Journal of Applied Engineering Science

ANALYSIS OF THE APPLICABILITY OF THE ANIVI-STURTEVANT DYNAMIC CLASSIFIER IN THE PRODUCTION OF CRUSHED AGGREGATES

Michal Vokurka — 2025-11-19

The presented paper analyses the applicability of the Anivi-Sturtevant dynamic classifier in production of crushed aggregate in a quarry. This dynamic air classifier allows separation of fine particles of smaller sizes than 0.063 mm from materials that have excessive amounts of these particles. This is executed in order to recover materials that would otherwise be deposited only as waste materials. The research included an experiment in a quarry following predefined methodology. By regular sampling of materials and their subsequent testing, the particle size distributions of grains were plotted, and also depending on the input moisture or due to the separation of fine particles. The operation of the classifier consumes electrical energy and from this point of view, it is necessary to monetize the output profitably. A modelling process has been implemented where the 0/4 mm fraction produced by Anivi is mixed into the commonly produced fraction 0/4 certified or into mixtures of 0/32 or 0/63.

THE TRAFFIC INTENSITY AND THE NUMBER OF TRAFFIC ACCIDENTS BASED ON PROBABILITY THEORY AND MATHEMATICAL STATISTIC FORECASTING

Liliya Kushchenko — 2025-12-02

Based on the collected experimental data on the number of vehicles moving along the street and road network of the urban agglomeration, a theoretical approach to predicting the number of vehicles based on mathematical statistics and probability theory is developed in the article. The obtained results of the intensity of vehicle traffic forecasting, together with the processed statistical data on the number of traffic accidents, make it possible to identify places with increased traffic accident rates for predicting the number of traffic accidents. The results of the predicted values of seasonal vehicle traffic intensity are given in the text (Table 1). The forecast results are within the confidence interval, which theoretically confirms the correctness of the obtained values. The theoretical approach to predicting the number of traffic accidents was obtained on the basis of the two-parameter Weibull distribution law. The results of the obtained numerical parameters of the statistical and theoretical distribution law λ(t) characteristics are shown in Table 3. An additional assessment was carried out when choosing the distribution curve λ(t), which makes it possible to implement the K. Pearson agreement criterion and its properties χ². The theoretical approach allows you to assess the road traffic situation in an urban agglomeration with the subsequent implementation and implementation of organizational and technical measures to reduce road deaths.

FLEXIBLE PAVEMENT REMAINING LIFE DUE TO ELASTIC MODULUS DECREASE BASED ON THE BINA MARGA 2017 METHOD AND THE ASPHALT INSTITUTE METHOD

Senja Rum Harnaeni — 2025-11-19

This research compares the remaining life of flexible pavement that experiences a decrease in elastic modulus due to road usage, utilizing The Bina Marga 2017 Method and The Asphalt Institute Method. The study begins with a structural evaluation of the pavement, field core sampling, and laboratory modulus testing. Variations in the asphalt mixture's elastic modulus are analyzed at 100%, 80%, and 60% of its original value for each layer. Using KENPAVE software, simulations determine the horizontal tensile strain on the bottom of asphalt layer to predict fatigue life and the vertical compressive strain on the top of subgrade for rutting life. The study also includes a traffic survey to assess traffic load, and remaining life calculations provide longevity predictions across both methods. The results indicate that a decrease in the elastic modulus value of the flexible pavement layer leads to a reduction in both fatigue life and rutting life, ultimately affecting the overall remaining life of the pavement. Notably, the remaining life assessments for fatigue and rutting calculated using The Bina Marga 2017 Method yield greater values than those determined by The Asphalt Institute Method. Therefore, it is recommended to utilize The Asphalt Institute Method for planning purposes, as it provides more conservative results, ensuring safer planning compared to The Bina Marga 2017 Method.

A STUDY ON DETECTING THE WELD SPOT FOR BUILDING AN AUTOMATIC WELDING ROBOT

Long Trinh — 2025-12-14

The use of automatic welding robots has become an important trend in the industry. Applying this technology not only helps increase production efficiency but also reduces risks and labor costs. In this context, our study proposes an advanced method by incorporating the YOLOv8 deep learning network into an automatic welding robot. The task of the YOLOv8 model is to detect and monitor welds in real time through a camera system. This helps automate the welding process by providing information about the position and shape of the weld points. Welding coordinate values are transmitted and the welding tip is adjusted to target specific welding points, creating an efficient and precise automated welding process. The paper also hopes that this research will encourage the development and application of artificial intelligence (AI) in the field of welding. By combining welding technology and artificial intelligence, it is believed that the welding industry will continue to progress and modernize while contributing to the sustainable development of global manufacturing.

ANALYSIS OF THE IMPACT OF INSTALLING CAI AND IMS ON A MOTORCYCLE ENGINE

Wijianto Wijianto — 2025-11-10

Engine performance and fuel efficiency are very important in a motor vehicle, so many studies aim to improve the performance of motor vehicles. The Intake Manifold Spacer (IMS) is placed on the intake manifold channel before the air and fuel mixture enters the combustion chamber, while the Cyclonic Air Injector (CAI) is placed on the air channel that will enter the carburettor chamber. With the addition of IMS and CAI, it is expected to increase the homogeneity of the fuel-air mixture and provide a turbulent flow effect (swirling) on the air entering the carburettor and the air-fuel mixture entering the combustion chamber. The method used in this study is to manufacture IMS and CAI with variations in the number of blades: 3 and 4 and the angle of inclination of the blades 35^o and 45^o. Testing was conducted on a 110cc 4-stroke motorcycle, where a dyno test was used to determine power, torque, and fuel consumption. The results of this study show that the addition of IMS and CAI can improve performance and increase fuel efficiency compared to standard motor vehicle conditions. The largest increase in motor power was in the variation of adding IMS and CAI with 4 blades and a blade angle of 35^o, which was 3.9%. Meanwhile, the maximum torque increased by 3.9 in the variation of adding IMS and CAI with 4 blades and a blade angle of 45^o. Fuel consumption also experienced savings or decreased compared to the standard conditions of all test variations. The highest efficiency of 9.36% occurred in the variation of adding IMS. Based on this research, it can be one of the considerations to improve the performance of combustion engines for the automotive industry. It can also serve as a reference for other researchers who wish to conduct research on combustion engine performance.

REGRESSION ANALYSIS ALGORITHM FOR THE RESULTS OF REINFORCED CONCRETE SLABS TECHNICAL INSPECTION

Valentin Mikhailov — 2025-12-03

The paper presents an algorithm for calculating key statistical parameters, including correlation dependences, correlation coefficients, and a method of checking the presence of a linear dependence. A quadratic regression equation is obtained, regression curve graphs are constructed, distribution functions and probability densities with the procedure for their normalization are calculated. The main statistical parameters of random variables are also calculated: mathematical expectation, variance, standard deviation, and quantiles of various levels. The proposed regression analysis algorithm can be used to assess safety and reliability of building structures, which allows analyzing their operation in a probabilistic form. Based on the theoretical and applied results of the work, prospects are opened for further development of probabilistic analysis methods for safety of construction projects as a whole, taking into account their complex structure and interaction of various structural elements.

GEAR TEETH OF BALL MILLS: WEAR, RESTORATION, AND MATHEMATICAL MODELING

Toty Buzauova — 2025-12-07

This study focuses on the restoration of large-module gear teeth of ball mills using the electroslag welding method, with an emphasis on practical results and mathematical modeling. The research established that optimal electroslag welding conditions are achieved by stabilizing key process parameters, such as current strength, slag bath volt-age, and cooling water flow rate. For high-quality welding of gear teeth with a module of 20 mm, the following parameters are recommended: current strength I=362.5 A, slag bath voltage U=73.25–74 V, and water flow rate Qw=3–3.5 l/min. These parameters ensure minimal roughness and the required hardness of the welded teeth. Mathematical modeling provided equations linking welding modes with the roughness and hardness of the welded teeth. The presented experimental data are highly relevant for the scientific com-munity and enterprises involved in the restoration of large-module gear wheels. The results hold significant practical value as they enable enterprises to reduce restoration costs and enhance the durability of components.

PERFORMANCE AND TECHNICAL FEASIBILITY STUDY OF WIND TURBINE FOR ACHIEVING ENERGY INDEPENDENCE: A CASE STUDY IN BANGOWAN TOURIST VILLAGE, INDONESIA

Eva Hertnacahyani Herraprastanti — 2025-11-17

This study evaluates the feasibility of wind energy for energy independence in Bangowan Tourist Village, Central Java, Indonesia, using real-time monitoring via the ThingSpeak Internet of Things (IoT) platform. The novelty of this work lies in combining IoT-based real-time monitoring with Archimedes turbines to assess renewable energy feasibility in a rural tourist village context. The average wind speed was 6.04 m.s-1. A single Archimedes turbine produced 5,284 Wh/day, while two turbines generated 10,568 Wh/day, equal to 32.95% of the 32,075 Wh daily demand. Regression analysis showed a modest but significant correlation between wind speed and power (p = 0.043; R² = 0.049), while Tip Speed Ratio–Coefficient of Performance (TSR–Cp) analysis revealed a strong relationship (R² = 0.867). The most effective configuration combined two turbines, 2 kWp photovoltaic (PV), and a 5 kVA generator set (genset) operating 4 h/day, achieving 108.81% adequacy at ~56 million Indonesian Rupiah (IDR). Results confirm that small-scale wind is feasible if integrated into modular hybrid systems with IoT monitoring for reliable, cost-effective rural electrification.

ANALYSIS OF CYLINDER HEAD REPAIR OF MAIN ENGINE: A CASE STUDY OF PASSENGER SHIP KM GD IN INDONESIA

Zulfaidah Ariany — 2025-12-13

KM GD a passenger ship operated by PT. PELNI. Playing an important role as a transportation link between regions in Indonesia, especially given the country’s archipelagic geography. The reliability of the main engine as the main driver of the ship is a crucial factor in ensuring smooth operations. One of the vital components in a master engine system is the cylinder head at KM GD was found to have repeated damage to the cylinder head shortly, although repairs have been made. Damage to the cylinder head has a high presentation on engine operation. Repeated damage is interesting for research to discover more details about the causes of cylinder head cracks. This study identified the root cause of damage using the Root Cause Analysis method with the 5 Whys approach and the Fishbone diagram. The results of the study show that many factors are the cause of cracks. The main factor of damage is a non-standard reconditioning procedure. Repairs to standards provide significant savings and improve engine reliability. Research using the RCA method effectively analyses technical issues and supports efficient and sustainable treatment decision-making. Recommendations are given to improve the working performance of the machine after reconditioning, among others, through the implementation of strict technical procedures according to the manufacturer's standards and increased quality control during the repair process. With a thorough improvement in this technical and managerial aspect, it is hoped that the damage frequency can be reduced and the reliability of the main's engine can be optimally maintained to support operations KM GD.

STUDY OF THE STRESS-STRAIN STATE OF BUSBAR PUNCHING TOOLS RESTORED BY VARIOUS METHODS

Dana Kassymbabina — 2025-11-26

The aim of this study is a comparative analysis of the stress–strain state of busbar punching tools after restoration using different methods. An overview of existing methods for restoring punches and dies was conducted. The analysis showed that each method has its own advantages and limitations. To address this issue, two restoration methods for the busbar punching tool are proposed: hardfacing of worn and damaged surfaces, and replacement of the working part with an insert made of carbon steel. A numerical simulation using the ANSYS software package was carried out to investigate the stress–strain state of busbar punching tools restored by two proposed methods. The simulation focused on determining the stresses in the working zones of the tool, deformations, and the distribution of contact forces. The results made it possible to identify critically loaded areas of the tool design and evaluate the effectiveness of the proposed restoration and modernization methods. The research, the results of which are presented in this article, is funded by the Committee on Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (grant № AP19578884 "Increasing wear resistance and improving the design of the tool of the busbar punching machine").

DESIGN AND IMPLEMENTATION OF A REMOTELY SURFACE VEHICLE (RSV EMAS) POWERED BY RENEWABLE ENERGY FOR AUTOMATED WATER QUALITY MONITORING

Imam Sutrisno — 2025-12-10

This paper presents the design, implementation, and field evaluation of RSV Emas, a compact, solar-powered, remotely operated surface vehicle (RSV) developed for autonomous water quality monitoring. The system introduces a novel integration of three key technologies: renewable energy harvesting for extended mission endurance, a fuzzy-PID hybrid control algorithm for adaptive navigation, and embedded piezoelectric actuators for real-time stabilization in dynamic aquatic conditions. RSV Emas is equipped with a multi-sensor suite capable of measuring temperature, pH, turbidity, and total dissolved solids, with data transmitted wirelessly to a remote dashboard. Field experiments in a controlled freshwater pond demonstrate that the vehicle can operate autonomously for over six hours under moderate sunlight, maintain stable trajectory with less than 0.5 m path deviation, and reduce tilt oscillations by up to 38% through smart material-based stabilization. These results confirm that RSV Emas offers a cost-effective, energy-efficient, and scalable platform for real-time water quality assessment, with potential applicability in environmental management and early pollution detection.

PREDICTIVE MODELING OF TRACK QUALITY INDEX WITH NEURAL NETWORKS

Ivona Nedevska Trajkova — 2025-12-14

The Track Quality Index (TQI) was used as a primary metric to assess the structural and geometric condition of railway track infrastructure, which is directly related to traffic safety, ride comfort, and maintenance prioritization. This paper presents a predictive modeling approach aimed at forecasting future TQI values by incorporating historical measurements, geometric characteristics, and operational parameters. The analyzed dataset consisted of 821 observations of track sections collected over several measurement cycles. It included explanatory variables such as previous TQI levels, train operating speed, traffic volume, and infrastructure elements like tunnels, bridges, and records of ballast tamping. A General Regression Neural Network (GRNN) was trained using 657 data samples and validated on 164 samples, achieving a coefficient of determination (R²) of 0.699, a root mean square error (RMSE) of 4.70, and a mean absolute error (MAE) of 3.55. The results confirmed that neural networks are suitable for short-term predictions of track conditions, facilitating more effective planning and optimization of maintenance interventions. The proposed framework supports engineering decision-making related to condition-based maintenance of railways.

EXPERIMENTAL ENHANCEMENT OF SOLAR WATER HEATER FOR USING IN A LOW TEMPERATURE WITH HEAT EXCHANGER VERTICAL COLLECTOR BY CONCENTRATOR AND ACETONE

Dheya G. Mutasher — 2025-12-13

This study presents an innovative solar water heating system that integrates a condenser with water or acetone as the working fluid, offering a promising solution to key challenges in solar energy utilization, like cost efficiency, optimal angle alignment, and material limitations. The proposed design significantly improves thermal performance, making it a viable alternative to conventional flat-plate solar collectors. Experimental results demonstrate a significant efficiency improvement of 80% compared to conventional systems. This improvement is referred to two main factors: First, advanced collector geometry: The utilize of a spiral-coil tube design enhances radiation absorption in all directions, reducing dependence on precise solar angle alignment. Second, improved heat transfer fluid. where the acetone used as the working fluid due to its superior thermophysical properties significantly improves heat transfer rates within a thermosyphon-based natural circulation system. The efficiency of acetone was found to be higher in both the single- and double-loop cases by 77.66% and 70.78%, respectively, compared to water. The combination of these innovations ensures consistent energy capture and heat production, even under suboptimal conditions. Furthermore, the system's scalability and adaptability suggest it could be widely applied in engineering contexts, including residential, industrial, and agricultural heating. By addressing cost constraints and efficiency limitations, this spiral solar collector emerges as a revolutionary alternative to conventional solar thermal technologies, accelerating the adoption of renewable energy solutions.

ASSESSMENT OF PROCESSING CAPACITY OF RAILWAY STATIONS BASED ON STATISTICAL ANALYSIS METHODS

Ihor Taran — 2025-12-14

The purpose of the study is to improve the methods of assessing the processing capacity of railway stations based on scientific observation data. The paper considers a large private station that provides transport services to port terminals when performing railway and water transportation. The research is performed based on methods of analysis of time series and theory of operation of railways. The study established the maximum permissible volume of work for the port station and also assessed the impact of the combination of diverse types of goods on the amount of its processing capacity. The scientific novelty of the work is to improve the methods of evaluating the processing capacity of railway stations based on the methods of statistical data analysis. Unlike the existing method, the method allows you to more accurately consider local features of stations. The practical value of the results obtained is that they allow to predict the work of the station in the conditions of accidental flow of port terminals requests for servicing and avoid overload. This enables the station management to develop more efficient strategies for managing its work.

BIBLIOGRAPHIC ANALYSIS AND DECISION FACTORS IN THE OPTIMIZATION AND MATHEMATICAL MODELS OF GROUND SOURCE HEAT PUMP SYSTEMS

Viktor Zonai — 2025-11-11

Due to the European Union's reinforced efforts in energy conservation, Ground Source Heat Pump (GSHP) systems have become a prominent technology for improving energy efficiency and environmental sustainability. These systems, which exploit stable underground temperatures for heating and cooling, are leading the charge in reducing energy consumption. However, the mathematical models used to predict the performance of GSHP systems are still under development and frequently overlook local geological and climatic variations. This oversight can lead to significant inaccuracies in the systems' design and efficiency. This study aims to enhance the mathematical modelling and optimization of GSHP systems to improve their operational efficiency and predictive accuracy. By conducting a comprehensive bibliometric analysis of the existing literature using the Web of Science database and VOSviewer software, the research maps the evolution of GSHP technology over the past decade, identifying key research centres and emerging trends. The findings from the analysis indicate a robust linkage between the optimization and mathematical modelling efforts within the field, highlighting an increasing focus on integrating renewable energy sources to bolster system efficiencies. Prominent institutions and significant publications have been identified, reflecting a shift towards more sustainable and energy-efficient solutions. The study concludes that refining the mathematical models of GSHP systems is crucial for optimizing their performance and sustainability. It emphasizes the necessity for models that can accurately reflect local environmental conditions. Moreover, the research supports continued collaboration between academia and industry to further develop and apply GSHP technology. Future research directions should aim to address the technological and market challenges to enable wider adoption and integration of these systems into existing energy framework.