Table of Content

25 June 2023, Volume 51 Issue 6

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2023, 51(6):  0. 

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Traffic & Transportation Engineering

User Portrait Method of Freeway Freight Car for Risk Identification of Freight Transportation



LIN Peiqun, GONG Minping, ZHOU Chuhao

2023, 51(6):  1-9.  doi:10.12141/j.issn.1000-565X.220525

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At present, the freight car overload phenomenon is coming from bad to worse, in order to improve the efficiency of freight car control on the highway and the level of safety in the freight transport, a freight transport risk level identification model based on user portrait of freight risk was proposed. Firstly, based on highway toll data, taking freight car as the research object, a user portrait system for freight transport risk identification was developed from the aspects of driving behavior and operation status. Then，the sample data was cleaned and the label index was extracted and analyzed. Then, K-means++ algorithm was applied to obtain the classification results of freight transport risk feature portraits. Next, the entropy weight method was used to score the freight risk of all kinds of freight car to determine the risk level of all kinds of freight car. Finally, by combining with the relevant indicators of various types of vehicles, the vehicle portrait was completed. Based on the trucking toll data of the entire highway network in Guangdong Province from March to May 2022, the proposed model was used to divide the trucking vehicles into five categories. Among them, “the freight car of high risk and high workload” accounted for 5.42%, the freight car of higher risk and night-driving and overloaded ”accounted for 19.12%, “the freight car of medium-risk and overspeed” accounted for 12.85%, “ the freight car of low risk and low-frequency” accounted for 37.00%, and “ the freight car of low risk and high-frequency ” accounted for 25.61%. The validity of the model was verified by the data of an accident database in Guangdong Province in the same period. The data showed that the relative risk coefficient of high risk vehicles is much higher than that of low risk vehicles. The research shows that the proposed model can effectively identify trucks with high freight risk characteristics. Based on the results of risk grade identification, traffic management departments can carry out high-risk vehicle identification, key inspection of overload and over-limit, and specific message push to guide vehicle driving safety, so as to improve the safety management level of the industry.

A Car-Following Model Driven by Combination of Theory and Data Considering Effects of Lane Change of Side Cars



ZHAO Jiandong, JIAO Lanxin, ZHAO Zhimin, et al

2023, 51(6):  10-19.  doi:10.12141/j.issn.1000-565X.220448

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In order to analyze the following behavior of the target vehicle under the influence of lateral vehicle lane change, this study proposed a combination of theory-data driving following model by combining the multi-velocity difference theoretical following model and deep learning method. Firstly, it considered the following vehicle’s characteristics of maintaining a safe distance between forward and lateral vehicles and being affected by vehicle speed difference. And it proposed a two-lane multi-speed difference following(FS-MAVD) model, the parameters of which were calibrated by differential evolution algorithm. Secondly, it constructed a CNN-Bi-LSTM-Attention data-driven car following model. Convolutional neural network layer (CNN) was used to fully extract forward and lateral vehicle traffic features. Bidirectional long and short term memory networks layer (Bi-LSTM) took driver memory effect into account. The Attention mechanism layer was used to assign model weights. Drivers’ memory duration, model training batches and training rounds are trained based on data. Thirdly, considering the wide applicability of the theoretical model and the characteristics of the data-driven model close to the real value and smooth, the study used the optimal weighting method to combine the two models for prediction. Fourthly, the following behavior sample set was established by using the track data of expressway vehicles shot by UAV, and the model was trained and tested. Compared with the prediction effect of LSTM model, Bi-LSTM model, CNN-Bi-LSTM-Attention model and FS-MAVD theoretical model, the prediction accuracy and error of different models for different vehicles were respectively compared. The results show that the acceleration prediction accuracy of the combined model constructed in this paper reaches 97.64%. The root-mean-square error of prediction is as low as 0.027. Compared with other models, the proposed model can better predict acceleration and deceleration of vehicles affected by lane changing of side vehicles, and better analyze the following behavior of target vehicles.

Design of Speed Limit at Expressway in Rainy Day Considering Drivers’ Visual Search Ability



WANG Linhong, LI Hongtao, LI Ruonan

2023, 51(6):  20-29.  doi:10.12141/j.issn.1000-565X.220552

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In order to solve the problem that drivers cannot accurately recognize the roadside information at expressway due to high speed in rainy day, this study firstly selected vehicle speed, clarity degree of drivers’ visual field pictures, line-of-sight angle and fixation distribution percentage as the attention distribution indicators in rainy day based on the attention distribution theory. And Fisher discrimination analysis method was used to establish the quantitative model of visual search ability. Secondly, a simulation driving software UC-win/Road was used to build an experimental platform. Rainfall intensity and vehicle speed were selected as the influencing factors, the change rule of driver’s attention distribution indicators under the cooperation of the two factors was studied, the relationship between rainfall intensity, speed and visual search ability was established, and the matching scheme between rainfall intensity and speed limit was proposed. The results show that the increase of vehicle speed and rainfall intensity would make it difficult for drivers to observe roadside information. To reduce the driving risk, the driver would change the visual search strategy and increase the focus on the front of the road, which reducing the visual search efficiency of the observation target. Therefore, drivers need to spend more efforts to transfer attention when the matching between rainfall intensity and vehicle speed is unreasonable, resulting in the inability to find roadside information in time. In addition, the overall correct percentage of classification of the model is 85.94%, which indicates that the model can evaluate drivers’ visual search ability. Finally, the speed limit schemes based on stopping sight distance and that considering drivers’ visual search ability of roadside information were compared. The results show that the speed limit calculated based on stopping sight distance is higher. To avoid that drivers cannot accurately identify the roadside information due to the high speed, the speed limit of light-rainy day, moderate-rainy day and heavy-rainy day should not exceed 100, 70 and 50 km/h, respectively.

Dropped Object Detection Method Based on Feature Similarity Learning



GUO Enqiang, FU Xinsha

2023, 51(6):  30-41.  doi:10.12141/j.issn.1000-565X.220604

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To overcome the limitation that the existing dropped object detection methods cannot identify the “unknown category”, this study proposed a dropped object detection architecture based on feature similarity learning. Firstly, the reference image and the query image to be detected were obtained during the dropping process. The appearance features were extracted through a weight-shared siamese convolutional network. Then, Euclidean distance was used to measure dissimilarities between features of reference image and query image. Finally, dropped objects were detected by selecting the pixel from the distance map whose distance value was larger than the fixed threshold. In order to improve its robustness to noise such as illumination change, this paper proposed a novel attention mask unit. And the semantic discriminativeness of the mask was improved through constructing the long-span contextual information and strong supervised learning method. This finally guides the feature response to focus on the appearance changes caused by the dropped objects while ignore the disturbance caused by noise, and solves the problem of feature entanglement between noise and the dropped objects. In order to verify the effectiveness of the method, this study collected data in a real highway scene and built a standard dataset. The results show that the attention mask unit effectively improves the semantic discriminative of features and greatly improves the accuracy of dropped object detection, which achieves F₁ an improvement of 6.4 percentage points. Meanwhile, the algorithm reaches in 30 FPS, which can be performed in real-time. The long-span context information constructed by the feature sequence state transition method is more conducive to attention mask focusing on the projectile feature information, and has stronger anti-noise interference ability. The attention mask contour obtained by strongly supervised learning is more accurate and the model accuracy is higher.

Resilience Evolution of Multi-mode Transportation Network in Urban Agglomeration Based on Risk Diffusion



MA Shuhong, YANG Lei, CHEN Xifang

2023, 51(6):  42-51.  doi:10.12141/j.issn.1000-565X.220486

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It can help improve the risk resilience of urban agglomerations to carry out in-depth analysis of the dynamic resilience evolution characteristics of multi-modal transport networks in urban agglomerations during the risk diffusion phase. Based on complex network theory and its extension theory, this study constructed a multi-modal and multi-level transportation network model for urban agglomerations based on road, railway and air networks. It matched node degree and node betweenness with accessibility, and analyzed their static topological characteristics under risk diffusion. Based on the theory of cascading failure dynamics, it considered the initial risk level, risk warning threshold and risk resilience of nodes at different stages, and constructed a risk dynamic diffusion model based on the nodes and connected edge measures affecting risk diffusion. Considering the characteristics of structural and functional changes under risk shocks, the paper constructed a network structural and functional resilience measurement model, and the resilience performance of multi-modal transport networks was represented by their coupling values. Using the multi-modal transport network of the Guan-Zhong Plain urban agglomeration as the research object, the Python Networkx and Matlab network analysis tools were used to simulate and analyze the dynamic resilience evolution of the multi-modal transport network of the urban agglomeration during the risk diffusion phase with respect to different risk diffusion methods, network reliability, redundancy, robustness and node risk handling capacity coefficients. The results show that the model results are consistent with reality. The network resilience can be effectively enhanced by improving network reliability, redundancy, robustness and node risk handling. Compared to the risk diffusion approach based on the node measure, the risk diffusion approach based on the connected edge measure has greater impact on resilience performance, suggesting that the distribution of route hierarchy levels has a greater impact on the resilience performance of multimodal transport networks in urban agglomerations compared to the number of routes. The overall resilience of a multi-modal, multi-level transport network performs better than that of a single transport network.

Active Disturbance Rejection Control of Active Stabilizer System Based on Particle Swarm Optimization



ZHAO Qiang, LIU Chuanwei, ZHANG Na, et al

2023, 51(6):  52-61.  doi:10.12141/j.issn.1000-565X.220535

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In order to improve the anti-roll ability of vehicle, this paper designed a hydraulic motor-driven active stabilizer control system, and proposed a hierarchical control strategy based on particle swarm optimization (PSO) algorithm. The upper active disturbance rejection controller (ADRC) calculates the anti-roll torque required by the whole vehicle, and the anti-roll torque required by the whole vehicle is distributed to the front and rear axles through a distributor. The lower three-loop proportional-integral-differential (PID) controller receives the anti-roll torque to be provided, calculates the control current and inputs it to the servo valve, so as to drive the motor output shaft to rotate and generates the active torque through the stabilizer bar to realize the active anti-roll control of the vehicle. In order to make the controller has better control effect, the PSO algorithm was used to optimize the upper and lower control as a whole, and the optimized ADRC and PID parameters were input into the vehicle model. In order to make the simulation close to the actual effect, the torsional stiffness of the lateral stabilizer bar measured by the experiment was also brought into the model. The serpentine and double lane shifting conditions were used for simulation on Class C road surface, and the simulation verification was carried out by comparing PSO-optimized ADRC system with passive system, PID control system and unoptimized ADRC system. The simulation data show that the roll angle directly affects the vehicle’s roll stability, the hierarchical control strategy optimized by PSO algorithm can significantly reduce the vehicle’s roll angle, and effectively suppress the instability caused by excessive body roll motion. The active control stabilizer can better provide the required anti-roll torque for the vehicle than the traditional passive stabilizer, and improve the anti-roll ability of the vehicle. The optimized ADRC controller has better active control effect than the passive system and the unoptimized ADRC controller. Under the same working condition, the roll angle is smaller, the anti-roll ability is stronger, the optimized three closed-loop PID response speed is faster, and the tracking performance is better.

Prediction Analysis of Settlement of Existing Road Under Shield Tunneling Based on IPSO-SVR



WEI Haibin, WEI Dongsheng, JIANG Boyu, et al

2023, 51(6):  62-71.  doi:10.12141/j.issn.1000-565X.220553

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At present, there are relatively few studies on the settlement prediction of shield tunnels crossing existing roads in parallel. To accurately predict the influence of different factors on the settlement of existing parallel roads in the shield process, this study proposed a support vector regression prediction model based on the improved particle swarm optimization (IPSO-SVR), which was applied to the surface road settlement prediction of actual subway tunnel engineering. Based on the Changchun Metro Line 6 under-crossing Feiyue Road section project, combined with the shield boring parameters, formation information and road settlement monitoring during the construction of the shield tunnel, this paper used the grid search method of libsvm to reduce the range of hyperparameters, and improved the change of inertia weight and acceleration factor in particle swarm optimization algorithm by combining the nonlinear decline strategy. Finally, IPSO-SVR prediction model was established to achieve the settlement prediction of subsequent sections in the interval. The results show that, comparing the changes of the objective function (mean square error) in the grid search method and in the conventional particle swarm optimization training, the convergence speed of the improved particle swarm optimization is greatly improved; the convergence effect of the objective function is better, and the minimum value is reduced by nearly 15%. The mean absolute error (MAE) of IPSO-SVR prediction of road settlement proposed in this paper is 0.287, the fitting coefficient R² is 0.884, and the average relative error is only 8.91%, which has better performance than back propagation (BP) neural network, support vector regression (SVR) and particle swarm optimization support vector regression (PSO-SVR) prediction models. It can be seen that IPSO-SVR has high precision for nonlinear prediction of multi-factor coupling under complex conditions, and its prediction method is feasible and generalizable. IPSO-SVR can provide a reliable basis for effective control of road settlement and is of great significance for ensuring the normal operation of roads and the safety of shield construction.

Optimization for Steel Frames with Semirigid Connections Based on Hybrid Algorithms



QIU Yudong, WANG Zhan, XIE Zhishen

2023, 51(6):  72-77.  doi:10.12141/j.issn.1000-565X.220494

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The dolphin echo algorithm (DEA) is a meta-heuristic optimization algorithm that simulates dolphins using echolocation to prey and has efficient search capabilities. By analyzing the basic principle of the dolphin echo algorithm, it is found that the selection mechanism of the algorithm can easily lead to the optimization result falling into the local optimal solution, and the algorithm itself does not have the mechanism to jump out of the local optimal solution. Therefore, to improve the global search ability of the dolphin echo algorithm, the genetic algorithm (GA) was introduced, and a hybrid dolphin echo-genetic algorithm (DEA-GA) was proposed: in each iterative step, the offspring was first generated based on the dolphin echo algorithm, and then the crossover and mutation operations with strong search ability in the genetic algorithm were introduced to generate new offspring. The hybrid algorithm combines the advantages of the dolphin echo algorithm and the genetic algorithm, so it not only has the advantages of fast convergence speed and high efficiency of the dolphin echo algorithm, but also takes the advantage of the strong global optimization ability of the genetic algorithm. Moreover, it overcomes the defects of the dolphin echo algorithm that is easy to generate local optimal solutions and the genetic algorithm that is prone to ‘prematurity’. In this paper, a single-span 5-storey and a two-span 10-storey plane frame were used as examples to establish a mathematical model for the optimization of semi-rigid steel frame structures with the objective function of minimizing the total weight of the structure. Genetic algorithm, dolphin echo algorithm and hybrid algorithm were used respectively, and the optimization process was realized by Matlab programming. The results indicate that the total weight of the structure obtained by the dolphin echo-genetic hybrid algorithm is more than 50% smaller than that of the genetic algorithm, and more than 7% smaller than that of the dolphin echo algorithm, and the trend increases with the increase of design variables. At the same time, the hybrid intelligent optimization algorithm is more efficient and effective in the optimization of complex structures.

Energy，Power & Electrical Engineering

Current Self-Balanced Bidirectional DC-DC Converter with Low Current Ripple and High Voltage Gain



WANG Keying, HUANG Yi, WANG Zihao, et al

2023, 51(6):  78-88.  doi:10.12141/j.issn.1000-565X.220265

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As a key interface device of the energy storage module in the integrated energy system, the bidirectional DC converter needs the features of low current ripple, high voltage gain and wide range soft switching. To achieve battery-friendly low current ripple ability, bidirectional DC converters use interleaving technology on the low-voltage energy storage side. However, restricted by the actual production process, this type of interleaved bidirectional DC converter has multi-phase current imbalance problems. In this paper, a current self-balancing bidirectional DC converter without complex control algorithm was proposed based on coupled inductors. In the integrated energy storage scenario, the converter not only has the characteristics of current self-balancing, but also has the comprehensive advantages of low current ripple, high voltage gain and wide-range soft switching. First of all, the converter used the clamp capacitor ampere-second balance to forcefully maintain the interleaved current balance in one switching cycle. Hence the low current ripple characteristic of current self-balance was realized at the circuit topology level. Secondly, the coupled inductor is both an energy storage inductor and a transformer. Through the cooperation of the multi-stage gain structure of the circuit, the high voltage gain characteristic was realized. Finally, the converter used a voltage matching control and phase shifting control strategy to decouple the voltage gain and power direction and consequently soft switching characteristics were guaranteed under different working conditions. The article analyzed the working principle and circuit characteristics of the converter, and designed an experimental prototype with an operating voltage of 30 V to 40 V on the low-voltage side, 400 V on the high-voltage side, and a bidirectional power of 1 kW. The experimental prototype simulated the operating characteristics of the low-voltage side lithium battery under different operating voltages, power levels and directions, thus effectively verifying the feasibility of the topology.

Numerical Analysis of Performance of Cyclone-Tube Demister Based on Orthogonal Design



LIU Dingping, ZHANG Xiangyang, CHEN Aihua, et al

2023, 51(6):  89-96.  doi:10.12141/j.issn.1000-565X.220655

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Facing the increasingly strict requirements of industrial flue gas emission in China, this paper designed a new type of cyclone-tube demister to overcome the low removal efficiency of fine droplets that particle size less than 20 μm by wave-plate demister. The flow of flue gas in the cyclone tube demister was numerically simulated by using Euler-Lagrangian method, using rigid spherical water drops instead of fog drops. And the RNG k-ε model and DPM model were used for the alternating coupling calculation of continuous phase and discrete phase. The performance changes of the cyclone-tube demister under different flow velocities were studied. Based on the simulation experiment of orthogonal design, the influence of the structural parameters of the cyclone-tube demister on the demisting performance was studied. The simulation results of basic structure cyclone-tube demister show that, under the flow rate of 3~7 m/s, the removal efficiency of droplets with diameter greater than 20 μm is more than 99%; the removal efficiency of droplets with a diameter of 10~20 μm is above 86.5%; the removal efficiency of droplets with a diameter of 2~10 μm is above 51.3%; when the pressure drop is 61.4~321.3 Pa, it can significantly improve the removal efficiency of fine droplets. By analyzing the results of orthogonal simulation test, it is found that the increase of a and the decrease of d are beneficial to improve the removal efficiency of droplets. With the increase of a, d and H, the pressure drop of flue gas flowing through the demister will be increased. The optimum structure with demister efficiency of 2~10 μm as index is d=100 mm, H=2 000 mm, a=900°, the optimum structure with demister efficiency of 10~20 μm as index is d=100 mm, H=1 600 mm, a=900°, the optimum structure with the pressure drop as index d=100 mm, H=2 400 mm, a=540° are obtained. The cyclone-tube demister proposed in this study can significantly improve the removal efficiency of fine droplets, which is of great significance to the ultra clean emissions of coal-fired power plants.

Research Progress of Online Carbon Emission Monitoring Technology for Thermal Power Enterprises



YAO Shunchun, ZHI Jiaqi, FU Jinbei, et al

2023, 51(6):  97-108.  doi:10.12141/j.issn.1000-565X.220731

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In 2021, China’s national carbon market was officially opened, and the power generation industry was first included in the national unified carbon emission trading market. In this context, accurate, objective, real-time and credible carbon emission data is an important basis for the efficient operation of the carbon trading market. Carbon accounting method and online monitoring method are two commonly used carbon emission measurement methods in the world. This paper firstly reviewed the advantages and disadvantages of the two methods. The accounting method is a common method in China, and it has the advantages of wide application scope and unified accounting standards. However, there are some problems, such as complex processing process, poor timeliness, and sampling process vulnerable to human factors. On-line monitoring method has been widely concerned because of its advantages of good timeliness, high degree of automation and data not affected by human factors. However, there are still many problems in the application of online monitoring method in China. Firstly, there is no corresponding support system; secondly, the data quality of the online monitoring method cannot be guaranteed, and the comparability with the accounting method is also controversial. The biggest factors affecting the data quality are CO₂ concentration monitoring technology and flue gas flow monitoring technology; thirdly, the accuracy of flue gas flow monitoring remains to be studied. Then, the data quality improvement and evaluation method of on-line monitoring method were analyzed and summarized. It is considered that the detection accuracy of CO₂ concentration in power plant can reach a good level, while the accuracy of flue gas flow monitoring has not yet reached a unified conclusion. Its monitoring technology and measuring point layout will affect its field application. It is imperative to develop a flue flowmeter with independent intellectual property rights, wide application range and high precision for China’s accurate carbon verification cause. The quality evaluation of online monitoring data can be quantified by uncertainty. Finally, the following suggestions were put forward: first, to set up different carbon emissions online monitoring pilot and select different types and capacity of the unit for the studies. According to the specific conditions of the site, different flowmeters should be installed for comparative analysis to explore more suitable flowmeter types and site measurement point layout. Second, to establish an uncertainty analysis model for online monitoring of carbon emissions, to quantitatively analyze the factors that introduce greater uncertainty, and to improve the data evaluation system. Third, to construct a comprehensive comparison system of carbon emission online monitoring data and verification data. If the online monitoring method and the accounting method coexist in the carbon market, it is necessary to ensure the consistency of different data and the fairness of the carbon market. Fourth, to establish a supporting mechanism for a continuous online monitoring system for carbon emissions as soon as possible, and to establish corresponding national standards to ensure that the report data is based on evidence.

Experimental Study on Heat Transfer Performance of Separated Heat Pipe Heat Exchanger in Communication Base Station



GAN Yunhua, LIAO Yuepeng, YUAN Hui, et al

2023, 51(6):  109-118.  doi:10.12141/j.issn.1000-565X.220499

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Communication base stations are facing the problems of uneven heat dissipation and high energy consumption of the heat dissipation systems. The separated heat pipe heat exchanger can replace air-conditioning in communication base stations and effectively reduce the energy consumption of base station heat dissipation systems. The heat transfer performance of separated heat pipe heat exchanger is affected by factors such as filling ratio, working fluid type and air volume. In order to study the influence of different factors on heat transfer performance, the difference between theoretical filling ratio and the actual filling ratio was analyzed through theoretical calculation. The experimental platform was built to study the heat transfer performance of heat exchanger under different filling ratios, the difference of heat exchanger performance under different high and medium temperature working fluids, and the influence of indoor and outdoor fan power change on heat exchanger performance. The study finds that when the working fluid R134a is used, the error between the theoretical value and the actual value of the minimum filling ratio is 4.74%, the optimal filling ratio range of the heat exchanger is 27.1%~47.9%, the optimal filling ratio is 31.6%, and the equivalent heat transfer coefficient of the heat exchanger under the optimal filling ratio is 909 W/℃. With the increase of filling ratio, the phase change area inside the heat exchanger increases first and then decreases, and the heat transfer form changes from sensible heat transfer of vapor working fluid to latent heat transfer of the phase change of the working fluid, and then to sensible heat transfer of the liquid working fluid. The high temperature working fluid is not suitable for the separated heat pipe heat exchanger. When using the high temperature working fluid, there is no obvious phase change area inside the heat exchanger. The lower the boiling point of the working fluid is used, the larger the phase change area, the better the performance of heat exchanger, and the larger the range of its optimal filling ratio. With the increase of power of indoor and outdoor fans, the performance of the heat exchanger increases rapidly and then slows down. However, due to the poor heat dissipation conditions on evaporator side, the improvement of the heat transfer performance of the system by increasing the power of internal fan is more significant than that of the external fan.

Numerical Simulation of Thermal Ratcheting of Triple Eccentric Butterfly Valve



LI Shuxun, ZHANG Jianzheng, YIN Huiquan, et al

2023, 51(6):  119-128.  doi:10.12141/j.issn.1000-565X.220349

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In order to study the effect of thermal ratcheting on the thermal deformation and sealing performance of the triple eccentric metal hard seal butterfly valve, this paper firstly excluded the possibility of plastic collapse failure of the butterfly valve and fatigue failure of the sealing structure under several alternating cyclic loads at room temperature and high temperature. ANSYS Workbench finite element analysis software was adopted to study the thermal ratcheting effect of the triple eccentric metal hard seated under alternating cyclic loading at room and elevated temperature, and ten times of temperature cyclic loading analysis were performed on the butterfly valve based on Chaboche nonlinear kinematic hardening model. The results show that the maximum temperature difference between the inner ring surface of the valve seat and the outer wall of the valve body is about 60 ℃ under high temperature conditions. After the temperature is reduced to room temperature, the maximum plastic strain of the valve seat increases with the increase of cycle times. The maximum plastic strain of the valve seat after 10 temperature cycles is 0.021 16, and the thermal ratcheting effect occurs under the action of temperature cyclic load. After the fifth temperature alternating cycle, the maximum radial deformation of the valve seat and the sealing ring is 0.284 4 mm and 0.275 3 mm respectively. The maximum radial deformation of the valve seat is greater than that of the sealing ring. The residual deformation of the valve seat leads to the gap of the sealing surface, which proves that the sealing failure of the triple eccentric butterfly valve is caused by the thermal ratchet effect of the valve seat. After applying good thermal insulation on the exterior wall of the valve body, the ratcheting effect of the valve seat does not occur according to finite element calculation, indicating that good thermal insulation on the valve body is an effective means to avoid sealing failure caused by ratcheting effect of the valve seat. The research results reveal the reasons for the sealing failure of the butterfly valve under several alternating cyclic loads at room temperature and high temperature, and this paper puts forward corresponding preventive measures, which is of great guiding significance for other types of valves and pressure pipelines under the same working conditions to avoid thermal ratcheting effect.

Materials Science & Technology

Study on the Compatibility Between Surface Modifiers of TiO₂ Nanoparticles and Orginic Solvents



XIE Pingbo, SHI Ruixue

2023, 51(6):  129-135.  doi:10.12141/j.issn.1000-565X.220654

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Synthesis of high refractive index nanocomposite by solution blending method can control the particle size distribution and surface properties of nanoparticles, and improve the dispersion of nanoparticles in organic matrices. TiO₂ nanoparticles are widely used in areas such as optical devices, sensors and photocatalysis because of their excellent photoelectric performance. The homogeneous dispersion of TiO₂ nanoparticles in the organic solvent is an important prerequisite for preparing high refractive index nanocomposites by solution blending method. In this paper, three kinds of silane coupling agents (SCAs) with different carbon functionalities were used to modify the surface of TiO₂ nanoparticles, which can be dispersed in three organic solvents with different polarities to obtain a transparent and stable dispersion. Results indicate that the median particle size (D₅₀) of TiO₂ nanoparticles in heptane, butyl acetate and 1-butanol are 13.5, 19.6 and 22.1 nm, respectively, and the distribution coefficients (PDI) are 0.038, 0.231 and 0.171, respectively. Dynamic laser scattering (DLS) measurements and transmission electron microscopical (TEM) observation indicate that the TiO₂ nanoparticles are dispersed on a primary particle size level. Turbiscan stability analyzer analysis demonstrates that TiO₂ dispersions with the same mass fraction of TiO₂ nanoparticles have different dispersion stability, indicating that the best compatibility is hexadecyltrimethoxysilane and heptane, and the dispersion has high dispersibility and good stability, followed by 3-(methacryloyloxy)propyltrimethylsilane with butyl acetate. This study indicates that the properties of the carbon functionalities of the SCAs are vital to the dispersion state of TiO₂ nanoparticles in organic solvents, and provides a new idea for the preparation of dispersion with high dispersibility and stability.

Research on Composition Optimization and Performance of Composite Modified Asphalt Sealant



XIA Huiyun, YANG Haotian, LU Changjie, et al

2023, 51(6):  136-145.  doi:10.12141/j.issn.1000-565X.220540

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Modified asphalt sealant has excellent repair effect and low production cost, and has been widely used in crack repair, but there are still problems such as insufficient adhesion, low flexibility and low durability. Thermoplastic vulcanized silicone (TPSiV) has the advantages of silicone rubber such as stable structure, good weather resistance, high strength and high elasticity of thermoplastic polyurethane, showing excellent adhesion, durability, flexibility and high and low-temperature stability. In this study, 90# matrix asphalt was used as the main raw material. Firstly, furfural extraction oil (FEO) was used to pre-swelling TPSiV, and then high-speed shear method was used to prepare a series of high efficiency composite modified asphalt sealant by adding styrene-butadiene-styrene (SBS), waste rubber powder (CR), CaCO₃ and other modifiers. The effects of SBS, TPSiV, CR content and CR particle size on the properties of modified asphalt sealant were systematically studied. Finally, the formula was verified through the indicators of the whole set of sealant. The thermal storage stability of the sealant was characterized by softening point difference method. The microstructure of TPSiV and TPSiV modified asphalt was observed by fluorescence microscope and scanning electron microscope. The IR spectra of asphalt before and after modification were characterized by Fourier infrared spectroscopy (FTIR).The results show that the increase of SBS content significantly improves its high temperature performance, and the best dosage is 3%. TPSiV improves the flexibility and cohesiveness of sealant, and the best dosage is 3%. With the decrease of CR particle size, the high-temperature performance is improved, while the low-temperature performance is decreased. The optimal particle size is 40 mesh. With the increase of CR content, the high-temperature performance of modified asphalt is improved, and the best dosage is 22%. The best sealant formula SBS∶TPSiV∶CR∶CaCO₃∶FEO mass ratio is 5∶3∶22∶5∶3, which meets the requirements of storage stability. TPSiV has a rough surface structure and the surface attached with silicone rubber particles is conducive to its adhesion to asphalt, and TPSiV disperses evenly in the composite modified asphalt. Chemical modification and physical modification of TPSiV compound modified asphalt exist simultaneously.

Preparation and Analysis of Laser Cladding Hard Coating on TC4 Surface



ZHENG Lijuan, HU Zitao, LIU Shaofeng, et al

2023, 51(6):  146-152.  doi:10.12141/j.issn.1000-565X.220605

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In order to solve the shortcomings of low hardness and poor wear resistance of TC4 titanium alloy, this study prepared titanium-based hard coatings reinforced by HfC, TaC and ZrC ternary ceramic phases (0%, 5%, 10%, 15%, respectively ) on TC4 surface by 4 kW high-power Laser4000 semiconductor laser with laser cladding technology. After the cladding, the cladding parts were cut, polished and corroded to prepare metallographic samples. The macroscopic morphology, microstructure and properties of the cladding coatings with different material components were compared and analyzed by EM electron microscope, SEM scanning electron microscope, EDS energy spectrometer and XRD diffractometer. The macro hardness value of the cladding layer was measured by TH120 A Leeb hardness tester, and the micro hardness change rule of the cladding sample section was analyzed by Qness type Vickers microhardness tester. The results show that the addition of ternary ceramic phase makes the cladding layer and the substrate form a good metallurgical bonding, and the substrate and the cladding layer have a clear smooth boundary. The cladding layer is mainly composed of α+β acicular martensite matrix and precipitated rod-like and block-like α phases. The cladding layer of the ternary ceramic reinforcement phase with a mass fraction of 15% is composed of block-like crystals, and the grains are the most coarse. For the coating of the ternary ceramic reinforcement phase with a mass fraction of 5% and 10%, the size of the rod-like and block-like α phases is significantly reduced, the grains are obviously refined, and the structure is more uniform and dense. The main components of the columnar and massive α phases in the cladding layer are Ti and trace Al, Zr, Hf and V elements. The acicular martensite of the coating contains high Al, Zr, Ta and V elements, and the black β phase between the crystals contains trace Zr and Ta elements. It is found that Hf and Ta elements usually exist in different phases. The hardness of the specimens is improved after laser cladding. When the mass fraction of the ternary ceramic addition is 10%, the grain of the cladding layer is the smallest, the distribution is uniform, and the hardness is the highest, reaching 715 HV, which is 2.31 times that of TC4 substrate.