Journal of Engineering and Thermal Sciences
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Digital solutions for the transition to a sustainable public transport system in Tashkent
Full text linkThe purpose of this study is to analyze the prospects for transitioning the city from automobile-dominated mobility to a public transport-oriented system. The methodological framework is based on the analysis of transport infrastructure. The research is conducted on the example of Tashkent – the capital of Uzbekistan – characterized by a high level of motorization and significant commuter migration. The study concludes that a successful transition to public transport requires a phased implementation, involving infrastructure modernization, digitalization, regulation of motorization, and transformation of citizens’ mobility behavior. The novelty of this study lies in developing a digital transition model for Tashkent that integrates international best practices (Berlin, London, Singapore) with the local transport and socio-economic conditions
Finite element analysis of grouted cylindrical wedge anchors for prestressed CFRP plates
Full text linkIn current research, the anchoring performance of prestressed Carbon Fiber Reinforced Polymer (CFRP) plate anchors is primarily acquired through experimental methods, which makes it difficult to capture the internal deformation and stress distribution of the anchor. In this paper, a model of a grouted cylindrical wedge anchor for prestressed CFRP plates is established using the finite element analysis software ABAQUS. The simulation replicates the processes of anchor relaxation at the release end and the second tensioning at the tensioning end, using a geometrically nonlinear static general analysis step. This approach yields the shear stress distribution at the interface between the internal adhesive and the carbon fiber plate, as well as the deformation and normal stress distribution within the carbon fiber plate. The analysis results provide technical support and theoretical backing for experiments and research on prestressed CFRP plate grouted cylindrical wedge anchors
Simulation and testing of modal characteristics of automotive disc brake
Full text linkModal characteristics serve as a critical basis for evaluating the vibration and noise performance of automotive brakes. Using the finite element software ABAQUS, modal simulations were performed on the assembly comprising brake disc, brake pad, piston, caliper, and retainer, calculating the modal shapes and frequencies within the specified range. Modal parameters of each component within this range were obtained through measurements using a Doppler laser vibrometer and an NI data acquisition system, as well as hammering tests. By comparing the experimental and simulation results, it was found that the errors for all components were within 5 %, meeting the accuracy requirements. This validation confirms the accuracy of the structural and material parameters of each brake component. The results demonstrate that this type of brake is less susceptible to low-frequency resonance, as the first-order natural frequencies of both the brake disc and the brake pad exceed 1 kHz
Numerical simulation of surrounding rock damage induced by different explosive casings in slotted charge blasting
Full text linkTo investigate the influence of slotted charge casings made of different materials on surrounding rock damage, single-hole and double-hole numerical models were established using finite element software. The effects of five casing materials – Cuprum (Cu), Aluminum (Al), Polyvinyl Chloride (PVC), Acrylonitrile Butadiene Styrene (ABS), and Polymethyl Methacrylate (PMMA) – on rock damage were compared, with particular attention to the evolution of stress distribution, crack propagation, and directional energy transfer in the surrounding rock. The results show that in the single-hole model, Cu casings exhibit pronounced fracture directionality and strong crack connectivity along the slotting direction, whereas in the double-hole model, the interaction between boreholes further enhances fracture penetration. PVC demonstrates stable main-fracture orientation, while PMMA casings provide moderate energy transfer and effective control of damage in both single-hole and double-hole cases. These findings offer a theoretical reference for the optimized design of slotted explosive charges and material selection, and provide technical support for achieving efficient, low-damage rock blasting in engineering applications
Pure IMU localization for intelligent platforms with CNN adaptive invariant extended Kalman filter noise fusion
Full text linkIn the context of intelligent vehicles, low- and medium- precision Inertial Measurement Units (IMU) are plagued by high levels of noise and considerable output uncertainly. When positioning and attitude estimation rely solely on IMU data, errors rapidly accumulate over time. To address this issue, this paper introduces a Convolutional Neural Network (CNN)-based noise-adaptive invariant extend Kalman filter (IEKF) vehicle localization. The proposed approach develops CNN models tailored for IMU measurement data as well as the process noise and observation noise in the IEKF. An enhanced CNN architecture and convolution mechanism are designed to dynamically adjust the covariance matrices associated with both process noise and observation noise in response to varying IMU input. This integration with IEKF principles ensures real-time positioning while achieving high accuracy in position prediction. The proposed method was tested and validated on 16 IMU sequences from the KITTI dataset, resulting in a relative translation error performance improvement ranging from a minimum of 10 % to a maximum of 24 % when compared to four existing methods. Additionally, its performance was further evaluated through various metrics including cumulative distribution of errors, root mean square error, and absolute position error. Trajectory tracking experiments further demonstrated that the proposed method produces smoother localization curves and more stable positioning performance
Modeling of the transportation process on the Kokand-Andijan section of the Kokand regional railway track junction of the Uzbek railway
Full text linkThe article presents original research results on the substantiation of the forward motion parameters of a freight train with a fixed maximum mass of the train and the main traction and operational characteristics of the energy efficiency of O’z-EL type AC freight electric locomotives on a real flat section of the railway. Energy-optimal control modes for the movement of the aforementioned freight train by electric locomotives of the O’z-EL series have been developed using the original computer hardware and software complex KORTES, and their traction and energy characteristics are presented in the form of numerical values and graphs with an error of no more than five percent compared to the practical data of the Kokand locomotive depot of the Uzbek Railway. The above results will be further used by the authors to evaluate the effectiveness of various options for energy-optimal control modes for the power equipment of the Oʼz-EL series electric locomotives when implementing freight transportation on sections of the Uzbekistan railway industry of varying complexity under real operating conditions
Towards the efficiency research of the working process of locomotives diesel under operating conditions
Full text linkA method is proposed for quantitative assessment and justification of the criterion of the rationing indicators of external and boost air temperature factors on the qualitative component of the working process of two-stroke supercharged diesel engines under various load conditions of the traction power plant of operating diesel locomotives. The results of the study were obtained in the numerical values and graphs, as well as analytical dependencies (equations) designed to substantiate the parameters under study, including their average values under different operating mode diesel and ambient temperatures. These studies are recommended to continue with the aim of studying the intensity of the dynamics of the decrease or increase in the relative filling coefficients of the 10D100 diesel cylinders with air and developing a methodology for predicting the criterion of the influence of the rationing of boost indicators and outside (external) air on the operating process of diesel locomotives diesels
Neural network-based ANC algorithms: a review
Full text linkActive Noise Control (ANC) technology is of great value in the field of noise mitigation. Recently, traditional linear adaptive control methods, represented by the FxLMS algorithm, are structurally simple and computationally efficient but often suffer from performance degradation or even failure in practical applications due to nonlinear system factors. For this reason, neural network-based ANC methods have attracted significant research interest for their strong nonlinear processing capabilities and have gradually emerged as a focal point for addressing nonlinear ANC problems. This paper systematically reviews the research progress of neural networks in the field of nonlinear ANC, focusing on two key dimensions: network architecture and training methods. In terms of architecture design, existing studies primarily enhance performance through topology optimization, improvements to functional link artificial neural networks, and innovative hidden layer designs. Advancements in training methods focus on the optimization of loss functions, innovation in weight update algorithms, and the introduction of other training strategies. In the future, neural network-based ANC algorithms will continue to deepen, with potential development paths including the integration of advanced network architectures such as Generative Adversarial Networks (GANs), optimization of utility functions, pruning of hidden layers, improvement in loss function design, and the adoption of more efficient training strategies. These efforts will further improve algorithm performance and ultimately provide robust support for achieving more precise and efficient active noise control
Improved iterative reweighted L1 norm minimization method for sound source identification
Full text linkSparse reconstruction algorithm is one of the main research topics in compressed sensing. To address the shortcomings of existing iteratively reweighted l1-norm minimization methods, which exhibit poor performance in low-frequency sound source identification and weak anti-interference capability, this paper proposes an improved iteratively reweighted l1-norm minimization method. Unlike traditional methods, this method introduces a log-sum penalty function and constructs a surrogate function, transforming the problem into an effective form for solving the source strength distribution vector. Through numerical simulations comparing the two methods under different frequencies and signal-to-noise ratios (SNR), the results demonstrate that the proposed method enhances both the sound source identification accuracy and anti-interference capability of the algorithm, while also being able to adapt to lower frequency ranges
Equations of motion for the rigid and elastic double pendulum using Lagrange’s equations
Full text linkThe double pendulum is a well-known system exhibiting nonlinear dynamics and chaotic behavior. This study extends the conventional rigid double pendulum by introducing elastic extensions in the links, leading to a system known as the elastic double pendulum. The mathematical model incorporates both rotational and translational motion, accounting for elastic deformations using Hooke’s Law. The governing equations are derived using Lagrangian mechanics, considering both gravitational and spring potential energy contributions. Numerical simulations are performed to compare the motion of the elastic and rigid double pendulums, highlighting differences in phase-space trajectories, energy transfer, and stability characteristics. Results demonstrate that elasticity introduces additional oscillatory components, increases system nonlinearity, and affects the overall predictability of motion. These findings provide insights into elastic multi-body dynamics and have potential applications in flexible robotic arms, soft mechanisms, and bio-inspired locomotion