Modeling Of Processes Research Articles

STATISTICAL EVALUATION OF PERFORMANCE INDICATORS OF PHOTOVOLTAIC PLANTS AS A SOURCE OF ENERGY FOR WATER DESALINATION IN THE AZOV-BLACK SEA REGION OF UKRAINE

The application of statistical methods for the analysis of random processes to obtain quantitative estimates for the performance indicators of photovoltaic plants as a stochastic energy source is considered. The power generation process is represented by a set of daily random functions with their respective trends and stochastic components. One hour was taken as the minimum stationari-ty interval of trend’s statistical characteristics. A time period of 16 years was studied to obtain statistically stable estimates. The meteorological database SARAH2 was used as a source of hourly data on the density of solar irradiance, ambient temperature and wind speed in the middle part of the Azov-Black Sea region of Ukraine. For mathematical modelling of power generation and electricity production processes, specialized software PVGIS version 5.2 of the European Commission was used. Hourly quantitative estimates of expected daily power generation trends for each month of the year, as well as their correlation functions, were computed. Algorithms were developed and levels of probabilistic assurance for hourly generated power were evaluated. Statistical estimates of the expected daily, monthly, and annual volumes of electricity production by photovoltaic power plants were studied, taking into account the meteorological conditions in the said region.

Применение принципа Понтрягина для оптимального отключения энергетического ядерного реактора

The theory of optimal control is based on two approaches, the dynamic programming method (Bellman equation) and Pontryagin maximum principle. Pontryagin maximum principle is applied in the physics of nuclear reactors when optimizing various transient processes. The mathematical justification of this theory is based on the elements of convex analysis, which is not used by physicists and engineers, so the physical issues are less studied in scientific literature. The subject of the study is a nuclear power reactor of the WWER type. The problem of minimizing its shutdown time, bypassing the iodine pit is solved and it is possible to start up the reactor at any moment after its shutdown. Analytical and numerical methods are used. The paper considers an example of applying the maximum principle for optimal control of the process of shutting down a nuclear reactor bypassing the iodine pit. A physical mathematical model of the Pontryagin principle is formulated. The process of optimal control of reactor shutdown for large and small reactivity margins is justified and calculated. Pontryagin principle does not contain an algorithm to find an optimization process; the stages of the process must be selected based on physical considerations, but these stages must satisfy the specified principle. Based on the Pontryagin principle, the results of the study make it possible to draw up a step-by-step action plan when shutting down a WWER-type reactor with any value of the reactivity margin and its switching is possible at any time after the transition process, which avoids downtime. The proposed plan can be used both in mathematical modeling of transient processes in a reactor and in reactor control systems to improve its controllability and, consequently, to improve safety.

Методология матричного моделирования многокомпонентных многопоточных многоступенчатых энергетических комплексов

Traditionally, heat transfer problems are solved in relation to two-flow systems in which heat exchange is carried out between hot and cold coolants. However, along with two-flow systems, there are often multiflow systems in which the number of coolant flows is three or more. In addition, each energy carrier stream may consist of several components, and the installation may include several stages. Thus, the development of universal approaches and methods for modeling, calculation, and optimization of multi-component multiflow multistage energy complexes within the framework of a unified methodology is an urgent scientific and practical task. A methodology of matrix formalization of modeling heat and mass transfer processes is based on methods and approaches of matrix description of heat and mass transfer systems in energy complexes. The approaches and methods of modeling energy power installations are summarized. Within the framework of the matrix description methodology, the rules and approaches to the development of models of heat and mass transfer processes are formulated in relation to multicomponent multiflow multistage energy complexes. The authors have proposed a solution to the inverse problems with and without considering a phase transition in coolants. Analysis of formulated and solved problems within the framework of the proposed methodology allows us to recommend the use of methods and approaches of matrix modeling of equipment to solve direct and inverse problems for multicomponent multiflow multistage energy complexes for various purposes.

Simulation of the work of glass furnaces with the purpose of searching for reserves and increase their efficiency

The object of research is the operation of a glass furnace. The work involved modeling the operation of a glass furnace by changing the technical and economic indicators of its operation in order to optimize the technological processes of manufacturing glass products, increase the energy efficiency of the process, and reduce the ecological burden on the environment. Glass furnaces are complex heat engineering units that require a large amount of energy to operate. Therefore, increasing their effectiveness is the main task of our research. In the work, computer modeling of thermal processes in the furnace was carried out, heat balances were calculated and analyzed, and the performance of the furnace was analyzed after changing and improving the technological regimes of combustion processes, glass boiling and furnace construction. Studies have shown that in order to increase the technical and economic performance of glass furnaces, it is advisable to conduct additional thermal insulation of the furnace enclosures. The thermal insulation of the vault increases the efficiency of the furnace by 2–3 %, and the thermal insulation of the remaining areas of the furnace in total allows to increase the efficiency of the heating unit up to 3 %. Such measures improve the sanitary and technical working conditions of the staff in the machine-bath shop. Studies have shown that additional heating of the air used for burning fuel significantly increases the efficiency of the furnace. Thus, an increase in air temperature by 100 °C increases the efficiency of the furnace by approximately 2.5 %. However, such a measure is possible with a corresponding increase in the volume of regenerator nozzles. A significant increase in the efficiency of the furnace was achieved when additional electric heating was installed. This allows to reduce the total energy costs, and at the same time, the introduction of every 10 % of additional electric heating increases the efficiency of the furnace by up to 3 % and improves the quality of the glass mass. Such additional heating can be recommended in the amount of 20–30 % of the total heat consumption for the operation of the furnace. The analysis of the obtained results showed a fairly good convergence of the results, which indicates the acceptable adequacy of the models. The obtained process simulation results allow choosing the optimal design and operation parameters of the glass furnace. The results of the work can be used in practice for the design of efficient glass furnaces of various purposes and performance.

Trip Assignment Modeling for Transportation in Denpasar City Using PTV Visum Software

Mapping and macro transportation modelling are methods used to obtain an overview and analysis of transportation conditions at the macro level, encompassing all road segments in urban areas. Critical constraints on road segments can be identified through this process. Macro transportation modelling serves as a tool for studying the implementation of problem-solving policies, allowing the anticipated outcomes to be analysed through simulations in transportation modelling. This research has a specific goal: to understand the travel patterns of the population in the city of Denpasar. Calibration and validation processes in the PTV Visum modelling are conducted to test the validity of the created macrosimulation model. The trip assignment results are generated through PTV Visum modeling. The research methodology involves quantitative analysis using household interview surveys, traffic counting, correlational studies, and macrosimulation modelling. Calibration is performed by calculating the beta coefficient value (with specific calculated values), time matrices, and distance matrices to measure travel impedance functions. Validation is conducted by evaluating the Generalised Exponential Horn (GEH) value, which is less than 5, to ensure the alignment between travel output in the model and field survey data from traffic counting. From the analysis of a sample of 2,725 households, a total of 2,165,876 daily trips were obtained. Types of trips include movements from internal to internal zones (2,115,602 trips), from internal to external zones (28,799 trips), from external to internal zones (19,319 trips), and from external to external zones (2,159 trips) per day. Roads with the highest traffic volume in a single day include Hasanudin Street (42,524 pcu/hour), Diponogoro Street (42,282 pcu/hour), Sudirman Street (31,062 pcu/hour), Sutoyo Street (30,180 pcu/hour), and Sumatra Street (23,515 pcu/hour).

Morphological and molecular data suggest the presence of cryptic diversity within Dermacentor nitens (Acari: Ixodidae) in Colombia</p >

Of the 44 species within the genus Dermacentor (Acari: Ixodidae) worldwide, nine are found in the Neotropics and four are endemic to this region. In Colombia, located in the northwestern corner of South America, there are two species of the genus: Dermacentor imitans restricted to the trans-Andean Pacific region, and Dermacentor nitens widely distributed in the country. Elsewhere, D. nitens is found in both the Nearctic and Neotropics, from southern USA to northern Argentina. In the Neotropics, D. nitens is widely distributed including records in Caribbean islands. Molecular analyses of D. nitens collected in the Amazon region of Colombia have shown genetic differences with specimens from other localities of the country, although morphological differences have not been explored. We performed morphological and molecular comparisons of individuals from two natural regions of Colombia: the Orinoquia, and the Amazon. The morphological and morphometric results show that females and males are grouped in two morphotypes: morphotype I from the Orinoquia region, and morphotype II from Leticia in the Amazon region. The molecular analyses supported the morphological results and showed the formation of two well-differentiated sister clades within D. nitens, with divergences between both morphotypes of 3–4% and 5–6% for the 16S rRNA and COI genes, respectively. Species delimitation analyzes and the Poisson Tree Processes model tentatively suggest the presence of two species within the sequences associated with D. nitens in Colombia. The first represented by the sequences from the Orinoquia region evaluated here, together with sequences from other regions of Colombia and other Neotropical countries such as Brazil, Panama, and French Guiana. The second is represented by the sequences of individuals from Leticia, in the Amazon region of Colombia. The results highlight that D. nitens might represent a species complex, but further sampling, experimental crosses, and studies at the level of complete genomes should be performed to obtain additional evidence for species recognition.

Mathematical modeling of heat exchange for efficient automated control systems

The article deals with the problem of mathematical modeling of heat transfer processes, taking into account a large number of factors affecting these processes and a variety of mathematical modeling methods. The article discusses the idea of developing a universal and flexible model that could quickly adapt to different initial modeling conditions and take into account various parameters for further use of the mathematical model in the synthesis of automatic control systems. The paper discusses the main aspects of mathematical modeling of heat transfer and the creation of a mathematical model in distributed heat exchanger parameters with the possibility of changing the properties and parameters of the equipment. The paper analyzes previous studies and identifies the problems of existing methods of mathematical modeling of heat transfer, such as lack of versatility, complexity, and insufficient accuracy. The paper goes on to review different approaches to mathematical modeling of heat transfer, such as models with a group of parameters, models in distributed parameters, and models based on artificial intelligence. The article provides an overview of model implementation methods and their advantages and disadvantages. Based on this analysis, the authors propose a new mathematical model of heat transfer in distributed parameters, which should be universal, easy to use, and accurate in accordance with the requirements of synthesizing automated control systems. The authors also outline the methodology for achieving this goal, which includes the implementation of the geometry of the heat exchanger, the implementation of conditions and mathematical modeling, as well as the study of the influence of parameters and the formation of transients. The general conclusion of the article is that the developed mathematical model of heat transfer can be used to synthesize automatic control systems for heat exchange processes in various industries.

Congenital variants of the ventral laminae of the sixth and seventh cervical vertebrae are not associated with clinical signs or other radiological abnormalities of the cervicothoracic region in Warmblood horses

AbstractBackgroundThere is controversy about the clinical relevance of congenital variants of the ventral laminae of the sixth (C6) and seventh (C7) cervical vertebrae and their relationship with other radiological abnormalities.ObjectivesTo document the prevalence of congenital variants of C6 and C7 and that of other radiological abnormalities from C6 to the second thoracic vertebra (T2).Study designCross‐sectional.MethodsThe study included Warmblood horses ≥3 years of age undergoing clinical assessment at two referral institutions: 127 control horses and 96 cases (neurologic, neck pain or stiffness, or neck‐related forelimb lameness). All horses underwent a standardised orthopaedic and neurologic examination. Lateral–lateral and lateral 45°–55° ventral–lateral dorsal (left to right and right to left) radiographic views of C5 to T2 were acquired and assessed blinded to the horse's clinical category using a predetermined grading system.ResultsThe ventral profile of C7 was abnormal in 54 horses (24.2%). Cases were less likely to have congenital variants than control horses, p = 0.0002, relative risk (RR): 0.63 (95% confidence intervals [CIs]: 0.4, 1.0). There was no association between the presence of a congenital variant of C7 and the presence of modelling of the articular processes (APs) of C6–C7, C7–T1 or T1–T2. Cases were more likely to have severe modelling of the APs at C6–C7, p = 0.01, RR: 1.94, CI: 1.1, 3.5 and C7–T1, p = 0.04, RR: 1.97, CI: 1.2, 3.2 compared with control horses.Main limitationsRadiographs were read by one assessor independently at each institution.ConclusionsThere was no association between the presence of congenital variants of C7 and any other radiological findings. Congenital variants occurred less frequently in cases compared with control horses. There was no association between the presence or absence of a congenital variant and the type of case.

About the use of machine learning in modeling business processes

In a highly competitive environment, as well as the activation of the domestic production market, enterprises need to quickly adapt to modern conditions. There is an obvious increase in the number of small manufacturing enterprises that participate in tenders on electronic trading platforms and offer their services to large enterprises, especially this growth is noticeable in the field of militaryindustrial complex. Customers prefer to cooperate with small enterprises that are adaptable to the order conditions and have not only short terms of order fulfillment, but also a flexible pricing system due to low administrative and bureaucratic costs. At the same time, such enterprises have problems with the organization of business processes when the volume of orders grows. In this paper, the authors have built a model of the Quality Control process using BPMN method on the basis of small enterprise practice. This model can be the basis for training a machine learning system to build a model of business processes. Natural language text processing is proposed as an area of artificial intelligence, which allows enterprises to use this unified technology to reduce the cost of developing and describing business processes.

Modeling of dynamics processes and dynamics control

Modeling of dynamics processes and dynamics control

Mathematical understanding (hermeneutic aspects of educational activities)

The article discusses the issues of mathematical understanding as an educational practice of identifying the algorithmic meanings of mathematical (mathematized) educational texts. The hermeneutic orientation towards following the “guiding thread of language” (G.-G. Gadamer), as it is shown, cannot be narrowed to the attitude towards natural languages inherent in humanitarian educational practices. The “common place” of mathematical understanding in educational practices is: some of created languages (of scientific communication) being consolidated around the mathematical installation are not reducible to its sign universality or educational generalizations. But it often turns out to be outside the field of view of practicing teachers, in a didactically abstract position. The article substantiates the possibility of rehabilitating the hermeneutic attitude in mathematical education in connection with its development and strengthening in understanding the prerequisites for the algorithmic solution of mathematical problems (the need for additional information, non-standard solution techniques, transfer of educational goal setting to the area of interdisciplinary relationships or life experience, etc.). The author shows and comments on the effectiveness of the hermeneutic approach in mathematics education using examples of solving problems in algebra, geometry and in constructing mathematical models of various physical processes.

Autonomous hybrid optimization of a SiO2 plasma etching mechanism

Computational modeling of plasma etching processes at the feature scale relevant to the fabrication of nanometer semiconductor devices is critically dependent on the reaction mechanism representing the physical processes occurring between plasma produced reactant fluxes and the surface, reaction probabilities, yields, rate coefficients, and threshold energies that characterize these processes. The increasing complexity of the structures being fabricated, new materials, and novel gas mixtures increase the complexity of the reaction mechanism used in feature scale models and increase the difficulty in developing the fundamental data required for the mechanism. This challenge is further exacerbated by the fact that acquiring these fundamental data through more complex computational models or experiments is often limited by cost, technical complexity, or inadequate models. In this paper, we discuss a method to automate the selection of fundamental data in a reduced reaction mechanism for feature scale plasma etching of SiO2 using a fluorocarbon gas mixture by matching predictions of etch profiles to experimental data using a gradient descent (GD)/Nelder–Mead (NM) method hybrid optimization scheme. These methods produce a reaction mechanism that replicates the experimental training data as well as experimental data using related but different etch processes.

PROMISING TYPES OF HEAT STORAGE ELEMENTS FOR REGENERATIVE AIR HEATERS OF BLAST FURNACES

The paper considers the problem of improving the efficiency of operation of blast furnace air supply systems, which are equipped with regenerative heat exchangers with fixed refractory nozzle for heating hot blast. The existing methods of improving the performance of air heaters are analyzed. It is shown that further growth of thermal efficiency of regenerative heat exchangers by optimization of operation parameters or replacement of nozzles is impossible without increasing the overall parameters. As a perspective measure the use of heat storage elements with phase transition is proposed, where as a fusible insert compounds with a certain melting point are used, which corresponds to the operating modes of blast furnace air heaters. They have found application for heat storage in solar systems. Due to the "residual" thermal effect, the nozzles accumulate additional heat. This will increase the heat capacity of the heat exchanger and increase the hot blast heating temperature without changing the dimensional parameters. Operating conditions of air supply systems of blast furnaces are characterized by high temperature level, which is 1200–1350 °С, significant flow rates and speeds of hot and cold coolants, their increased pressure. Therefore, there is a question of choosing appropriate heatacumulative elements taking into account their properties and operating parameters of blast furnaces. Operation of such nozzles has revealed a number of problems, the solution of which requires additional research. For this purpose it is necessary to carry out modeling of quasi-stationary heat-exchange processes in the nozzle chamber of regenerative air heaters in order to select chemical compounds or their mixtures, which meet the operating conditions of blast furnace air supply systems, and to determine the optimal combinations of nozzle materials. Application of this technology will make it possible to obtain higher hot blast heating temper- ature, reduce metallurgical coke consumption or increase blast furnace productivity.

CFD Analysis of Gas-Dynamic and Heat Transfer Processes in a Propulsion System Using Polymer Fuel

In the presented work, a computer model of thermodynamic and gas-dynamic processes in a rocket engine of a new type, which uses solid polymers as fuel is considered. The design feature is the presence of a central body - a gasification chamber, where solid polymer fuel is decomposed into volatiles. To conduct the research, a preliminary thermodynamic analysis of the combustion of gasification products was carried out. Based on the results of the thermodynamic analysis using the mathematical model of the turbulent flow of viscous compressible gas, the processes of gas dynamics and heat transfer in the chamber and nozzle of the rocket engine were simulated. Analyses are made for the geometry of a real experimental sample of a polymer-fueled rocket engine developed at Oles Honchar Dnipro National University (Ukraine), which has passed the first successful tests. As a result of CFD simulation, dynamic and thermal fields in the combustion chamber and engine nozzle were obtained, and ways of further improvement of the design were determined.

Diagnostics of the technical condition of wells drilled through freshwater horizons using active thermometry

Relevance. Recently, ESG (Environment, Social, Governance) principles have been given an important role in the agenda of oil and gas companies – this is an actively developing global trend in the modern business environment. One of its key aspects is a responsible attitude to the environment, increasing the priority of solving environmental problems arising from the extraction of hydrocarbons. A significant environmental problem is, in particular, pollution of freshwater horizons during oil production due to their poor-quality insulation during well cementing. At the same time, in the space of the well behind the casing, there is a flow of borehole fluid to freshwater horizons, which has a negative impact on the environmental situation in this region. In this regard, monitoring the technical condition of wells crossing freshwater horizons is an important and urgent task. Object. An operational well drilled through freshwater horizon, in which geophysical studies are carried out by the method of active thermometry – local heating of the casing section is carried out and the dynamics of the temperature field in it is studied. Aim. To identify qualitative patterns and obtain quantitative estimates of the effect of the fluid flow in the space behind the casing (column space) on the temperature field in the casing. Methods. Numerical mathematical modeling of thermal and hydrodynamic processes in a well using the software package Ansys Fluent (ANSYS Academic Research CFD license, agreement with Bashkir State University dated 06/15/2020). Results. The authors have studied the influence of a plane-parallel horizontal fluid flow of the freshwater horizon on the azimuthal temperature distribution of the casing string during induction heating. It is shown that in the case of leakiness of the cement ring in the interval of the freshwater horizon, an inhomogeneity of the azimuthal temperature distribution of the column is observed, reaching a value of few more K. The authors carried out the simulation of induction heating in the well with liquid column flow to the interval of the freshwater horizon. It is shown that the sign indicating the overflow is the occurrence of a temperature disturbance area vertically above the induction heating interval with a length of more than 1 m. In general, the results of the performed studies show the informativeness of the active thermometry method in relation to the diagnosis of the technical condition of wells drilled through freshwater horizons.

Applying Design Thinking to Develop AI-Based Multi-Actor Decision-Support Systems: A Case Study on Human Capital Investments

Artificial intelligence, particularly machine learning, has revolutionized organizational decision-making processes by assuming many decision responsibilities traditionally allocated to humans. In this scenario, decision-support systems based on AI have gained considerable relevance, although the attitudes of managers toward intelligent agents are still unbalanced towards human intervention in decision-making. An additional level of complexity arises when the development of these systems occurs within the context of investments in human capital, such as startup funding or organizational development. In this field, decision-making becomes even more critical, since it implies the will, goals, and motivations of every human actor involved: the investors and those seeking investments. termed multi-actor decision-making, this process involves multiple individuals or groups of individuals who, starting from non-coincident objectives, must reach a mutual agreement and converge toward a common goal for the success of the investment. Considering these challenges, this study aims to apply the design thinking technique as a human-centered methodology to support the design of an AI-based multi-actor decision-support system, conceived by Mylia (The Adecco Group), in the field of organizational development. Additionally, the integration of strategic organizational counseling will be introduced to facilitate the modeling of internal DM processes within the provider organization, enabling the seamless flow of internal behaviors from the decision-support system’s conceptualization to its integration in the external market.

Visualizing sustainable rainwater harvesting: A case study of Karbala Province

Abstract The management of rainwater collection in a practical way is a fundamental need for the management of water resources in a manner that is sustainable. The goal of this research is to determine whether or not remote sensing technology is effective in providing data on precipitation for the purpose of locating rainwater collection tank locations in the province of Karbala. Rainfall patterns fluctuate considerably. Remote sensing may not capture variability enough to estimate the rainfall period and location. Sustainable rainfall harvesting requires accurate rainfall timing and distribution. This information is applied in the modeling of hydrological processes, the management of disasters, and environmental research. Following the completion of a geographical study, it has been established that the city of Karbala may be divided into two basic sections. Through the use of estimation, it is possible to more easily identify the region that is ideal for the location of rainwater-harvesting reservoirs and lakes. On the contrary, it is crucial to keep in mind that a location that was chosen based on average rainfall over a period of two years could not be suitable for other time periods. This is an idea that should be kept in mind several times. To put this into perspective, when choosing a location, it is vital to take into consideration the severity of the rainfall as well as the geographical location of the area. Particularly in locations such as Karbala, the implementation of data visualization systems into water management practices has the potential to improve both the efficiency and sustainability of water management methods. The findings of this study show the significance of implementing precise site selection techniques to enhance rainwater collection systems and encourage activities that are environmentally responsible for water management.

Advanced Statistical Approach for the Mathematical Modeling of Transfer Processes in a Layer Based on Experimental Data at the Boundary

Advanced Statistical Approach for the Mathematical Modeling of Transfer Processes in a Layer Based on Experimental Data at the Boundary

Клиентоцентричный и процессный подходы в деятельности органов публичной власти

This paper aims to advance the theory and practice of employing complementary customer-centric and process approaches in public administration. The research methodology is grounded in system approach, customer-centric and process approaches, and lean production technologies. A review of implementing practices of the process approach through the adoption of lean management in the constituent entities of the Russian Federation under the “Effective Region” project in partnership with the state corporation Rosatom is conducted. Analysis of the promotion of the customer-centric approach in public authorities is undertaken within the framework of the federal project “State for the People”. The connection between customer-centricity and process approach is elucidated. It is proposed to supplement federal-level regulatory documents pertaining to the customer-centric approach under the federal project “State for the People” and customer-centricity standards with sections describing the modeling and optimization of business processes using modern graphic notations such as IDEF0, VAD, DFD, EPC, CFFC, BPMN, and requirements for training new competencies of state and municipal employees in this field.

Time series modeling and forecasting of epidemic spreading processes using deep transfer learning

Traditional data-driven methods for modeling and predicting epidemic spreading typically operate in an independent and identically distributed setting. However, epidemic spreading on complex networks exhibits significant heterogeneity across different phases, regions, and viruses, indicating that epidemic time series may not be independent and identically distributed due to temporal and spatial variations. In this article, a novel deep transfer learning method integrating convolutional neural networks (CNNs) and bi-directional long short-term memory (BiLSTM) networks is proposed to model and forecast epidemics with heterogeneous data. The proposed method combines a CNN-based layer for local feature extraction, a BiLSTM-based layer for temporal analysis, and a fully connected layer for prediction, and employs transfer learning to enhance the generalization ability of the CNN-BiLSTM model. To improve prediction performance, hyperparameter tuning is conducted using particle swarm optimization during model training. Finally, we adopt the proposed approach to characterize the spatio-temporal spreading dynamics of COVID-19 and infer the pathological heterogeneity among epidemics of severe acute respiratory syndrome (SARS), influenza A (H1N1), and COVID-19. The comprehensive results demonstrate the effectiveness of the proposed approach in exploring the spatiotemporal variations in the spread of epidemics and characterizing the epidemiological features of different viruses. Moreover, the proposed method can significantly reduce modeling and predicting errors in epidemic spread to some extent.