated by scaling the BRDF of a paint containing only metallic flakes, leveraging the observation that the normalized spectrum of colored metallic paints remains stable across concentrations. This method significantly reduces computational cost compared to full ray tracing while maintaining accuracy. Experimental validation involved calculating paint appearance for various concentrations of aluminum flakes and diffuse pigments and comparing it with measured real paint samples. Results demonstrated strong agreement between calculated and measured spectra. The hybrid approach not only bridges gaps in training data but also offers a practical solution for automotive repairs, where original paint formulations are often unavailable or altered by environmental factors. By combining AI's data-driven strengths with the robustness of physics-based simulations, this work advances the field of automotive paint color matching, enabling faster and more accurate results in real-world applications.
Physics-guided machine learning for predicting gas permeability of standard carbonate core plugs from low-resolution microtomography image stacks
R. I. Kadyrov, T. H. Nguyen, E. O. Statsenko
Accepted: 2025-07-28
Abstract
This study presents a physics-guided workflow for predicting the gas permeability of carbonate reservoirs directly from low-resolution microtomography (µCT) imagery. Standard core plugs were scanned at 34.6–36 µm/voxel, and a total of 52,327 grey-scale slices (737 per plug) were extracted from 71 samples. Each slice was labelled with a synthetic 3D permeability value based on a fractal analytical model and then normalized using either harmonic-mean or bottleneck-based aggregation against experimental plug-scale measurements. The grey-scale images and log-transformed permeability labels were used to train a Swin Transformer model, pre-trained on ImageNet. Two models were developed independently: one using harmonic-mean aggregation and the other using the bottleneck approach. Both models demonstrate stable convergence despite the highly skewed data distribution. The harmonic-mean model achieved R² = 0.904 on the validation set, while the bottleneck model yielded R² = 0.879. Although the higher R² reflects a closer fit to the overall trend, the bottleneck model, in blind testing on ten independent samples (0.4–2300 µm² × 10⁻³), reduced the MAE from 165 to 104 µm² × 10⁻³ (−37 %) and the RMSE from 255 to 140 µm² × 10⁻³ (−45 %) relative to the harmonic-mean model. The method provides a fast and interpretable permeability prediction based solely on raw µCT slices, without requiring image segmentation or 3D reconstruction. The proposed approach demonstrates robust performance across a wide range of standard carbonate plugs and effectively captures permeability trends even in the presence of structural heterogeneity. While samples with extremely large fractures or vugs can introduce local inconsistencies in labelling due to the limitations of slice-based estimation, these cases are rare and can be systematically addressed in future work. Overall, the results highlight the strong potential of physics-guided machine learning to accelerate digital core analysis and provide reliable, image-driven permeability predictions for complex carbonate reservoirs.
Research and application of nanosecond discharges for visualization of structure of supersonic flows
I.V. Mursenkova, A.A. Ivanova, A.S. Sazonov
Accepted: 2025-07-28
Abstract
An experimental study was carried out on the spatial distribution of glow in a nanosecond surface sliding discharge and a combined volume discharge in supersonic air flows around a streamlined axisymmetric body in a channel. The flow in the discharge chamber included shock waves generated by the flow around the body and those reflected from the channel walls. Flow visualization was performed by the direct shadowgraphy and by recording the discharge glow with photo cameras and ICCD camera. Supersonic air flows with Mach numbers of 1.36–1.60 were generated behind plane shock waves with Mach numbers of 3.0–4.4 in a in a rectangular shock tube channel. Discharges were initiated under a voltage pulse of 25 kV either along the surface or within the volume, extending up to 100 mm along the flow direction. Spatial emission characteristics of the discharge initiated at various stages of gas-dynamic flow were analyzed. Digital image processing and analysis of the glow captured during discharge development were carried out and compared with shadowgraphy images of the flow field. A correlation was demonstrated between the emission distribution of the sliding surface discharge in supersonic flows and the state of the boundary layer on the channel wall where the discharge develops. Comparison of volume discharge images with shadowgraphy frames enabled the reconstruction of the three‑dimensional structure of the supersonic flow, featuring a bow shock in front of the body and the oblique shock waves downstream.
Study of a Shock Wave Turbulent Boundary Layer Interaction by Means of Optical Methods
S.S. Popovich, I.A. Znamenskaya, M.I. Muratov, I.A. Zagainov
Accepted: 2025-07-28
Abstract
The velocity and temperature fields of an incident shock wave boundary layer interaction region for a flat plate flow is investigated. The research was carried out on a supersonic wind tunnel of periodic action with a closed working part and an adjustable supersonic nozzle, and impulse shock tube with flow duration up to several milliseconds. The shock system was generated by a wedge mounted at a distance of 20 mm from the upper wall, and by local inhomogeneities of the channel. The thickness of the boundary layer at the beginning of the test section on the upper and lower walls was about 6 mm. Experimental channels are equipped with optical quartz side windows and transparent upper and lower plexiglass sections, which allows the use of panoramic visualization methods. The distribution of the longitudinal and transverse components of the flow velocity in the interaction region of the incident shock wave with a flat plate was determined using the PIV method. The flow pattern in the area of interaction of the incident shock wave with the wall was also visualized using infrared thermography and the IAB-451 shadow device.
Shadow Visualization of Water Droplets Breakup Process in a Laval Nozzle Two-Phase Flow
S.S. Popovich, A.G. Zditovets, U.A. Vinogradov
Accepted: 2025-07-28
Abstract
The results of an experimental study of an air-droplet flow in a flat supersonic Laval nozzle of a periodic-acting wind tunnel are presented. The droplets were fed into the flow using fine spray nozzles installed in the pre-chamber. The working part of the wind tunnel has a rectangular cross-section with dimensions of 70x98 mm. The Mach number at the nozzle exit varied in the range 2,0-3,0 due to the mechanism of compression of the nozzle critical section, the total pressure in the pre–chamber was 450-550 kPa, and the total temperature was 288-298 K. The initial concentration of the dispersed (liquid) phase in the flow and the initial droplet size distribution were varied by changing the pressure drop at the spray nozzles. When studying the dynamics of droplet crushing in the critical section of the nozzle, the SSP (shadow photography) laser method was used, which includes: a flow illumination system based on a Beamtech dual-pulse Nd:YAG laser with a wavelength of 532 nm, a 7-joint optical arm for delivering laser radiation, a light-scattering screen for creating a backlight with alcohol solution of rhodamine phosphor, a digital CCD camera with a frame rate at full resolution up to 15 Hz, an Infinity K2 DistaMax microscope lens and the synchronization processor. A series of snapshots of the instantaneous state of the air-droplet flow in the critical section and in the expanding part of the Laval nozzle were obtained.
Visualization of Complex Roots for Nonlinear Algebraic Equations
Mehmet Pakdemirli
Accepted: 2025-05-26
Abstract
Visualization of complex roots of a nonlinear algebraic equation is discussed in this work. The method is based on calculating the modulus of the complex valued function and representing it as a surface in a three dimensional space where the axis consist of real and imaginary axis and the modulus function. Since it may be inconvenient to visualize multiple roots in a three dimensional surface, contour plot is suggested as an alternative to visualize better the location of roots. Roots of polynomial functions as well as non-polynomial functions are treated as examples. The contour plot is the best to visualize the complex roots in a single graph.
DATA CLASSIFICATION WITH USING VISUALIZATION TOOLS
Andrey Dzengelewski
Accepted: 2025-04-29
Abstract
This article discusses ways to use visualization tools to build object classifiers during automation of a large enterprise. The proposed approaches allow stakeholders to get a visual representation and participate in the decisions required when building a classifier for large arrays of records.
The use of visualization tools is considered when selecting classification objects, determining the attributes and values of classification attributes, ensuring the convenience of the classifier and implementing conflicting requirements from stakeholders. Among the proposed solutions, the methods of using system classes, building logical and physical models of the classifier, multidimensional classification, attribute-value data model, logical data model for describing the required analytics are described.
The subject area is a classifier of works and services, examples of using the proposed solutions and the results of building a classifier at a large enterprise are given.
Design of a Hybrid Metric for Fingerprint Image Matching: A Grediant, Aczil, and SourceAFIS Approach
Mohammed Abdulameer Aljanabi, Noor Abd Alrazak Shnain
Accepted: 2025-04-29
Abstract
One of the most popular biometric matchings is the fingerprint used for personal matching, verification, and authentication. Numerous fingerprint metrics have been developed to detect various types of fingerprint image distortions. The majority of these metrics are based on a single approach. It is feasible to match a specific person's fingerprint image by comparing images of the same person's fingerprint, which we will discuss in detail in this paper. In this work, we provide an alternative technique by interpolating the Aczel metric with gradient matching and Source Automated Fingerprint Matching System (SourceAFIS) algorithm. The Aczel metric demonstrates strong predictive capabilities in discerning relationships among intensity values within fingerprint images while gradient matching is used to gage the change in contrast and structure in images. SourceAFIS describes fingerprints using high-level abstractions called minutiae, creates edges, matches minutiae and edges, and scores pairings based on random feature likelihood. The combined method has been tested against powerful statistical approaches for image analysis such as gradient matching metric and SourceAFIS matching algorithm. Simulation results using four well-known FVC2000, FVC2002, FVC2004, and FVC2006 image databases prove the effectiveness of the proposed technique achieves better consequences than the current methods in matching fingerprint images.
Using Sperm Imaging with Laser Interference Microscopy for Comprehensive Assessment of the Functional State of Cells during Cryopreservation and under the Action of Molecular Hydrogen
A.V. Deryugina, M.N. Ivaschenko, P.S. Ignatiev, V.B. Metelin
Accepted: 2025-04-29
Abstract
Significant advances have been made in sperm cryopreservation but the search for effective sperm cryopreservation technologies is a pressing issue in modern biology and medicine. The most effective cryopreservation leaves 50-60% of viable cells. The paper discusses the use of molecular hydrogen (H2) as a new approach to enhancing sperm protection during freezing and thawing. H2 is a universal antioxidant and limits damage to biomolecules. Visual registration of spermatozoa under the action of H2 was performed using modern microscopy techniques. Laser interference microscopy was used in the work. Laser interference microscopy records the cell surface architectonics depending on the modulation of the optical density of cellular structures. This visualization option provides information on the metabolic level and expands the possibilities for interpreting experimental results. Sample preparation, dyes, and fixatives are not used in interference visualization. The paper presents an analysis of phase images of spermatozoa during cryopreservation and using H2 as a cryoprotector. Verification of the method for analyzing phase characteristics of spermatozoa as an indicator of the metabolic state of cells was performed by analyzing clinical and laboratory parameters of spermatozoa. The phase height of spermatozoa during cryopreservation decreased, the intensity of energy processes decreased, and the oxidative potential of cells increased. A direct correlation was shown between the phase height of spermatozoa and the concentration of ATP, and an inverse correlation was found from the concentration of malondialdehyde (MDA). The use of H2 determined an increase in the phase height of spermatozoa, an increase in energy metabolism, and a decrease in cell oxidation. Changes in the metabolic activity of spermatozoa under the action of H2 were combined with an improvement in sperm fertility. Thus, phase interference microscopy allows for a qualitative and quantitative assessment of the physiological state of spermatozoa. It is an objective method of vital analysis of complex metabolic activity of cells. It can be used for express diagnostics of their functional state.
Glyph-Based Approach to Web Rendering of Geophysical Fields in Geoinformation Systems
G.R. Vorobeva, A.V. Vorobev, G.O. Orlov
Accepted: 2025-04-29
Abstract
One of the significant problems in visualizing geophysical fields is the inability to simultaneously represent them as an integrated spatial layer, taking into account the complex nature of the parameters being analyzed. Currently, the designated visualization task is solved by decomposing the set of parameters into separate components, followed by rendering spatial layers that are not connected to each other either visually or logically. As a result, information that is important for research or decision-making is lost due to excessive overload of the geopatial image.
The paper proposes an approach to visualizing multicomponent geophysical fields based on graphical primitives called tensor glyphs, which are combined into a single spatial layer to represent several components of the geophysical field. Each individual image is a superellipse, composed of ellipses distributed along the axes and scaled according to the analyzed values, whose intersection points with each other and with the axes provide reference points connected using Lamé curves.
The operability and clarity of the proposed solution are examined using the parameters of the geomagnetic field as an example. Additionally, an analysis of performance metrics for its web implementation is conducted, which allows evaluating the quality of the corresponding solutions.
Pressure-gradient method for the visualization of a wave attractor
Stepan Elistratov
Accepted: 2025-04-13
Abstract
A wave attractor, a phenomenon of self-focusing of internal/inertial waves on a closed trajectory, has recently been widely studied from different viewpoints. How-ever, there is a lack of investigations concerning its visualization. Peculiar set-ups lately studied show that conventional methods need some improvement.
Herewith, in gas dynamics, the Schlieren method, based on the density gradient, is widely used. Concerning incompressible flows, it is inapplicable; however, pressure can be considered instead density. In this work, a pressure gradient is used as a way to visualize an attractor.
Determination of Adiabatic Wall Temperature in High-Speed Gas Flows Using Infrared Thermography
Í.Ñ. Ìàëàñòîâñêèé, Í.À. Êèñåë¸â, À.Ã. Çäèòîâåö, À.Þ. Âèíîãðàäîâ
Accepted: 2025-03-21
Abstract
This paper presents a method for the non-contact determination of the adiabatic wall temperature in high-speed gas flows. The method is based on the processing of a sequence of thermograms obtained using an IR camera, within a program developed in Python 3.10. The approach demonstrated high efficiency when handling large datasets, particularly concerning minimizing temporal and computational demands. The adiabatic wall temperature was determined under both steady-state conditions, directly in the experiment, and transient conditions, through the extrapolation of the heat flux as a function of the current temperature of the examined surface. The effectiveness of this method was demonstrated in the investigation of non-mechanical energy separation in compressible gas flows.
Three-dimensional images of residual strain fields by wavelet transform method
I.V. Laktionov, E.V. Gladkih, A.P. Fedotkin, G.Kh. Sultanova, À.S. Useinov
Accepted: 2025-03-21
Abstract
The accuracy of measuring Vickers hardness values depends on image focusing both during automated determination of residual imprint diagonal lengths and during operator working. Widespread algorithms for image focusing are based on brightness and contrast adjustment. We propose a new approach based on alternative algorithms for more accurate microscope focusing system used in marking imprints after indentation. Implemented algorithms are based on variance, Laplace function and wavelet transform. We select the optimum values of the basis and transform depth when using the wavelet transform. We tested new approach on samples with poor contrast, rough surfaces, and materials with pile-ups occurred in the indentation process. Applying different focusing functions depending on focus position demonstrates a more stable performance of the algorithm with wavelet transform. We also demonstrated obtaining a fully focused frame and a pseudo three-dimensional map of the sample.
Use of Hadamard matrices in single-pixel imaging
Denis V. Sych
Accepted: 2024-08-13
Abstract
Single-pixel imaging is a method of computational imaging that allows to obtain images of objects using a photodetector that does not have spatial resolution. In this method, the object is illuminated by light having a special spatio-temporal structure, — light patterns, and a single-pixel photodetector measures the total amount of light reflected from the object. The possibility of obtaining an image and the image quality are closely related to the properties of the applied patterns and computational algorithms. In this paper, we consider patterns obtained from modified Hadamard matrices and study the features of image calculation using single-pixel imaging. We show the possibility of reducing both the sampling time and the computational resources required to obtain images by modifying the pattern system. The proposed theoretical method can be used in the practical implementation of the single-pixel imaging method in an experiment.
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