Journal of Engineering and Thermal Sciences
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Vibrodiagnostics and dynamic operation of reinforced concrete sleepers under the influence of moving load
Get PDFVidrodiagnostics is one of the methods of monitoring and diagnosing the railroad track for defects and damages. Determination of vibration (dynamic) impact on the track from the rolling stock load is possible with the help of vibration sensors - velocimeters and accelerometers. The article presents the results of full-scale (operational) tests of reinforced concrete sleepers with different types of bonding on three sections of the railroad mainline. The dependences between the maximum amplitudes of vibration displacement, vibration velocity are determined. The purpose of this study was to identify the main causes of defects in reinforced concrete sleepers by vibrodiagostic method, to identify the greatest attenuation of vibrations of the track structure, damping of vibration from passing rolling stock and determination of the best dynamic operation of the track. This research will help further technological and economic development of railroads, as well as maintain safe operation of the main network of the Republic of Kazakhstan
Scientific and practical substantiation of transient processes in asynchronous electric motors of mainline electric locomotives
Get PDFThe research work focuses on scientifically substantiating the operating conditions of small and medium-power auxiliary asynchronous electric motors used in mainline electric locomotives under JSC “Uzbekistan Railways”. The aim is to provide a scientific basis for the operational efficiency of auxiliary asynchronous electric motors and, based on the research findings, to conduct a practical investigation of their service life. This, in turn, will enable timely maintenance of auxiliary asynchronous electric motors in locomotives. Additionally, it will contribute to improving the performance indicators of auxiliary asynchronous electric motors
Enhancing loess deformation resistance using waste tire rubber particles
Get PDFLoess, characterized by its large pore structure and vertical joints, is prone to collapsible deformation upon moisture infiltration and significant settlement under load, threatening the stability of buildings and infrastructure. This study systematically investigates the effects of rubber particle size (10, 20, 40, and 100 mesh), content (0 %, 5 %, 10 %, 15 %, and 20 % by volume), moisture content, and freeze-thaw cycles on the deformation properties of loess. This systematic investigation distinguishes itself by using waste tire rubber particles as the sole amendment to elucidate both the individual and coupled effects of these factors. Results demonstrate that incorporating rubber particles significantly reduces the compression coefficient of loess, with optimal compressibility achieved at a 5 % rubber particle content and 40 mesh particle size. The collapsibility coefficient is minimized at a 20 mesh particle size with the same 5 % content. Moisture content significantly influences deformation behavior, with both high and low levels increasing the compression and collapsibility coefficients. The study also reveals that rubber particle-loess mixtures exhibit superior freeze-thaw resistance, with smaller increases in deformation coefficients after multiple freeze-thaw cycles compared to remolded loess. The particle size and content of rubber particles are identified as the most important factors influencing the compressibility and collapsibility of loess. This research provides specific guidelines for optimizing rubber particle size and content, controlling moisture levels, and evaluating freeze-thaw impacts to enhance the engineering performance of loess. The findings offer a scientific basis for sustainable waste tire management and advance the application of rubber particles in geotechnical engineering
Enhancing the strength of steel grade 45 guide rails for ball rolling using the chemical-thermal carbonitriding method
Get PDFThe enhancement of guide rail strength for ball rolling applications is crucial to improving the durability and operational efficiency of the manufacturing process. One effective method for achieving this is carbonitriding, a chemical-thermal treatment that forms a hardened surface layer by saturating the material with both carbon and nitrogen at relatively low temperatures. This study was aimed at improving the mechanical properties of the guide bar used to hold balls on the rolling axis in ball rolling mills by chemical-thermal strengthening-carbonitration. Specimens of mild and medium carbon steel were used as tests. The process consisted in immersing the specimens in a bath with molten salts at a temperature of 570 °C and holding for 1.5 hours. The samples were then cooled in oil and then cleaned with high-pressure water. The study showed that the melt of salts based on urea and potassium carbonate saturates the steel surface with nitrogen and carbon, forming a hardened layer. The depth of the hardened layer depends on the exposure time, but after one hour, the penetration of diffusing substances slows down. This is due to the saturation of the steel crystal lattice with alloying elements (carbon and nitrogen) during carbonitration. The maximum hardening depth for high-alloy tool steels is 0.05-0.12 mm, for carbon steels 0.1-0.6 mm. Carbonitration can be used to increase the hardness, strength, wear resistance of balls without increasing the brittleness of the part
An analysis of the ultrasonic technology to stitch materials, and conceptualization and realization of a new sewing machine
Get PDFUltrasonic stitching is a thread-free and green technology for stitching fabrics, which uses the vibration energy of high frequency to transform it into heat at the joint to achieve local fusion. This paper provides the conceptual design and experimental validation of a roller-based ultrasonic sewing system for thermoplastic and composite textile. This work introduces a portable roller-type ultrasonic actuator coupled with a physics-based thermal model which allows the controlled and threadless joining of textiles, which is the main innovation of this paper. When operated at 27 kHz, 100 W and contact pressure of 5 MPa, the method gives maximum lap shear strengths of 86 N for polyester and 67 N for cotton + LDPE. The measured results define the process window and show the possibility of low-waste industrial utilization. Novelty: (I) a small size ultrasonic stitching unit based on the roller technology; (II) a closed-form thermal model for the relationship between energy input and joint strength; (III) validated process parameters towards a sustainable textile bonding application
Complex fault diagnosis in wind turbine bearings: a hybrid approach combining the improved feature mode decomposition and convolutional neural networks
Get PDFThe complex noise interference and diverse fault-induced signals in vibration data from wind turbine equipment pose significant challenges for bearing fault diagnosis, including cumbersome methodologies, prolonged processing times, and compromised accuracy. To address these limitations, this study proposes a novel composite fault diagnosis framework that integrates Feature Mode Decomposition (FMD), Fast Spectral Kurtosis (FSK), and Convolutional Neural Network (CNN). While conventional Empirical Mode Decomposition (EMD) exhibits limited noise robustness and struggles to extract subtle fault signatures in composite failure scenarios, our approach employs FMD to decompose fault-related intrinsic mode functions (IMFs)and further filters the IMF components using fast spectral cliffs with enhanced feature separability. Subsequently, the Short-Time Fourier Transform (STFT) is applied to derive time-frequency representations, followed by Fast Spectral Kurtosis analysis to identify optimal demodulation bands for non-stationary signals. The energy spectrum of denoised signals is converted into grayscale images, serving as input to a tailored CNN architecture for hierarchical feature learning. Experimental validation demonstrates that this hybrid methodology achieves a fault recognition accuracy of 98 % under compound fault conditions, outperforming conventional EMD-based approaches in terms of noise immunity and diagnostic precision. Comparative analysis reveals an 8 % improvement in detection reliability over standalone deep learning models, particularly in low signal-to-noise ratio (SNR) environments. The proposed framework offers a robust solution for multi-fault identification in industrial Bearing machinery, demonstrating superior generalization capability across varying operational conditions
Research progress on 3D printed geopolymer materials
Get PDFThe integration of 3D printing technology with geopolymer materials offers a sustainable alternative to conventional construction methods, significantly reducing CO2 emissions. However, challenges such as rapid setting, limited workability, and weak interlayer bonding limit their broader application. This review summarizes recent progress in 3D printed geopolymer composites, focusing on materials selection, rheological optimization, buildability, and mechanical performance enhancement. Strategies including the use of rheology modifiers, fiber reinforcements, nano-additives, and process optimization have shown promise in improving printability and structural performance. Remaining challenges, such as balancing setting time and printability and enhancing interlayer adhesion, are also discussed. Future research directions are proposed to further advance the development of high-performance, low-carbon geopolymer 3D printing materials for sustainable construction
Implementation of lookup tables for different optimization strategies of semi-active car suspension system
Get PDFRoad irregularities and various vehicle loads influence comfort and safety levels. Owing to these changes, the driver cannot quickly and easily find the best driving parameters. Control of damping in a semi-active suspension adjusts the damping process in the vehicle to minimize the acceleration of the crew. This ensures comfort for them, influencing the level of fatigue of the driver and safe driving. A theoretical analysis was implemented using a mathematical full-car model in Simulink/MATLAB. We performed a simulation of a vehicle with all passengers passing various artificially generated road profiles at different velocities. We optimized the damping coefficient for the maximum comfort level using one, two, or four damping values, implementing different optimization strategies. The obtained research results were finalized by the conclusions
Research on rockfall scratch damage of FRP-coated oil and gas pipelines based on finite element method
Get PDFOil and gas pipelines, as vital arteries for energy transportation, play a crucial role in ensuring the supply of energy. However, under harsh geological conditions and external forces, the pipeline's anti-corrosion layer is susceptible to damage, particularly the destruction caused by external forces such as rockfall. This study focuses on the performance of a new type of anti-corrosion material-Fiber Reinforced Polymer (FRP) coating-under rockfall scratch, and compares it with Polyethylene (3PE) coating. By establishing a three-dimensional finite element model of the pipeline and rockfall, the study simulates the scratch process of rockfall on FRP and 3PE coated pipelines, analyzing the impact of various parameters on the coating damage. The results indicate that the FRP coating has a significant advantage in resisting rockfall damage, effectively dispersing and absorbing the impact force, thereby reducing damage. Moreover, parameters such as rockfall moving velocity, angle, penetration depth, and coating thickness significantly affect the degree of damage to the FRP coating. This research provides theoretical basis and technical support for the protection of oil and gas pipelines, which is of great importance for enhancing the safety and reliability of pipelines
Engineering protection of the subgrade from sand drifts using geomaterials, as exemplified by the Bukhara-Miskin railway line
Get PDFIn arid regions of southwestern Uzbekistan, protecting the railway subgrade from wind-blown sand is a priority engineering task. This paper presents a systems approach to selecting and applying geomaterials for the Bukhara–Misken railway: climatic-geotechnical zoning, assessment of sand-drift intensity, a decision matrix based on wind loading, and a techno-economic evaluation. The proposed measures (geogrids, geotextiles, geomats, aerodynamic barriers, and biopolymer stabilizers) enhance subgrade stability, reduce maintenance costs, and extend maintenance intervals. The approach is transferable to transport infrastructure in desert zones of Central Asia