Journal of Engineering and Thermal Sciences
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Numerical simulation of chloride ion transport in concrete based on a random aggregate model
Full text linkA three-dimensional stochastic aggregate model of concrete was established using the Monte Carlo method, and a numerical simulation of chloride ion diffusion at the microscopic level was conducted. The study investigated the migration behaviour of chloride ions in concrete regarding mixing proportions and temperature. The results showed that compared to the simulation results at an ambient temperature of 20 ℃, the chloride ion diffusion coefficient increased by 31 % and 70.5 % for concrete at 25 ℃ and 30 ℃ at 28 days, respectively. The chloride ion penetration depth increased by 17.3 % and 34.9 % for concrete at 25 ℃ and 30 ℃, respectively. With a slag content of 10.4 %, 20.8 %, and 27.1 %, the chloride ion diffusion coefficient at 28 days decreased by 1.4 %, 2.7 %, and 4.1 %, respectively. With a fly ash content of 8.3 %, 16.7 %, and 25 %, the chloride ion diffusion coefficient at 28 days decreased by 2.1 %, 5.4 %, and 9.2 %, respectively. Both slag and fly ash can reduce the chloride ion diffusion coefficient in concrete, with fly ash showing better effectiveness than slag. A water-to-binder ratio of 0.4, combined with 27.1 % slag and 25 % fly ash as cement replacements, can effectively improve the resistance of concrete to chloride ion attack. The micro-scale finite element model of concrete, developed through Monte Carlo simulation, offers enhanced visualization of chloride ion penetration processes under varying mix proportions and temperature conditions
Multi-mode frequency response prediction of milling robot based on feature transferring with small sample sets
Full text linkIndustrial robots are increasingly used in machining due to their cost-effectiveness and larger work envelopes. However, their relatively low structural stiffness makes them vulnerable to machining chatter, which negatively impacts both process stability and surface quality. Accurate prediction of the multi-mode frequency response function (FRF) of robotic milling systems is crucial to ensure process stability. Traditional FRF prediction approaches, however, often require extensive experimental procedures, are complex, and are time-consuming. To address these challenges, this study proposes an innovative feature-transfer-based method for multi-mode FRF prediction in milling robots, requiring only a minimal set of impact tests. The method organizes measured FRFs into second-order complex tensors, facilitating the transfer of features between different postures. Multi-mode parameters of the tool-tip FRF under the source posture are extracted using the least-squares complex exponential (LSCE) method and assembled into a label vector. A complex-kernel extreme learning machine with augmented inputs (CKELM-AI) is then trained to predict the tool-tip FRF under the target posture. Additionally, a virtual sample generation strategy based on CKELM-AI and feature augmentation, including statistical, frequency, and time-frequency features, is applied to enhance prediction accuracy. Experimental validation on a milling robot demonstrates that the proposed method significantly improves both prediction efficiency and accuracy, establishing a new, more efficient approach for predicting multi-mode FRFs without the need for extensive testing
Fault diagnosis method for wind turbine rolling bearings based on adaptive deep learning
Full text linkIn response to the problem of difficulty in extracting fault features of rolling bearings in wind turbine transmission systems under complex working conditions, which limits the accuracy of fault diagnosis. This article proposes an Adaptive Deep Learning based Rolling Bearing Fault Diagnosis Method (ADLM). Introducing dynamic convolution into Convolutional Neural Networks (CNNs) can adaptively capture data features; At the same time, the fishing optimization algorithm (CFOA) was used to optimize the hyperparameters of the bidirectional long short-term memory network (BiLSTM), and the CFOA-BiLSTM network was constructed to fully leverage its advantages in time series analysis. The specific implementation steps are as follows: first, preprocess the collected vibration signals and divide the processed dataset into a training set and a testing set; Then, parallel adaptive convolutional neural networks (ACNN) are used to process the training set and extract spatial domain local features from the vibration signal; Then, the features extracted from the two branches are weighted and fused through a dynamic weight adjustment mechanism, and the fused features are input into the CFOA-BiLSTM network to further capture the time-dependent features of the signal; Finally, the extracted features are input into the classifier to complete model training, and the model performance is evaluated using a test set. Experimental verification shows that on the dataset of Southeast University, the diagnostic accuracy of the ADLM model reached 98.52 %, demonstrating good reliability, robustness, and superiority in the diagnosis of rolling bearing faults
Mathematical modeling of the rotating drum granular fill flow oscillatory stability
Full text linkDrum-type machines have become widely used in many industries for processing various granular materials. An innovative direction for significantly increasing the energy efficiency of such equipment is the use of self-oscillating working processes. Self-excitation of auto-oscillations allows you to bring into pulsating flow and activate the passive part of the intra-chamber filling and significantly enhance the interaction of granular particles with each other and with the surrounding environment. The purpose of the study is to build a mathematical model of the conditions and factors of oscillatory instability of the flow of polydisperse granular filling in the chamber of a rotating drum. The research methodology includes analytical modeling of wave processes and experimental modeling of manifestations of instability of the filling flow. The inertial mode of flow of the active part of the filling in a shear flow state is analyzed, the behavior of which is described using averaged values. Based on the results obtained, an increase in instability with an increase in the dilatancy of the medium during deformation is established and the destabilizing effect of the damping action of the fine fraction on the interaction of particles of the coarse fraction is revealed. The main scientific novelty of this study is the identification of the regularities of the unsteady motion of the oscillatory system of a filled drum. The study confirms the possibility of generating, under certain conditions, self-excitation of auto-oscillations of the intra-chamber filling, which is a decisive factor in the predicted intensification of the technological process. The results obtained are valuable for researchers and engineers involved in the study and design of innovative energy-efficient working processes of drum machines
Direct writing and parameter optimization of microchannels in glass microfluidic chips using RF CO2 laser
Full text linkMicrofluidic chips, featuring microchannels as key components, are crucial in chemistry, biology, and medical diagnostics. This study uses an RF CO₂ laser for direct writing on glass substrates, offering a cost - effective and fast fabrication method for microfluidic chip development. We investigated the RF CO2 laser’s energy distribution to set guidelines for processing line widths. Key parameters, laser power, processing speed, PPI, and repetition frequency, were studied for their effects on microchannel surface width and depth. We also examined how processing speed, laser power, and surface water films affect edge chipping on glass. Findings show that when PPI exceeds 2000 and processing speed is above 2000 mm/s, microchannel surfaces are smoother. There is a linear relationship between microchannel surface width/depth and laser power/repetition count. To minimize edge chipping, glass processing should remove internal stress, use high speeds, and apply low laser power. Edge chipping can undermine microchannel quality; thus, controlling processing parameters to reduce it is vital for high-quality microfluidic chip fabrication
Parametric study of the noise of a propeller-driven fixed-wing unmanned aerial vehicle with a piston engine
Full text linkThe results of full-scale acoustic tests of a Ptero-G0 unmanned aerial vehicle (UAV) in an anechoic chamber are presented. The aim of the work is to determine the acoustic characteristics of a Ptero-G0 UAV and to assess the influence of various parameters on the noise level of the device. A unique aspect of the experiment is that a full-scale apparatus with a power plant including a single-cylinder 4-stroke piston engine and 2-bladed fixed-pitch propeller, was studied. Data on the spectral, energy and directivity characteristics of the UAV and its power plant were obtained. The tests assessed the effects of incoming flow velocity, power condition of the power plant, pitch angle of the UAV, propeller diameter, and vibrations of the bonnet on the UAV noise. In particular, increase in the power condition (engine speed) and incoming flow velocity led to an increase in spectral noise levels in the 1/3-octave frequencies bands ranging from 40 to 10,000 Hz. At the same time, background levels up to 40 Hz were determined by background noise. The influence of engine speed and incoming flow velocity on the directivity pattern has not been established. An increase in propeller diameter at a constant speed resulted in higher circumferential speed of the propeller and thrust, as well as increased load on the engine. As a result, intensity of the tonal components of propeller and engine noise increases. A slight decrease in diameter (by 6 %) led to a decrease in the overall noise level by 1.3 dB. Placing the engine in the bonnet without a vibration insulation system led to an increase in the overall sound pressure levels by up to 2.5 dB
Dynamics and stability analysis of a single-mass oscillatory system with a slider-crank vibration exciter
Full text linkTraditional slider-crank mechanisms transmit high loads through the mechanical structure, hindering the design of compact machines. The paper considers the dynamic behavior of a single-mass oscillatory system actuated by a slider-crank excitation mechanism. The research methodology involves mathematical modeling and computer simulation to analyze the trajectory and kinematic characteristics of the considered oscillatory system. The dynamic diagram of the single-mass vibratory system is considered, and the mathematical model describing its motion is derived using Euler-Lagrange equations. The obtained results show the time response curves of the oscillating mass plane-parallel motion under different excitation conditions, as well as the amplitude and phase responses as functions of frequency. The primary scientific novelty of this research is determining the influence of specific design parameters of the vibration exciter on the trajectory of the working member motion, as well as defining the stability of the response at different frequencies. The research highlights the possibility of generating circular, elliptical, and rectilinear vibrations of the working member depending on the specific operation, such as conveying, screening, sieving, or compacting. This adaptability is crucial for tailoring the system to different industrial applications and optimizing its performance for specific tasks
Dynamic analysis of a new type of linear vibrating screen with adjustable vibration direction angle
Full text linkTo address the limitations of conventional vibrating screens, such as restricted operational conditions and poor adaptability, this study proposes a new type of linear vibrating screen with an adjustable vibration direction angle. By altering the fixed positions of the bolts between the vibration motors and motor supports, the angle between the vibration direction and the screen surface can be modified to achieve vibration direction angle adjustment, thereby enabling the screen to adapt to diverse working conditions. Creo and ANSYS Workbench were employed to conduct dynamic analyses of this innovative design, revealing displacement and stress distribution maps under various vibration direction angles. The results demonstrate that the new type of vibrating screen exhibits excellent structural strength and stiffness, effectively meeting industry requirements. This study provides valuable insights into the design of linear vibrating screens
Investigating the mechanism of X80 pipeline failure under landslide impact
Full text linkAs energy demand continues to grow and environmental issues become more severe, the development and utilization of clean energy natural gas are becoming increasingly important. This paper focuses on the impact mechanism of landslide disasters on pipelines, analyzing how landslide displacement, width, pipeline wall thickness, and internal pressure affect pipeline stress and displacement. The study finds that landslides cause stress concentration at the middle and boundary positions of pipelines. As landslide displacement increases, pipeline stress also increases. For example, when landslide displacement is 1.2 meters, pipeline stress is approximately doubled compared to when the displacement is 0.6 meters. This research aims to explore the impact mechanism of landslide disasters on the stress response of natural gas X80 pipelines, with the goal of providing technical support for their stability and reliability
Optimization of the dynamic stiffness of the body attachment points for a certain vehicle model
Full text linkTo solve the issue of abnormal vibration while accelerating during the development of a certain vehicle model, this paper utilizes the transfer path analysis (TPA) method to identify the key factors contributing to abnormal noise and vibrations within the vehicle. Through a combination of theoretical derivation and simulation analysis, the study examines the dynamic characteristics of the vehicle’s attachment points, particularly focusing on the shock absorber mounting locations. Based on the findings, a specific method for optimizing the dynamic stiffness of these attachment points is proposed. This optimization significantly improves the vehicle’s NVH (Noise, Vibration, and Harshness) performance, thereby reducing unwanted noise and enhancing the overall comfort and driving experience. The paper offers valuable insights and practical solutions to improve vehicle development processes and ensure superior NVH outcomes