Journal Issue: Научная визуализация
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Volume
2024-16
Number
4
Issue Date
Journal Title
Journal ISSN
2079-3537
Том журнала
Том журнала
Научная визуализация
(2024-16)
Статьи
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Modeling and Visualization of Complex Shaped Surfaces Using Interpolation Curves
(НИЯУ МИФИ, 2024) Konopatskiy, E. V.; Bezdytniy, A. A.
This article presents an approach to modeling and visualizing surfaces of complex shapes using interpolation curves with predetermined geometric properties. A modified Bezier curve of n-order was used as interpolation curves. Modification of a Bezier arc into an interpolation curve is possible both with and without preserving tangents. When preserving tangents, the Bezier arc retains its properties as a contour arc and acquires the ability to pass through preset points. The considered modification is possible in several variations: universal, based on the uniform distribution of the parameter during the modification process, and adaptive, when the parameter values are adapted to the initial data. The use of interpolation curves makes it possible to implement a special case of the moving simplex method, an analogue of which in geometric modeling and computer-aided design systems is the section operation (or lofting). The difference is that a continuous curve is used as a generating surface instead of a piecewise one. To ensure the functionality of such a connection, we give examples of models of the surface of an onion dome and a vase using various guides. An analysis of the obtained results was carried out. The introduction of research results into CAD/CAM will significantly expand their tools in terms of shape formation and visualization of surfaces and bodies that have predetermined geometric requirements.
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A High-Level Adaptation Toolkit for Unified Integration of Software Systems with Neural Interfaces
(НИЯУ МИФИ, 2024) Chuprina, S. I.; Labutin, I. A.
The paper is devoted to the urgent problem of automating the process of integrating different types of neurointerfaces into the infrastructure of the Internet of Things. Due to the low-level nature of these devices and related tools, integrating neurointerfaces with a wide range of IoT devices is a complex task requiring specialized knowledge and skills in the fields of neuroscience and signal processing. To tackle the significant challenge of automating such kind integration we continue to improve our previously proposed ontology-driven methods and tools for seamless integration of software systems with neural interfaces in a unified way. The presented notable improvements include the introduction of a new data processing pipeline that utilizes a portable device to validate the effectiveness of the system and the development of an intuitive graphical user interface enabling real-time data visualization facilities that provides an easy and understandable feedback.
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Integrating Scientific Visualization in the Assessment of Openfoam Solvers for the Flow Around a Spherically Blunted Cone
(НИЯУ МИФИ, 2024) Bondarev, A. E.; Kuvshinnikov, A. E.
This study presents a comprehensive comparative analysis of four OpenFOAM solvers for simulating supersonic flow around a Spherically Blunted Cone. Utilizing the generalized computational experiment technique, we evaluated solver performance across varying Mach numbers and cone half-angles. The research aimed to provide clear recommendations for solver selection in high-speed flow simulations. Results show that rhoCentralFoam exhibited the lowest deviation from the exact solution, followed closely by pisoCentralFoam. The sonicFoam solver demonstrated limitations at higher Mach numbers. The QGDFoam solver, while showing promise, requires further optimization of its smoothing parameter for improved accuracy. This study offers valuable insights for OpenFOAM users, enabling them to make informed decisions when choosing solvers for compressible gas dynamics problems.
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Experience of Constructing and Carrying Out the R&D "Scientific Visualization and Visual Analytics" at RTU-MIREA in 2024
(НИЯУ МИФИ, 2024) Bondarev, A. E.
This work presents the experience of constructing and conducting the research project "Scientific Visualization and Visual Analytics" at RTU-MIREA in 2024. The research project was conducted for 3rd-year students of the Department of Higher Mathematics of the Institute of Artificial Intelligence at RTU-MIREA. The construction and organization of the research project are described. Examples of tasks and their implementation are given. This work may be of interest for teaching similar disciplines in this subject area.
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Event Analysis: Application in Social Forecasting
(НИЯУ МИФИ, 2024) Korenkova, T. V.; Artamonov, A. A.; Ulizko, M. S.; Артамонов, Алексей Анатольевич; Улизко, Михаил Сергеевич
Monitoring the interrelationships between social events and phenomena and forecasting the dynamics of their changes are necessary in the conditions of instability of the modern world. There are many separate methods of analysis for social forecasting, however, for this research, the method of event analysis has been chosen, which is insufficiently considered in the scientific literature within the framework of this task, but has high potential. The purpose of the article is to adapt the event analysis methodology for its use as a social forecasting tool. The main data for the study was collected from the Russian information and news resource in the period 2020-2023. Based on the classical methodology of event analysis, the classifiers presented in this paper in the form of social spheres are defined in the research. As part of the analytical comparison stage, a graph analysis was carried out (graphs of relationships between categories were constructed, central nodes-categories were identified); time series analysis was performed (segmentation of time series by the PELT algorithm, clustering of time series by the k-means algorithm); key terms for press events were defined. The final product is an analytical dashboard with filters, statistics and interactive graphs. The analytical dashboard makes it possible to compare data in a static and dynamic state, to draw conclusions about the past and future states of objects of social forecasting. The main result of the research is the event analysis methodology developed by the author, which can be used for a comprehensive analysis of news streams, adapted to the necessary categories representing a certain entity or sphere, and applied in various social organizations or monitoring services.