This paper presents the results of modeling heat fluxes from the outer surface of the KRO-200 container. The study was conducted for a temperature range of 40–150 °C. A comparison of the results was performed for coating materials characterized by different values of emissivity (ε = 0.4–0.95). The total heat release and its components – thermal radiation and convective heat transfer – were calculated. The aim of the study is to evaluate the temperature distribution on the outer surface of the KRO-200 container, which may affect its reliability, leak-tightness and durability. The modeling enabled the establishment of a relationship between the intensity of heat release and the parameters of heat exchange with the environment. The results confirm the importance of using adaptive technologies and monitoring systems to prevent local overheating or excessive cooling. The analysis serves as a basis for developing recommendations on optimizing container design and improving environmental safety during the long-term storage of liquid radioactive waste.
The paper proposes a method for building a laboratory research stand for a multi-motor electric drive using a Raspberry Pi 5 single-board computer and brushless direct current (BLDC) motors. A feature of the approach to developing the laboratory research stand is the use of a software-oriented architecture of the automatic control system. This simplifies the application of different control algorithms without the need to change the hardware of the laboratory stand. During the study, a series of experiments were conducted with two methods for controlling the rotation speed of motor shafts. The obtained results showed that the use of software-oriented architecture allows to increase the flexibility of the automatic control system and reduce the integration time of new control methods into a multi-motor electric drive. The scientific and practical value of the study lies in the development of a universal laboratory research stand for the experimental analysis of modern methods of controlling multi-motor electric drives.
This paper investigates the impact of architectural scaling in YOLO-family neural object detectors on object detection performance in unmanned aerial vehicle (UAV) systems under CPU-only inference conditions without hardware acceleration. Standard nano and small model configurations are analyzed, along with an intermediate model obtained through controlled width scaling of the network. Experimental evaluation is conducted on an embedded Raspberry Pi 5 platform under fixed hardware and software conditions using ONNX Runtime, ensuring fair comparability of the models. Performance is assessed using detection accuracy metrics (mAP@0.5; mAP@0.5:0.95), average inference latency and the coefficient of variation of latency, as well as an integrated efficiency metric. The results demonstrate that increasing model complexity leads to a nonlinear improvement in detection accuracy, accompanied by a growth in inference latency, which limits the applicability of such models in real-time scenarios.
This paper analyzes the causes of emergency damage to a building’s internal engineering systems resulting from water freezing. It has been established that a combination of climatic conditions during the cold season, design decisions and operational factors creates an increased risk of failures in water supply, heating and drainage systems. The physical conditions for water freezing in pipelines and their impact on the reliability and durability of building engineering systems are examined. To quantitatively assess the consequences of a heating system shutdown, an algorithm is proposed for determining the time required for a room to cool down, depending on the outdoor air temperature, heating system parameters and the thermal condition of the building envelope. Using the example of a typical apartment in a five-story prefabricated residential building, a calculation was performed to determine the time required for the indoor air temperature to drop to characteristic temperature levels. Additionally, an assessment was performed of the time parameters for cooling and subsequent freezing of water in heating devices after the heating system stops operating. The results obtained allow for an assessment of the potential risk of water freezing in the internal engineering systems of buildings and can be used to justify engineering solutions aimed at improving their operational reliability.
Reports from modern conflicts clearly highlight technological changes in military strategies, tactics and doctrines. At the same time, artillery is still playing a huge role in combat operations, which in turn increases the demand for artillery ammunition and creates additional logistical challenges. Ammunition of insufficient quality greatly impacts the outcome of artillery combat operations. The study identifies the lack of a mathematical model which considers the possible ammunition resource limitations and defects in artillery systems when estimating the effectiveness of target firing. The study proposes a discrete stochastic model for estimating the effectiveness of artillery battery target firing and takes into consideration combat mission objectives and resource limitations. The study proposes using acceptance sampling strategies for the mission preparation phase, based on binomial and hypergeometric distributions, to optimize ammunition quality validation process and minimize preparation time. The model allows comparing different strategies for ammunition distribution and the use of artillery systems with different quality for defined combat mission tasks and restrictions. Additionally, the model takes into consideration the probability of enemy retaliation fire, which impacts the overall fire accuracy of artillery battery and the time required for repositioning maneuver to decrease the probability of enemy retaliation. Calculation results allow for strategy evaluation using two criteria: the efficiency coefficient, defined as the ratio of expected hits to total shots fired, and the total time required for mission completion, including both preparation and execution phases. Experiments compare multiple strategy combinations across different mission scenarios, varying required hit counts, danger coefficients, artillery battery compositions and ammunition distribution approaches. The experiment results demonstrate the possible trade-offs between mission preparation and execution time and ammunition usage efficiency. The proposed model provides a calculation tool which could be used during initial mission planning and resources allocation to provide more accurate estimations for possible strategy outcomes.
The paper proposes a solution to the relevant scientific and applied problem of optimizing the design of chordal multi-path ultrasonic flowmeters for measuring the flow rate of distorted flows. The object of the study is the integration accuracy of the velocity profile of distorted flows using numerical integration methods. The authors have developed a methodology for searching for the optimal design parameters of chordal multi-path ultrasonic flowmeters (location coordinates and weight coefficients of their acoustic paths) based on a hybrid genetic algorithm. The proposed approach combines the global search of the genetic algorithm with local optimization using the gradient descent method. This approach minimizes the methodological flow measurement error, which significantly outperforms the accuracy of the classical Gauss-Jacobi and OWICS methods. Analysis of the error surface topology revealed the presence of an "optimality zone" in the form of an extremal trough, which is described by a quadratic relationship between the two specified geometric parameters. The obtained results prove that adapting the design of chordal ultrasonic flowmeters through the functional relationship between coordinates and weight coefficients ensures the instrument's invariance to flow asymmetry. The developed methodology is universal for designing high-precision energy resource metering systems based on ultrasonic flowmeters.
The PHV-1000 steam generator is one of the main heat exchangers in the primary circuit of the power unit of nuclear power plants with a WWER-1000 reactor. The efficiency of its operation directly affects the thermal power and overall electricity generation of the power unit. The reliability of the heat exchange tubes forming the main heat exchange area is critical not only for thermal performance but also for the safety characteristics of the steam generator. As a result of damage and tube plugging, the active heat-exchange surface decreases, directly affecting the steam generator's operation. The paper investigates the impact of heat-exchange tube degradation and plugging in the PHV-1000 steam generator on its thermal parameters, particularly steam productivity. The importance of limiting the number of plugged heat exchange tubes within the regulated norms (up to 2% of tubes) is emphasized, and the possible consequences of exceeding this threshold for the thermal efficiency and resource of the power unit are substantiated. Methods for monitoring the condition of heat-exchange tubes are analyzed, particularly, the eddy-current non-destructive method and the modern welded method ZOK–PG 08 for tube plugging is considered.
At present, the problem of saving energy resources is more relevant than ever. The largest consumers of these resources are industrial enterprises, institutions and organizations, all of which are interested in the efficient use of electricity, heat, water and other resources. One of the key criteria for the effectiveness of any industrial production is its energy efficiency. Increasing energy efficiency is an essential factor for their optimal operation. Distillation plants are among such facilities. One of the important directions for improving their energy efficiency is the enhancement of automatic control systems for such units. Modern approaches to the improvement of automatic control systems include: the application of intelligent control algorithms, adaptive and predictive regulation systems, the use of more accurate and energy-efficient peripheral equipment, the application of various software optimization methods in the calculation of mathematical models of objects, advanced diagnostic techniques and the design of facilities considering energy-saving criteria, among many others. Even within each method or technique, there is a wide range of possible implementation approaches. This paper provides a review of literature sources related to the improvement of distillation systems according to energy-saving criteria, their analysis and structuring, as well as the formulation of general approaches to possible solutions for enhancing modern automation systems.
The low-temperature separation (LTS) process is widely used for moisture and condensate removal in natural gas treatment and is typically controlled using local automation systems. However, the process is inherently multivariable, with strong cross-couplings between inputs and outputs, and is significantly affected by external disturbances. This study defines the control inputs as actuator signals on the gas and condensate outlet lines, while the outputs are the gas pressure and condensate level in the separator. Disturbances include variations in inlet gas pressure and condensate line pressure. A linearized mathematical model of the LTS process is developed, based on input–output and disturbance–output relationships. Using this model, an invariant automatic control system is synthesized, incorporating cross-coupling and disturbance compensators. The cross-coupling compensator ensures decoupling of control loops, while the disturbance compensator reduces the impact of external disturbances. The effectiveness of the proposed system is verified through simulation, confirming the validity of the theoretical approach and demonstrating improved control performance.
Protection systems for three-phase induction motors are essential for ensuring reliable and safe operation of electric drives in industrial installations. The application of microcontroller-based technologies significantly expands the functional capabilities of protection devices by enabling simultaneous monitoring of multiple motor parameters and providing flexible configuration of protection settings. This paper presents the design and experimental validation of a low-cost microcontroller-based protection system for three-phase induction motors. The proposed solution is implemented using the ESP32 microcontroller and integrates measurement channels for stator voltage, current and motor temperature to detect abnormal operating conditions. The system architecture includes a measurement subsystem, a control unit, a backup power supply module and a web-based user interface that allows configuration of protection thresholds via a Wi-Fi connection. A laboratory prototype and a dedicated experimental test bench were developed to verify the system performance. Experimental results confirmed the correct operation of the monitoring and protection algorithms and demonstrated the effectiveness of the proposed system in detecting emergency conditions such as voltage asymmetry, phase loss, overload and motor overheating.
This paper examines the challenges of monitoring the condition of power equipment and systems as well as detecting the changes in their operation before irreversible processes occur. The study included an analysis of the electrical parameters of existing methods for monitoring and diagnosing electrical systems in a general approach as well as current research and examples of practical methods for detecting electrical, chemical and physical parameters of electrical systems. A list of non-electrical parameters is provided that can form a comprehensive monitoring system for pre-critical conditions and early response (air humidity at the equipment location, temperature of equipment and ambient air, corrosive gases, vibrations). The analysis of non-electrical parameters provides a foundation for future research utilizing electronic devices and corresponding software for the comprehensive monitoring of the condition of electrical and power systems.
This work addresses the problem of producer gas cleaning in low-capacity units (up to 40 m³/h) to ensure the reliable operation of internal combustion engines. Since traditional dry cyclones do not provide the required purity, the objective of this study is the optimization of the design parameters of a compact inertial-water filter. To study the complex multiphase hydrodynamics in the “gas–water–solid particles” system, a mathematical model was developed, integrating the Volume of Fluid (VOF) method for tracking the free liquid surface and the Lagrangian approach for solid particle trajectories. Based on the orthogonal central composite design of experiments, the influence of key geometric factors on separation efficiency and the risk of moisture ejection was investigated. Multi-objective optimization allowed for determining the optimal characteristics: the inlet pipe diameter (Din = 36.5 mm), the relative distance from the inlet pipe to the water (hin/Din = 1.5) and the ratio of the outlet pipe diameter to the distance to the water surface (Dout/hw = 0.928). Under these conditions, the predicted cleaning efficiency reaches 91.94% with a minimal compromise level of water ejection (0.00078 kg/s), which forms the theoretical foundation for designing such systems.
In this paper, a MATLAB-based model of a variable frequency drive–induction motor system with scalar control U/f=const and speed feedback is developed and investigated. The system includes a three-phase two-level PWM inverter, a rectifier and a DC-link. The electromechanical parameters of the induction motor are taken into account. Additionally, a PI speed controller and feedback signal filtering are implemented, which allows the model to closely represent the behavior of a real industrial electric drive. The developed model enables the study of transient processes in both open-loop and closed-loop operating modes. In the open-loop mode, characteristic torque and current ripples caused by the PWM inverter are observed, as well as the absence of speed disturbance compensation under load application. In the closed-loop mode, the system demonstrates astatic behavior and speed recovery under load disturbances due to the PI speed controller. The study of PI controller parameters shows that increasing the proportional gain improves the system response speed but leads to higher overshoot and dynamic overloads, whereas increasing the integral time constant enhances damping at the expense of slower response. It is determined that compromise tuning of the controller provides the best performance, ensuring satisfactory transient response without exceeding the permissible limits of the power converter. The obtained results confirm the effectiveness of the developed model as a virtual test bench for the analysis and tuning of variable frequency drive systems.
A mixer with coaxial arrangement of inner and outer circular cylinders with smooth surfaces is considered. During the mixer operation, a circulating flow is formed between the cylinders with the same conditions of motion along the entire length of the annular gap. The smooth surfaces of the inner and outer vertical cylinders reduce the possibility of the polymer solution destruction as an agent for reducing hydraulic resistance due to the high speed of rotation of the inner cylinder and/or the outer cylinder. The hydrodynamics of the mixing process of an aqueous solution of polyacrylamide (PAA) with a mass concentration of 100 ppm in the gap between the cylinders, the inner one of which was rotating, were estimated by the dependence of the power criterion NP on the modified Reynolds criterion Rem. The mixing of the aqueous solution of PAA occurred in a laminar mode with a decrease in NP at a certain fixed value of Rem compared to water.
The paper investigates the influence of optimization methods on the efficiency of an extremal control system based on acoustic anomaly detection. The proposed system can detect abnormal equipment operating modes by analyzing sound characteristics and automatically adapting control parameters to new operating conditions. Using mathematical modeling, the operation of the system with different optimization algorithms (gradient descent, Momentum, Nesterov and RMSProp) was studied. The results show that RMSProp provides the fastest transition to steady state (103 s) with minimal overshoot (3%), but there are significant oscillations in the control signal. Classic gradient descent demonstrates an acceptable stabilization time (123 s) with moderate overshoot (23%). The Momentum and Nesterov methods are characterized by the longest settling time (173 and 160 s, respectively). The study confirms the feasibility of using extremal control systems with adaptive optimization to improve the reliability and efficiency of technological equipment under variable operating conditions.
This paper presents the development and validation of a fuzzy control model with automated rule base generation for artillery system actuators in game simulators. The proposed model integrates a bioinspired optimization mechanism based on the ant colony algorithm, enabling the automatic synthesis of efficient rule bases without relying on expert knowledge. This approach ensures adaptability and autonomy under uncertain conditions and provides logical transparency, allowing detailed analysis of control strategies. The model can be employed to simulate the decision-making behavior of virtual allies or adversaries, representing their different skill levels by adjusting reference models and objective functions at the design stage, thereby enhancing the realism in combat scenarios simulation. Experimental studies conducted on the example of an electric drive simulation model responsible for artillery mount barrel elevation demonstrated the superiority of the fuzzy model over a traditional PD controller in terms of robustness, efficiency and accuracy. The methodology presented in this paper can also be applied to hydraulic and other types of actuators.
The work presents the development and investigation in MATLAB of a model of an autonomous self-excited induction generator with a rotor circuit inverter for a wind turbine. The system employs a scalar-controlled inverter with an independent power supply, and the nonlinear magnetization curve of the induction generator is taken into account. Voltage and frequency regulation are separated. The developed model made it possible to study the self-excitation mode for different rotor supply frequencies. During the simulation of the self-excitation process of the autonomous induction generator, it was found that the optimal parameters for stable self-excitation were achieved at a rotor frequency of 1.8 Hz and a rotor supply voltage of 20 V. The study also examined the effect of applying an active-inductive load and the system’s response to changes in the drive shaft speed. When a 40% load of the rated value was connected, a slight voltage drop accompanied by an increase in the rotor phase current was recorded; however, the system remained stable without the need for additional control measures. By increasing the inverter voltage, the generator terminal voltage was restored to its initial level. When the drive shaft speed was suddenly reduced by 10%, a minor voltage decrease and a corresponding increase in rotor current were also observed. This mode remained stable, and the voltage and frequency were successfully leveled again by means of the inverter.
The paper analyzes developments in the field of environmental parameter monitoring using microcontrollers and Internet of Things technologies, with results that justify the use of ESP8266 microcontroller. A monitoring system for microclimate parameters (temperature, humidity and atmospheric air pressure) in smart homes and industrial premises based on ESP8266 microcontroller has been developed, which demonstrated its effectiveness through a combination of hardware and software tools. The integration of BMP280 and AHT10 sensors ensured the accurate measurement of temperature, humidity and atmospheric air pressure. The asynchronous web server integrated into the ESP8266 allows for displaying the results as interactive, real-time graphs. In the developed system, users access data directly from the local network, ensuring functionality even without Internet access. Furthermore, the cost of the hardware (ESP8266 controller, BMP280 and AHT10 sensors) remains minimal, making the system accessible for widespread use. The implementation of a user notification system via WhatsApp Messenger using CallMeBot service became an important addition, allowing for the prompt notification of users about exceeding parameter limit values, even without logging into the web application. This approach increases the level of automation, convenience and reliability of microclimate control, making the system suitable for a wide range of tasks in domestic and industrial applications.
The increase in electricity demand and the need for renewable energy are driving the rapid adoption of distributed generation sources, where photovoltaic (PV) generation holds a leading position. While PV systems convert free sunlight into electrical energy, their sensitivity to weather variations and lack of inertia limit widespread application without auxiliary energy storage systems. The variable nature of output power caused by dynamic solar radiation intensity changes is one of the main challenges for PV. In weak electrical grids, PV output power changes could significantly affect voltage levels, leading to electromagnetic compatibility issues and compromising the stability of generation sources and consumers. This paper focuses on studying short-time intensive solar irradiance changes the impact on a PV-rich medium voltage grid. Using the MATLAB/Simulink environment the rapid solar irradiance changes have been modeled to examine output PV power changes and the resulting voltage changes in the point of common coupling, depending on the control mode applied by the PV inverter.
The paper presents research results on the application of infrared thermography for diagnostics of machines and devices in railway infrastructure. The theoretical foundations based on Fourier’s heat conduction equation are outlined and the principles of designing an automated diagnostic system using thermal cameras, a data processing server, and machine learning algorithms are described. Examples of thermograms and graphs illustrate the detection of defects in cable connections, rail joints and turnout drives. Experimental studies confirmed that infrared diagnostics ensure high accuracy, speed and reliability in detecting hidden faults that remain unnoticed by traditional inspection methods. An economic analysis demonstrated a reduction in maintenance costs by up to 65% and a 67% decrease in train downtime. The obtained results prove the feasibility and effectiveness of implementing infrared thermographic systems in the maintenance practice of Ukrainian railways to enhance operational safety and optimize maintenance expenses.
