Academic literature on the topic 'Computer Simulation Models -Network Forming Liquids'

With the rapid development of the Internet of Things (IoT), the physical system and the network space are further deeply integrated, forming a larger-scale IoT heterogeneous fusion system. The attack mode considered in the security mechanism research of traditional large-scale complex systems is relatively simple; only simple attack types such as random attacks on physical systems or network systems are considered. In addition, existing attack modalities such as selectivity, locality, and distribution cannot fully consider the characteristics of security threats in the IoT system. In this paper, for large-scale heterogeneous IoT system scenarios, attackers can attack network systems or physical systems through cyberspace. We conduct situational awareness analysis on important traffic nodes or backbone nodes and study the cascading failures of two interdependent heterogeneous space systems. In view of the existence of such targeted attack threats in large-scale IoT heterogeneous systems, we focus on security assessment and risk prediction issues. First, this paper analyzes and models different IoT heterogeneous systems. Then using the penetration theory, we analyze the cascading failure process step by step and obtain the critical threshold for system collapse failure. Finally, we further verify the correctness of the theoretical values through simulation to effectively analyze and illustrate the reliability of the parameters affecting the system risk. The experimental results show that the large-scale IoT heterogeneous system presents a first-order discontinuous transition value near the critical threshold and the power-law index of the SF network has little effect on the system security.

Numerical methods based on finite element (FE) have proven their efficiency for many years in the thermomechanical simulation of forming processes. Nevertheless, the application of these methods to new materials requires the identification and implementation of constitutive and flow laws within FE codes, which sometimes pose problems, particularly because of the strongly non-linear character of the behavior of these materials. Computational techniques based on machine learning and artificial neural networks are becoming more and more important in the development of these models and help the FE codes to integrate more complex behavior. In this paper, we present the development, implementation and use of an artificial neural network (ANN) based flow law for a GrC15 alloy under high temperature thermomechanical solicitations. The flow law modeling by ANN shows a significant superiority in terms of model prediction quality compared to classical approaches based on widely used Johnson–Cook or Arrhenius models. Once the ANN parameters have been identified on the base of experiments, the implementation of this flow law in a finite element code shows promising results in terms of solution quality and respect of the material behavior.

The problem of multivariate nature is formed and solved, which is related to the modeling of logistics actions regarding various military equipment and weapons that enter the zone of military conflict. The relevance of the research is related to the comprehensive solution to the problem of the logistical nature of the supply and mastering modern various weapons by the military to create parity of forces in the military conflict zone. The current study creates a complex of logistic methods and models that allow analyzing training of the military, supply of weapons, ammunition and spare parts to the zone of military conflict, for the successful implementation of the goals of the military operation. This article analyzes the problem of using modern and diverse military equipment, which needs to be solved by systematically presenting military training in logistics, supplying various weapons from various manufacturers to the area of combat operations. The optimization model has been created to select and justify the composition of suppliers of weapons, spare parts and ammunition, in the context of risks that arise in the production and transportation of military cargo in a heterogeneous transport network. Optimization is performed in conditions of conflicting criteria: the number of new weapons; time and costs for the production and supply of military equipment; logistical risks. To study dynamic processes in the logistics of supplying weapons, spare parts and ammunition, a model has been created that allows, with the help of simulation agents, the investigation of the paths of movement of military cargo under the conditions of military threats and possible excitation of critical vulnerabilities in the heterogeneous transport supply network. An algorithm for forming the optimal delivery route at the minimum time under risks has been developed. Simulation modeling is used to estimate the movement time of military cargo, delays in supply, accumulation of risks in cargo transportation, consequences of threats and vulnerabilities in supply logistics, etc. This study examines the process of training the military by mastering new competencies for the use of various modern weapons in combat conditions. Simultaneously, the short terms of training of military personnel and the logistics of their transportation to training centers are considered subject to the threats and risks of wartime. The effectiveness of the proposed approach is ensured by a systematic representation of the logistics of supplying various weapons, spare parts and ammunition to the conflict zone, and a comprehensive solution to the research tasks set. The scientific novelty of the conducted research is associated with the development of new methods and models based on system analysis. The following methods were used: simulation modeling, models for optimizing, competence model for acquiring new knowledge by the military personnel. The results of the study should be used to select and justify suppliers of new diverse weapons and military equipment, train the military to use modern kinds and types of weapons, plan routes and schedules for the supply of military cargo to the area of combat operations, in conditions of wartime threats.

In metal forming, the plastic behavior of metallic alloys is directly related to their formability, and it has been traditionally characterized by simplified models of the flow curves, especially in the analysis by finite element simulation and analytical methods. Tools based on artificial neural networks have shown high potential for predicting the behavior and properties of industrial components. Aluminum alloys are among the most broadly used materials in challenging industries such as aerospace, automotive, or food packaging. In this study, a computer-aided tool is developed to predict two of the most useful mechanical properties of metallic materials to characterize the plastic behavior, yield strength and ultimate tensile strength. These prognostics are based on the alloy chemical composition, tempers, and Brinell hardness. In this study, a material database is employed to train an artificial neural network that is able to make predictions with a confidence greater than 95%. It is also shown that this methodology achieves a performance similar to that of empirical equations developed expressly for a specific material, but it provides greater generality since it can approximate the properties of any aluminum alloy. The methodology is based on the usage of artificial neural networks supported by a big data collection about the properties of thousands of commercial materials. Thus, the input data go above 2000 entries. When the relevant information has been collected and organized, an artificial neural network is defined, and after the training, the artificial intelligence is able to make predictions about the material properties with an average confidence greater than 95%.

The performance of this study involves the use of the zoning method based on the principle of the hierarchical relationship between probabilities. This paper proposes an analytical model allowing for the design of information and analysis platforms in intelligent transport systems. The proposed model uses a synthesis of methods for managing complex systems’ structural dynamics and solves the problem of achieving the optimal balance between the information situations existing for the object and the subject under analysis. A series of principles are formulated that govern the mathematical modeling of information and analysis platforms. Specifically, these include the use of an object-oriented approach to forming the information space of possible decisions and the division into levels and subsystems based on the principles of technology homogeneity and information state heterogeneity. Using the proposed approach, an information and analysis platform is developed for sustainable transportation system management, that allows for the objective, multivariate forecasting-based record of changes in the system’s variables over time for a particular process, and where decision-making simulation models can be adjusted in relation to a particular process based on an information situation existing for a particular process within a complex transport system. The study demonstrates a mathematical model that solves the optimal balance problem in organizationally and technically complex management systems and is based on vector optimization techniques for the most optimal decision-making management. The analysis involves classical mathematical functions with an unlimited number of variables including traffic volume, cargo turnover, safety status, environmental performance, and related variables associated with the movement of objects within a transport network. The study has produced a routing protocol prescribing the optimal vehicle trajectories within an organizationally and technically complex system exposed to a substantial number of external factors of uncertain nature.

Introduction. It is obvious that in the near future, the issues of equipping moving robotic systems with autonomous control elements will remain relevant. This requires the development of models of group pursuit. Note that optimization in pursuit tasks is reduced to the construction of optimal trajectories (shortest trajectories, trajectories with differential constraints, fuel consumption indicators). At the same time, the aspects of automated distribution by goals in group pursuit were not considered. To fill this gap, the presented piece of research has been carried out. Its result should be the construction of a model of automated distribution of pursuers by goals in group pursuit.Materials and Methods. A matrix was formed to study the multiple goal group pursuit. The control parameters for the movement of the pursuers were modified according to the minimum curvature of the trajectory. The methods of pursuit and approach were considered in detail. The possibilities of modifying the method of parallel approach were shown. Matrix simulation was used to build a scheme of multiple goal group pursuit. The listed processes were illustrated by functions in the given coordinate systems and animation. Block diagrams of the phase coordinates of the pursuer at the next step, the time and distance of the pursuer reaching the goal were constructed as a base of functions. In some cases, the location of targets and pursuers was defined as points on the circle of Apollonius. The matrix was formed by samples corresponding to the distribution of pursuers by goals.Results. Nine variants of the pursuit, parallel, proportional and three-point approach on the plane and in space were considered. The maximum value of the goal achievement time was calculated. There were cases when the speed vector of the pursuer was directed arbitrarily and to a point on the Apollonius circle. It was noted that the three-point approach method was convenient if the target was moving along a ballistic trajectory. To modify the method of parallel approach, a network of parallel lines was built on the plane. Here, the length of the arc of the line (which can be of any shape) and the array of reference points of the target trajectory were taken into account. An equation was compiled and solved with these elements. On an array of samples with corresponding time values, the minimum time was found, i.e., the optimal time for simultaneous group achievement of multiple goals was determined. For unified access to the library, the control vector was expressed through a one-parameter family of parallel planes. A library of calculations of control vectors was formed. An example of applying matrix simulation to group pursuit was shown. A scheme of group pursuit of multiple goals was presented. For two goals and three pursuers, six samples corresponding to the distribution of pursuers by goals were considered. The data was presented in the form of a matrix. Based on the research results, the computer program was created and registered – “Parallel Approach on Plane of Group of Pursuers with Simultaneous Achievement of the Goal”.Discussions and Conclusion. The methods of using matrices in modeling group pursuit were investigated. The possibility of modifying the method of parallel approach was shown. Matrix simulation of group pursuit enabled to build its scheme for a set of purposes. The matrix of the distribution of pursuers by goals would be generated at each moment of time. Methods of forming matrices of the distribution of pursuers and targets are of interest in the design of virtual reality systems, for tasks with simulating the process of group pursuit, escape, evasion. The dynamic programming method opens up the possibility of automating the distribution with optimization according to the specified parameters under the formation of the matrix of the distribution of pursuers by goals.

How specific features of the environment are represented in the mammalian brain is an important unexplained mystery in neuroscience. Visual information is considered to be captured most preferentially by the brain. As one of the visual information elements, motion direction in the receptive field is thought to be collected already at the retinal direction-selective ganglion cell (DSGC) layer. However, knowledge of direction-selective (DS) mechanisms in the retina has remained only at a cellular level, and there is a lack of complete direction-sensitivity understanding in the visual system. Previous studies of DS models have been limited to the stage of one-dimensional black-and-white (binary) images or still lack biological rationality. In this paper, we innovatively propose a two-dimensional, eight-directional motion direction detection mechanism for grayscale images called the artificial visual system (AVS). The structure and neuronal functions of this mechanism are highly faithful to neuroscientific perceptions of the mammalian retinal DS pathway, and thus highly biologically reasonable. In particular, by introducing the horizontal contact pathway provided by horizontal cells (HCs) in the retinal inner nuclear layer and forming a functional collaboration with bipolar cells (BCs), the limitation that previous DS models can only recognize object motion directions in binary images is overcome; the proposed model can solve the recognizing problem of object motion directions in grayscale images. Through computer simulation experiments, we verified that AVS is effective and has high detection accuracy, and it is not affected by the shape, size, and location of objects in the receptive field. Its excellent noise immunity was also verified by adding multiple types of noise to the experimental data set. Compared to a classical convolutional neural network (CNN), it was verified that AVS is completely significantly better in terms of effectiveness and noise immunity, and has various advantages such as high interpretability, no need for learning, and easy hardware implementation. In addition, activation characteristics of neurons in AVS are highly consistent with those real in the retinal DS pathway, with strong neurofunctional similarity and brain-like superiority. Moreover, AVS will also provide a novel perspective and approach to understanding and analyzing mechanisms as well as principles of mammalian retinal direction-sensitivity in face of a cognitive bottleneck on the DS pathway that has persisted for nearly 60 years.

The article presents a solution to the problem of synthesizing training tasks and data arrays when organizing a computer training platform for conducting practical exercises to investigate information security incidents. Two main stages of the synthesis of the background and situa-tional components of the conditionally real data arrays based on the structural-parametric model of interaction between users of information and telecommunication services are pro-posed: the formation of static and dynamic components. 14КОМПЛЕС НЫЙИ. ТОАИЦ-МЛИМПЧ К ЕЛЙИДЗ-ВЕИЛЛИУ МЙОДО Р 1Ь35Х / 2020Вступление в силу Федерального закона «О безопасности критической информацион-ной инфраструктуры Российской Федера-ции» свидетельствует об актуальности и зна-чимости решения задачи по обнаружению, предупреждению и ликвидации последствий компьютерных атак и реагирования на ком-пьютерные инциденты. Условием качествен-ного решения данных задач является практи-ко-ориентированная профессиональная под-готовка соответствующих специалистов. Для организации и проведения практи-ческих занятий по расследованию инциден-тов информационной безопасности в сетях документальной электросвязи и сети Интер-нет как на потоках магистратуры по направ-лению «Информационная безопасность», так и на потоках специалитета «Информацион-ная безопасность телекоммуникационных систем» и «Информационно-аналитические системы безопасности» необходимо созда-ние учебного компьютерного полигона, осна-щенного современными образцами инфор-мационно-аналитических систем безопасно-сти (далее – ИАСБ), такими как IBM I21, МФИ СОФТ «Январь»2, Lampyre3, Gephi4 и др. ИАСБ – это аппаратно-программные ком-плексы для проведения поисково-аналитиче-ской работы, имеющие возможность нака-пливать и анализировать данные о взаимо-действии пользователей информационно-те-1 http://www.ibm.com/software/ products/ru/analysts-notebook2 http://www.mfisoft.ru/direction/sorm/sorm-3/3 http://www.lampyre.io4 http://www.gephi.orgлекоммуникационных сервисов (далее – ИТ-сервисов). Однако подключение учебных ИАСБ к действующему оборудованию опера-торов связи, являющемуся источником ин-формации о взаимодействии пользователей ИТ-сервисов, невозможно в соответствии со ст. 64 Федерального закона «О связи». Также отсутствует возможность применения насто-ящих массивов биллинговой информации в силу того, что такие массивы содержат персо-нальные данные пользователей, а доступ к ним ограничен законодательно. Обзор литературы позволяет сделать вы-вод об отсутствии готовых методов и алгорит-мов генерации массивов данных, отражающих взаимодействие пользователей ИТ-сервисов.Для решения данной проблемы при соз-дании учебного компьютерного полигона по расследованию инцидентов информацион-ной безопасности в учебно-научном центре «Информационная безопасность» ИРИТ-РтФ УрФУ им. первого Президента России Б.Н. Ельцина разработано программное обеспе-чение (далее – ПО). Данное ПО работает в со-ответствии с созданной структурно-параме-трической моделью взаимодействия пользо-вателей в ИТ-сервисах и позволяет синтези-ровать массивы условно-реальных данных. Файлы, содержащие сгенерированные мас-сивы, в дальнейшем загружаются в базу дан-ных ИАСБ для проведения практических за-нятий по решению поисково-аналитических задач. На текущем этапе разработки ПО спо-собно генерировать массивы условно-реаль-ных данных о взаимодействии пользователей социальных сетей и сетей мобильной связи.Static components are synthesized based on the method of forming the structure of social graphs using a composition of models for constructing complex networks with various struc-tural parameters: the Watts-Strogatz model is used for a mobile communication service, and the Barabashi-Albert model is used for a social network service. To preserve the relationship between users in various services, a method is proposed for determining the largest common part of social graphs, based on the mutual differentiation of vertices and the allocation of a partial isomorphism of the compared graphs. When generating vertex attributes, the method of searching for social groups (families) is used, based on the Bron-Kerbosch algorithm for find-ing a click of a given size in a graph.For the synthesis of dynamic components of data arrays that describe the performance of communication events, the mathematical apparatus of color Petri nets is used. An interaction event in information and telecommunication services is represented in the form of a Petri net label, which contains the necessary set of parameters, depending on the type of service. It is proposed to use the structural, event, social and temporal statistical characterist

PurposeHydrofracturing technology has been widely used in tight oil and gas reservoir exploitation, and the fracture network formed by fracturing is crucial to determining the resources recovery rate. Due to the complexity of fracture network induced by the random morphology and type of fluid-driven fractures, controlling and optimising its mechanisms is challenging. This paper aims to study the types of multiscale mode I/II fractures, the fluid-driven propagation of multiscale tensile and shear fractures need to be studied.Design/methodology/approachA dual bilinear cohesive zone model (CZM) based on energy evolution was introduced to detect the initiation and propagation of fluid-driven tensile and shear fractures. The model overcomes the limitations of classical linear fracture mechanics, such as the stress singularity at the fracture tip, and considers the important role of fracture surface behaviour in the shear activation. The bilinear cohesive criterion based on the energy evolution criterion can reflect the formation mechanism of complex fracture networks objectively and accurately. Considering the hydro-mechanical (HM) coupling and leak-off effects, the combined finite element-discrete element-finite volume approach was introduced and implemented successfully, and the results showed that the models considering HM coupling and leak-off effects could form a more complex fracture network. The multiscale (laboratory- and engineering-scale) Mode I/II fractures can be simulated in hydrofracturing process.FindingsBased on the proposed method, the accuracy and applicability of the algorithm were verified by comparing the analytical solution of KGD and PKN models. The effects of different in situ stresses and flow rates on the dynamic propagation of hydraulic fractures at laboratory and engineering scales were investigated. when the ratio of in situ stress is small, the fracture propagation direction is not affected, and the fracture morphology is a cross-type fracture. When the ratio of in situ stress is relatively large, the propagation direction of the fracture is affected by the maximum in situ stress, and it is more inclined to propagate along the direction of the maximum in situ stress, forming double wing-type fractures. Hydrofracturing tensile and shear fractures were identified, and the distribution and number of each type were obtained. There are fewer hydraulic shear fractures than tensile fractures, and shear fractures appear in the initial stage of fracture propagation and then propagate and distribute around the perforation.Originality/valueThe proposed dual bilinear CZM is effective for simulating the types of Mode I/II fractures and seizing the fluid-driven propagation of multiscale tensile and shear fractures. Practical fracturing process involves the multi-type and multiscale fluid-driven fracture propagation. This study introduces general fluid-driven fracture propagation, which can be extended to the fracture propagation analysis of potential fluid fracturing, such as other liquids or supercritical gases.

Abstract In recent years, artificial intelligence has gradually become the core driving force of a new round of scientific and technological revolution and industrial transformation, and is exerting a profound impact on all aspects of human life. With the rapid development of Internet big data and high-performance parallel computing, relevant research in computer vision has made significant progress in the past few years, becoming one of the important application branches in the field of artificial intelligence. The exercise of image classification forming part of computer vision tasks involves a large amount of computation, and training based on traditional deep learning (DL) classification models typically involves slow training and low accuracy in many parameters. Thus, in order to solve these problems, an image classification model based on DL and SAE network was proposed. Firstly, the main research of computer vision task-image classification is introduced in detail. Then, the combination framework of deep neural network and SAE network is built. At the same time, the deep neural network was used to carry out convolution operation of the parameters learned by SAE and extract each feature of the image with neurons, so as to improve the training accuracy of the deep neural network. Finally, the traditional deep neural network and SAE network were used for comparative experiment and analysis. Experimental results show that the proposed method has a certain degree of improvement in image classification accuracy compared with traditional deep neural network and SAE network, and the accuracy reaches 97.13%.

For the last decade, many researchers have been working to develop self-healing materials, and have obtained good results in the field of polymers, these components with microencapsulated healing agent have exhibited noticeable mechanical performance and regenerative property The research described in this paper applies the concept of self healing to simulate self healing polymer matrix composites, with the aid of models developed by the authors for the manufacturing processes and self-healing behavior. The development of self-healing is a novel idea that has not been totally explored in great detail yet. The concept of self-healing described in this paper consists of simulation of a healing agent dicyclopentadiene (DCPD) inside of a microvascular network within a polymer matrix coating with catalyst forming a self-healing composite (SHC). When this SHC is damaged or cracked, the healing agent by capillary action will flow inside of the microvascular network; when the liquid enter in contact with the catalyst will form a polymer structure and sealing the crack. The study consists of theoretical analysis and Computational Fluid Dynamics of a self-healing polymer. The objective of the study reported here was to find the influence and efficiency of the microvascular network in healing a polymer matrix. To check this effect a computational model was created to simulate the healing treatment, thus a crack was created on the matrix surface piercing the microvascular network filled with healing agent and the method to simulate healing behavior of the composite allows assessment of the effects of the autonomously repairing repeated damage events.

SKYTHIA is a computer code for computational simulation of transient multi-phase flows based on three multi-component velocity fields in a porous structure that may change its geometry in time. The foundation of the computer code SKYTHIA allows applications for mathematical simulation of a variety of processes. From • two-phase gas-plasma multi-component hydrogen detonation in pipe-network with dissociation of the gases, • through condensation water-steam shock waves in complex pipe networks, • gas solution and dissolution in liquids, dissolved gas release from water in pipe network and gas-slug formation and transport, • pressure wave propagation, piping force computation and risk analysis in conventional island of 1700 MWe power plant including detailed models of the high pressure turbine, • diesel injection problems, • particles sedimentation in water, • turbulent mixing and transport in a nuclear power plant sump, • termite injection by high pressure steam-hydrogen mixture into air environment, melt-water interaction in postulated SWR 1000 severe accidents, alumina melt jet dropped into a subcooled water, Urania melt jet dropped in water, • void formation in existing-, • or future boiling water reactors, • void fraction and velocity distribution in nuclear reactors with different thermal powers, • modern steam generator simulation, thermal coupling of multi-phase non-equilibrium three fluid non-homogeneous non-equilibrium flow inside the primary piping systems to complete 3D multi-phase non-equilibrium three fluid non-homogeneous non-equilibrium flow inside secondary systems with cyclones and dryers, • volume fraction of steam in family of steam generators with different power, • water velocities and void fraction in flooding reservoir for primary emergency condenser being operating on the secondary site as boiler; thermal coupling of multi-phase non-equilibrium three fluid non-homogeneous flow inside the primary piping systems to complete 3D multi-phase non-equilibrium three fluid non-homogeneous flow inside secondary systems, • complete system for moisture separation of typical PWR, dynamic performance: multi-phase non-equilibrium three fluid non-homogeneous flow inside the secondary moisture separation system, • local volume fractions of oxide and sodium liquid as a function of (r, z) in the vertical plane for a fast breeder reactor during melt water interaction; energetic interaction of molten reactor material with liquid sodium in argon environment, • modern pre-heater (condenser) simulation, thermal coupling of single phase flow inside the primary piping systems to complete 3D multi-phase non-equilibrium three fluid non-homogeneous non-equilibrium condensing flow inside secondary systems, etc. All this applications demonstrate the capability of single model architecture to handle different material systems, different intensities of interactions, and large variety of the spatial and temporal scales of the simulated processes. This paper gives brief information about the basic principles used to build SKYTHIA, part of the validation procedure and illustrations of some very complex process simulations.

Флагманом современной географии выступает моделирование географических систем и процессов их функционирования, базирующееся на огромных базах данных и алгоритмах многомерного компьютерного моделирования поведения сложных многосвязных систем. Сам процесс моделирования базируется на мощном аппарате математического анализа и статистической обработки базовых параметров объектов, на основе которых производится построение имитационных моделей их функционирования и развития. Речной бассейн является самым распространенным на поверхности суши природным объектом, обладающий отчетливо выраженными границами, структурной организацией, иерархией, относительной замкнутостью потоков вещества и энергии. При описании структуры водосборного бассейна речной системы традиционно применяются порядковые классификации. Порядковая классификация водотоков базируется на основополагающем свойстве речных потоков образовывать при последовательном слиянии древовидную структуру со ступенчатым нарастанием основных параметров системы. Стабильность структуры при этом поддерживается непрерывной деятельностью мощных потоков вещества и энергии. Широкое применение получила нисходящая порядковая классификация Р. Хортона 7, в основу которой легло положение о том, что неразветвленные элементарные водотоки сходны в разных условиях и должны иметь наименьший 1й порядок, образуя при слиянии водоток 2го порядка, в то время как водотоки 2го порядка образуют водоток 3го порядка и т. д. Также Хортоном, на основе анализа структуры речных сетей и их бассейнов были предложены законы соотношения основных характеристик водотоков разных порядков. Позднее порядковая классификация Хортона была доработана Стралером 6, который исключил понятие главной реки , которая на всем своем протяжении имеет максимальный порядок, хотя структурно состоит из множества разнопорядковых сегментов. Данные классификации сейчас принято рассматривать в едином контексте как классификацию ХортонаСтралера. Еще в XIX веке был высказан тезис о том, что водоразделы и тальвеги являются главными структурными линиями рельефа и находятся в тесной взаимосвязи 2, определяя распределение потоков вещества и энергии в водосборном бассейне. С использованием классификации водотоков ХортонаСтралера предложен принцип классификации водоразделов. На основе авторской методики обработки цифровых моделей рельефа (ЦМР) с использованием инструментов ГИС было апробировано использование порядковых характеристик водоразделов для получения детальной информации о вариациях основных характеристик однопорядковых элементов речной сети в зависимости от порядка водораздела в пределах бассейна реки Уссури.The flagship of modern geography is the modeling of geographical systems and the processes of their functioning, based on huge databases and algorithms for multidimensional computer modeling of the behavior of complex multiply connected systems. The modeling process itself is based on a powerful apparatus for mathematical analysis and statistical processing of the basic parameters of objects, based on which simulation models of their functioning and development are built. The river basin is the most widespread natural object on the land surface, which has distinct boundaries, structural organization, hierarchy, and relative isolation of matter and energy flows. In describing the structure of the catchment of a river system, ordinal classifications are traditionally applied. The ordinal classification of watercourses is based on the fundamental property of river flows to form a tree structure with successive merging with a stepwise increase in the main parameters of the system. The stability of the structure is supported by the continuous activity of powerful flows of matter and energy. The descending ordinal classification of R. Horton 7 was widely used, which was based on the proposition that unbranched elementary watercourses are similar under different conditions and should have the smallest 1st order, forming second order watercourses at the time how 2nd order watercourses form a 3rd order watercourse, etc. Also, Horton, based on an analysis of the structure of river networks and their basins, proposed the laws of correlation of the main characteristics of watercourses of different orders. Later, the Horton ordinal classification was finalized by A. Straler 6, who excluded the concept of the main river, which along its entire length has the maximum order, although it structurally consists of many differentorder segments. Classification data is now considered to be considered in a single context as the HortonStrahler classification. As early as the 19th century, the thesis was expressed that watersheds and thalwegs are the main structural lines of the relief and are closely interconnected 2, determining the distribution of matter and energy flows in the catchment. Using the classification of HortonStrahler watercourses, the principle of the classification of watersheds is proposed. Based on the authors methodology for processing digital elevation models (DEM) using GIS tools, the use of ordinal characteristics of watersheds was tested to obtain detailed information on variations of the main characteristics of singleorder elements of the river network depending on the order of the watershed within the Ussuri River Basin.