Table of Content

25 July 2024, Volume 52 Issue 7

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2024, 52(7):  0. 

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Electronics, Communication & Automation Technology

Modeling of Source/Drain Access Region Resistance in GaN HEMT Considering Self-Heating and Quasi-Saturation Effect



YAO Ruohe, YAO Yongkang, GENG Kuiwei

2024, 52(7):  1-8.  doi:10.12141/j.issn.1000-565X.230405

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The region between gate and source/drain is called source/drain access region resistances (R_D,S) in GaN HEMT equivalent circuit model. Accurately constructing the source/drain access region resistance (R_D,S) model is of great significance for analyzing the DC and RF characteristics and building a comprehensive large-signal model for GaN HEMTs. This paper presented an R_D,S model considering self-heating and quasi-saturation effects. Firstly, the nonlinear self-heating effect model was derived based on the relationship between the temperature of the source/drain access region (T_CH) and the dissipated power (P_diss). Furthermore, based on the quasi-saturation effect and Trofimenkoff model, a nonlinear R_D,S model was constructed. Under low bias conditions, the decrease of 2DEG and mobility with increasing T_CH results in the increase of R_D,S with T_CH at ambient temperatures (T_amb) ranging from 300 to 500 K. At constant T_amb, R_D,S presented a nonlinear increasing trend with the increase of bias. The results show that the average relative errors of the R_D models in this paper and in the literature are 0.32% and 1.78% respectively, and the root mean square errors (RMSE) are 0.039 and 0.20 Ω respectively. The mean relative errors of R_S model are 0.76% and 1.73% respectively, and RMSE are 0.023 and 0.047 Ω respectively. Compared with the experimental data reported in the literature, the results show that the average relative errors of the RD model in this paper and that in the literature are 0.91% and 1.59% respectively, and the RMSE are 0.012 and 0.015 Ω respectively. The mean relative errors of RS are 1.22% and 2.77% respectively, and RMSE were 0.001 5 and 0.003 4 Ω respectively. The proposed model with lower mean relative error and root mean square error, is able to more accurately characterize the variation of R_D,S with the drain-source current (I_DS) in the linear operating region of GaN HEMTs. This model can be used for the design optimization of the device or as a Spice model for circuit simulation.

Epilepsy Electroencephalogram Signal Classification Method Based on Multi-Band Path Signature Features



GUO Lihua, YANG Hui, WU Qianyi, et al

2024, 52(7):  9-18.  doi:10.12141/j.issn.1000-565X.230586

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Automatic detection of epilepsy based on electroencephalogram (EEG) signals is greatly helpful for clinical diagnosis and treatment of epilepsy. Most epilepsy detection algorithms ignore the temporal relation of EEG signals, therefore, this paper proposed an epilepsy EEG signal classification method based on multi-band path signature features. Firstly, EEG signals were decomposed into five frequency bands. Secondly, features were extracted using the path signature (PS) algorithm. Thirdly, features were fused after local principal component analysis (LPCA) removed the feature’s correlation. Finally, an ensemble classifier was used to predict epilepsy. Since the path signature can dig into the correlation of EEG signals, combined with local principal component analysis, the method proposed in the paper can obtain more discriminative epilepsy classification features.The comparative experiments of 10-fold cross-validation were conducted to validate this method on two datasets, i.e., the private dataset from a local hospital with more than 2 000 seconds of segments and the CHB-MIT epilepsy dataset. The results show that the average classification accuracy of the method reached 97.25% on the private dataset, which is higher than those of the classical EMD (Empirical Mode Decomposition) method and the up-to-date LSTM (Long Short-term Memory Network) + CNN (Convolutional Neural Network) method by 3.44 and 1.35 percentage points respectively. Moreover, the proposed method can achieve an average classification accuracy of 98.11% on the CHB-MIT dataset, which is higher than those of the classical EMD method and the up-to-date LSTM+CNN method by 5.20 and 2.64 percentage points respectively, and this method achieves the best classification accuracy than other methods on both datasets.

Parametric Human Body Mesh Reconstruction Based on Global Consistency Network



BAO Wenxia, TIAN Ruzhen, WANG Nian, et al

2024, 52(7):  19-28.  doi:10.12141/j.issn.1000-565X.230608

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Human body mesh reconstruction (HMR) has wide applications in human-computer interaction, virtual/augmented reality, and other fields. In order to further improve the accuracy of human body pose and shape estimation in image-based human body mesh reconstruction, this study proposed a parametric human body mesh reconstruction network based on hybrid inverse kinematics and global consistency deep convolutional neural network, called GloCoNet. To enhance the network’s global consistency and long-range dependencies, a Global Consistency Booster (GCB) module was designed on top of the feature extraction network. It can enhance the model’s perception and expression capabilities of global information, and allow the model to adaptively adjust the feature map weights of different channels and spatial positions. Furthermore, a multi-head attention mechanism was introduced to capture the model’s long-range dependencies globally, helping the model better capture key relationships and patterns when dealing with long-term dependencies, and modeling global contextual information to enrich the diversity of feature subspaces. Meanwhile, the network adopts a hybrid inverse kinematics approach to bridge the gap between human body mesh estimation and 3D human joint estimation, ultimately improving the accuracy of human 3D pose and shape estimation. Experimental results show that the GloCoNet model significantly outperforms previous mainstream methods with an average per joint position error of 51.3 mm on the publicly available Human3.6M dataset.

A TT-Tucker Decomposition-Based LC Convolutional Neural Network Compression Method Without Pre-Training



LIU Weirong, ZHANG Zhiqiang, ZHANG Ning, MENG Jiahao, ZHANG Min, LIU Jie

2024, 52(7):  29-38.  doi:10.12141/j.issn.1000-565X.230617

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Tensor training (TT) decomposition and Tucker decomposition are two effective compression methods for convolutional neural networks. However, TT and Tucker decomposition face the problems of spatial structure information loss and high computational complexity respectively. To solve the above problems, this paper considered the information retention rate and resource occupancy of the network structure and proposed a LC convolutional neural network compressed method (TT-LC) without pre-training based on TT-Tucker decomposition, adopting the learning-compression (LC) algorithm constraint compression framework. The TT-LC method includes two parts: learning step and compression step. The learning step didn’t not need the pre-training process, and adopted the exponential cyclic learning rate method to improve the training accuracy. In the compression step, this paper selected the global optimal rank according to the advantages of TT and Tucker decomposition and the characteristics of Bayes rule, and used empirically variable Bayesian matrix factorization (EVBMF) and Bayesian optimization (BayesOpt) to select reasonable ranks to guide tensor decomposition. The TT-LC method was used to compress the trained model. TT-LC method not only reduces the loss rate of spatial structure information and computational complexity, but also solves the problem that the unreasonable rank selection of the tensor leads to the significant decrease in model accuracy. It can realize the double Bayesian rank selection and double compression of the model, and obtains the optimal compression model. Finally, experiments were carried out on CIFAR10 and CIFAR100 datasets using ResNets and VGG networks. The results show that for ResNet32 network, compared with the benchmark method, the proposed method achieved a compression rate of parameter quantity of 69.6% and a floating point computation compression rate of 66.7% with the accuracy of 92.22%.

Probability Density Function Shape Control Method for Nonlinear Stochastic Systems Based on Compactly Supported Multi-Variable Polynomials



WANG Lingzhi, ZHANG Kun, QIAN Fucai

2024, 52(7):  39-52.  doi:10.12141/j.issn.1000-565X.230610

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For the probability density function (PDF) shape control problem of nonlinear stochastic systems, this paper used the Fokker-Planck-Kolmogorov (FPK) equation as a tool and proposed a PDF shape control method based on the compactly supported multivariable polynomials (CSMP) function. When the system is in a steady state, the PDF of the system was trapped in a specific compact subspace and didn’t need to be integrated over the whole space. The CSMP function is non-zero in a continuous space, satisfying the compact subspace characteristic. Therefore, the linear combination of CSMP (CSMP-LC) was utilized as the steady-state approximate solution of FPK equation for approaching the target PDF. Firstly, the moth-flame optimization (MFO) algorithm was used for optimizing parameters of the CSMP-LC function. Then, by integrating each dimensional state variable of the multidimensional steady-state FPK equation, the integration of the steady-state FPK equation over the whole space was ensured to be zero. Finally, the solution of the one-dimensional and two-dimensional uncoupled state variable PDF shape controller was completed, and simulation experiments were conducted. The results demonstrate that the proposed method can achieve PDF shape control for different types of target PDFs (single-peaked shapes, double-peaked shapes and triple-peaked shapes) for one-dimensional nonlinear stochastic systems. In particular, for complex triple-peaked shapes, it has a significant advantage over the multi-Gaussian closure method and the exponential polynomial method. The method in the paper was extended to the nonlinear stochastic system with uncoupled two-dimensional state variables, which can better realize the control of PDF shape and provide a new research idea for the study of PDF shape control of multivariate stochastic systems. Moreover, the CSMP function can reduce the complexity of the integral computation and reduce the difficulty of solving PDF shape controllers for nonlinear stochastic systems.

Research on Autonomous Grasping of a Humanoid Robot Based on Vision



ZHANG Xuchong, YANG Jun

2024, 52(7):  53-61.  doi:10.12141/j.issn.1000-565X.230528

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With the development of robotics technology, humanoid robots have shown application potential and value in multiple fields. Research on autonomous grasping of humanoid robots based on machine vision aims to improve their grasping adaptability and humanoid actions in natural environments. In terms of machine vision, the Realsense-D435 depth camera was adopted, and the YOLO (You Only Look Once) object detection model was used to achieve target object recognition, spatial positioning, depth map cropping, and target point cloud generation. The object’s posture was obtained based on the registration algorithm (ICP) between the target point cloud and the standard point cloud. The robot head was modeled using the D-H method, and the position and posture of the object were converted from the camera coordinate system to the robot coordinate system. In terms of motion planning, according to the grasping law of the human arm, the grasping process was divided into 9 basic actions: initial position, moving to the pre-grasping position, grasping the object, lifting the object, moving the object, moving to placement position placing the object, retreating position, and returning to the initial position. Corresponding grasping postures were determined for different objects to improve the success rate of grasping. Based on the grasping and placing points obtained visually, the remaining key points were calculated independently, and the spatial arc was used as the grasping trajectory. Through Matlab simulation, the rationality of the end movement trajectory and joint trajectory of the robotic arm during the grasping process was verified. Finally, an object grasping experiment was conducted, and the results showed that the humanoid robot can quickly and accurately recognize and locate different objects in the natural environment, and can successfully grasp and transport them with a success rate of over 80%. And it takes into account the imitation of human nature of the action, verifying the effectiveness of the proposed solution. This study can promote the application and popularization of humanoid robots in human daily life.

Attention Module Based on Feature Similarity and Feature Normalization



DU Qiliang, WANG Yimin, TIAN Lianfang

2024, 52(7):  62-71.  doi:10.12141/j.issn.1000-565X.230313

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In recent years, attention mechanisms have achieved great success in the fields of image classification, object detection and semantic segmentation. However, most existing attention mechanisms can only achieve feature fusion in channel or spatial dimensions, which greatly limits the flexibility of attention mechanisms to change in channel and spatial dimensions and cannot fully utilize feature information. To address this issue, this paper proposes a convolutional neural network attention module based on feature similarity and feature normalization (FSNAM), which can utilize the characteristic information of both channel domain and spatial domain. FSNAM consists of a feature similarity module (FSM) and a feature normalization module (FNM). FSM generates a two-dimension feature similarity weight map using the channel feature information and local spatial feature information of the input feature map, while FNM generates a three-dimension feature normalization weight map using the global spatial feature information of the input feature map. The weight maps generated by FSM and FNM are fused to generate a three-dimension attention weight map to achieve the fusion of channel feature information and spatial feature information. Moreover, to demonstrate the feasibility and effectiveness of FSNAM, ablation experiments are conducted. The results show that, for image classification tasks, FSNAM significantly outperforms other mainstream attention modules in improving the performance of the classification network on CIFAR dataset; for object detection tasks, the object detection network using FSNAM improves the detection accuracy of small and medium-sized objects in VOC dataset by 3.9 and 1.2 points of percentage, respectively; and, for semantic segmentation tasks, FSNAM can significantly improve the performance of HRNet model, and helps to achieve an average pixel accuracy increase of the model on SBD dataset of 0.58 points of percentage.

Chemistry & Chemical Engineering

Construction of a Limit Model for Isothiazolinones Migration from Children Sports Protection Articles to Sweat



MA Tongmei, ZHU Zhenhai, LI Qiong, HUANG Lina, HUO Weiqiang, FANG Han, LIU Zuoqi

2024, 52(7):  72-80.  doi:10.12141/j.issn.1000-565X.230271

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The physiological characteristics and behavioral patterns of infants are somewhat different from those of adults, resulting in a much higher frequency and amount of exposure to harmful chemicals than those of adults when using the same type of products. Therefore, national regulations and standards have set safety limits for harmful chemicals to protect the most vulnerable and sensitive infants. Isothiazolinone, as the common additive to improve antibacterial performance of children products, is a potential sensitizing compound that can induce allergic dermatitis. So far there is no chemical safety limit setting for it in China, while in the international existing regulations and standards, this chemical is only restricted with the total content limit. To this end, this study examined the chemical safety assessment method of infants, summarized the existing chemical safety limit model, and defined the key steps of constructing the limit model. First, dose-response data of the chemical was determined; then the dimension of the chemical limit was confirmed; after that, with the dimensional analysis method, the parameters based on product characteristics and human behavior patterns were introduced to establish the connection between the dose-response data and the chemical migration limit. On this basis, by introducing parameters of no expected sensitization inducing level, sensitization assessment factors, sweat rate and sports time, it proposed the limit model for isothiazolinones migration from children sports protection articles to sweat. Finally, the appropriate parameter values were selected based on the infant and product characteristics, and the model was applied to calculate the migration limits of the three isothiazolinones (MI, CMI and BIT) at 0.150, 0.014 and 0.150 mg/L, respectively. These migration limits are anticipated to be incorporated in the upcoming Chinese national standard Juvenile Products: General Requirements for Daily Sports Protection Articles scheduled for release by the end of 2023, which can be employed to protect of children’s skin from isothiazolinones.

Process Research on Supercritical CO₂ Fluid Extraction of Natural Nicotine from Tobacco



ZHANG Huiping, TANG Qianru, YAN Ying

2024, 52(7):  81-87.  doi:10.12141/j.issn.1000-565X.230661

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Extracting nicotine from tobacco can achieve the resource utilization of waste tobacco. Therefore, this article conducted a single-factor experiment to investigate the effects of process conditions (extraction time, extraction pressure, extraction temperature, CO₂ flow rate, particle size of raw materials) on the yields of nicotine and tobacco extract. In addition, using nicotine extraction rate as the indicator, extraction time, extraction pressure, extraction temperature, and CO₂ flow rate as factors, an orthogonal experiment was designed to optimize the extraction process. The composition of the obtained tobacco extract was analyzed with gas chromatography-mass spectrometry. The results show that extraction temperature has the greatest impact on nicotine extraction rate, extraction time and pressure have a relatively large impact, and CO₂ flow rate has the least impact. The optimal extraction conditions are as follows: extraction temperature is 65 ℃, extraction pressure is 22 MPa, CO₂ flow rate is 25 L/h (based on 150.0 g of tobacco raw material), extraction time is 80 minutes, and particle size is 0.60 mm. Under the optimal conditions, the nicotine extraction rate was 97.89%, and the tobacco extract yield was 5.57%. Fourteen components were detected in the volatiles of the tobacco extract, and the main components were nicotine (52.22%), neophytadiene (10.29%), and vitamin E (6.67%). Additionally, the extract also contained phytosterols, linoleic acid, and liquidambar resin, etc. Due to high nicotine content, the extract can be used as a good raw material for nicotine purification in later stages.

Architecture & Civil Engineering

Discontinuous Breaks Identification and Space Vibrancy Deduction of Recreational Path Network in Urban Area



ZHAO Miaoxi, LIANG Xiyan, ZHANG Xiaoxing, SHI Haochen

2024, 52(7):  88-96.  doi:10.12141/j.issn.1000-565X.230581

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Improving the vitality of self-organized recreational path network is an important goal of urban renewal planning. Due to the discontinuity and the existence of dead end roads in the recreational path network in old towns, the comfort of residents’ recreational activities is restricted. The self-organization of recreational path network means that the top-down planning and design mode is difficult to match the needs of citizens. How to deduce the spatial vitality of recreation planning in a bottom-up mode and then identify potential land plots is an important issue to improve the quality of urban recreational path network. By taking the old town in Guangzhou as an example, this paper constructs the indicators of break degree and spatial vibrancy based on the complex network theory. Then, by using GPS trajectory data to identify the breaks in the existing recreational path network, the identification of discontinuous breaks based on citizen recreation behavior and the activation effect of urban renewal projects are quantitatively discussed, and the potential impacts brought by the implementation of renewal projects are simulated. The discontinuity analysis shows that the break degree of the recreational path network in the old town in Guangzhou is generally low, and the connection degree is good, but there are still some obvious breaks due to the street location and historical problems. Moreover, the results of spatial vibrancy deduction show that urban renewal projects have a positive impact on the self-organized recreational path network, and that the implementation plan and schedule of urban recreation quality improvement projects can be determined according to the deduction analysis results. This study makes a beneficial exploration of urban self-organizing characteristics from the perspectives of planning and transportation, and makes up for the deficiency of top-down planning in considering urban self-organized recreational path network.

Alignment Analysis of Railway Steel Truss Arch Bridge Based on Point Cloud Slicing Algorithm



PENG Yipu, LI Jian, HAN Yanqun, TANG Zhiyuan, LI Zichao, YU Fengxiao, CHEN Li, ZOU Kui

2024, 52(7):  97-106.  doi:10.12141/j.issn.1000-565X.230478

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The alignment measurement of railway bridge plays an important role in bridge health detection and the safe operation of railway. In order to improve the efficiency of alignment measurement of steel truss arch bridge in operation railway, this study constructed a complete “pure” bridge point cloud model. It took a three-span steel truss arch bridge as an example and used the terrestrial laser scanning (TLS) technology to scan the bridge members as a whole. From the three aspects of bridge alignment measurement accuracy, scanning integrity and point cloud number, the optimal number of bridge scanning stations was determined as 10. The 3DNDT point cloud registration algorithm was used to register each station one by one. The accuracy of bridge point cloud registration is 2 mm. The bridge point cloud was projected onto the xoy plane and the noise points were removed by the radius filter. The point cloud equidistant slicing and point cloud plane slicing algorithm were proposed to extract the bridge alignment, and the alignment point cloud data was exported to Auto CAD to pick up the coordinates. The point cloud slicing method was used to extract the TLS measurement value, and the total station method measurement result was compared with the original bridge alignment. In the analysis of the bridge deck alignment, the two methods measured the maximum deformation at the mid-span A₅ point as 12.69 mm and 10.29 mm. The maximum mutual difference R of the two methods is 2.4 mm, and the correlation coefficient is better than 99.93%. In the analysis of arch axis alignment, the maximum deformation of point cloud slicing method and total station method is 6.2 mm and 3.9 mm at B₄ point in the upper chord span of main truss, and 5.9 mm and 3.5 mm at B₁₀ point in the lower chord span of main truss. The maximum mutual difference R of the two methods is 3.2 mm, and the correlation coefficient is better than 99.87%, which verifies the effectiveness of point cloud slicing algorithm and the high precision of TLS measurement. There is no obvious lateral displacement in the transverse alignment of the arch axis. The verticality of the 19 suspenders obtained by the point cloud equidistant slicing remains good, and no torsion and offset occurs. The research results provide a reference for the alignment analysis and point cloud processing methods of the operating railway steel truss arch bridge, and have important practical value.

Stability Analysis of Shallow Buried Tunnel Under Nonlinear Failure Criterion



FU Helin, CHANG Xiaobing, HU Kaixun

2024, 52(7):  107-118.  doi:10.12141/j.issn.1000-565X.230370

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The pressure value of tunnel surrounding rock is an essential parameter for shallow buried tunnel design and calculation. In order to further improve the credibility of the surrounding rock pressure calculation results, the paper proposed a circular slip surface failure model based on the traditional shallow buried tunnel collapse model. Based on the nonlinear Mohr-Coulomb failure criterion, the limit analysis upper bound method was applied to derive the formulae for calculating the pressure in shallow buried tunnel surrounding rocks under the action of seismic forces. The credibility of the calculation results was verified and the influencing factors were discussed. The high credibility and accuracy of the theoretical formula was proved through comparing the results with field engineering and existing results. It also finds that the pressure of the surrounding rock is more significantly influenced by the nonlinear coefficient and the initial cohesion; the larger the nonlinear coefficient and the smaller the initial cohesion, the greater the surrounding rock pressure. As the parameter to be defined K (ratio of horizontal surrounding rock pressure to vertical surrounding rock pressure ) decreases, the horizontal rock pressure decreases and the vertical rock pressure increases. The influence of seismic forces on the pressure of the surrounding rock cannot be ignored. The surrounding rock pressure is most affected by the vertical seismic force alone, followed by the horizontal and vertical seismic force working together, and least affected by the horizontal seismic force alone. As the horizontal and vertical seismic force coefficients increase, the surrounding rock pressure also increases. The results of the study are of high reference value for the study of most tunnels, especially shallow buried tunnels that are susceptible to seismic effects.

Seismic Performance of Hoop Head Tenon Timber Joint with Added Corner Dampers



CHEN Qingjun, LEI Jun, LI Bingzhou, ZUO Zhiliang, CAI Jian

2024, 52(7):  119-134.  doi:10.12141/j.issn.1000-565X.230658

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To provide theoretical basis for the restoration of Guangfu wooden structures, five hoop head tenon joint specimens were designed and manufactured using Merbau wood. Considering the influence of the size of mortise and tenon construction, quasi-static tests were carried out on undamaged and unreinforced joint specimens. Then, to preserve the original appearance of the building as much as possible, the damaged joint specimens mentioned above were reinforced by the Queti-type dampers that have minimal influence on the original appearance of the structure. Finally, quasi-static tests were conducted again on the reinforced joints to investigate the difference in their seismic performance and the strengthening effect of the dampers. The results show that the joint specimens reinforced with dampers exhibit significant indentations at the mortise and tenon connections when being loaded to failure. There is noticeable splitting on the outer side of the tenon of the beam and the detachment of the tenon, as well as obvious separation between the rubber and steel plate at the base of the damper. The addition of dampers to joints can compensate the decrease in force-bearing performance caused by initial damage, provide better post-damage stiffness for the damaged mortise and tenon joints, and enhance the ultimate load-bearing capacity and energy absorption capacity. After adding the damper, there occur enhancements in terms of post-damage stiffness, load-bearing capacity and energy absorption of specimens, as compared with the unreinforced joints, with the increment being more than 18%, 19% and 20%, respectively. Moreover, on the basis of the existing simplified mechanical model and in combination with OpenSees, a macro-modelling method was proposed for hoop head tenon timber structures, which helps to obtain hysteresis curves of the joints being in good agreement with the experimental results, meaning that the modelling method can effectively simulate the hysteresis energy dissipation characteristics of the hoop head tenon joints strengthened with dampers.

Pressure Loss of Pipeline Conveying Large-Size Pebbles in Slurry Discharge System of Slurry Shield



LI Xinggao, GUO Yidong, SUN Yu, LIU Hongzhi

2024, 52(7):  135-144.  doi:10.12141/j.issn.1000-565X.230559

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During slurry shield tunneling in the sandy pebble stratum, the slurry discharge pipeline will transport a large number of the large irregular pebbles, generating unstable turbulence, which causes difficulties to the determination of the pipeline pressure loss. This study designed a circulating flow test device, and the slurry used in the experiment is CMC transparent viscous slurry. And the study established a numerical model using the computational fluid dynamics-discrete element method (CFD-DEM) coupling approach. Taking pebbles with a particle size of 5~80 mm as the research object, the study investigated the effects of pebble particle size distribution, slurry velocity, pebble volume fraction, and pipeline inclination angle on the pressure loss along the pipeline, respectively. The results indicate that the pressure loss along the pipeline increases exponentially with the increase of slurry velocity under the same particle size distribution, pebble volume fraction, and pipeline inclination angle. And for horizontal pipelines, the effect of pebble particle size distribution on the pressure loss along the pipeline is not significant. In addition, for the low slurry velocity (v < 2 m/s), the pressure loss along the pipeline increases linearly with the increase of pebble volume fraction. And for the high slurry velocity (v ≥ 2.0 m/s), the pressure loss along the pipeline increases exponentially with the increase of pebble volume fraction. For inclined and vertical pipelines, the pressure loss along the pipeline firstly increases slowly with the increase of the pipeline inclination angle, and then increases sharply under the same particle size distribution, pebble volume fraction and slurry velocity, and the pipeline inclination angle at the turning point is 60°. In addition, under the action of mud buoyancy and turbulence, it is difficult for large-size pebbles to overcome their own gravity and reach a state of complete suspension. Therefore, large-size pebbles mainly move along the lower wall of the pipeline, and the pressure at the elbow of the pipeline is obviously stratified.

Influence Factors of Mechanical Properties of Geocell Retaining Wall Under Seismic Load



JIN Feifei, SONG Fei, SHI Lei, et al

2024, 52(7):  145-160.  doi:10.12141/j.issn.1000-565X.230412

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This paper established a numerical model of geotechnical flexible retaining wall supporting slope with FLAC^3D software, and the model was verified by the results of shaking table tests. With the calibrated numerical model, it systematically studied the influence of four factors on the dynamic response of slope, including strip stiffness, cell size, retaining wall thickness and filling elastic modulus. Additionally, it discussed the failure mechanism of the retaining wall and calculated the influence weights of each parameter. The results indicate that the stability of a retaining wall under earthquake action is closely related to these four factors. The distribution law of confining pressure and permanent horizontal displacement along elevation follows a two-stage pattern of “increase-attenuation”. Furthermore, settlement at the top of the slope presents a “V” shape distribution with smaller ends and larger middle portions. The horizontal peak acceleration exhibits a three-stage pattern of “increase-attenuation-increase” along elevation. With the increase of stiffness, the confining pressure of the cell increases, but the permanent horizontal displacement, slope roof settlement and horizontal peak acceleration decrease. With the increase of cell size, cell confining pressure, permanent horizontal displacement, slope top settlement and horizontal peak acceleration increase. With the increase of retaining wall thickness and filling elastic modulus, cell confining pressure, permanent horizontal displacement, slope top settlement and horizontal peak acceleration all decrease. Among the four influencing factors, the influence weight of cell size is the largest, and the influence weight on cell confining pressure is 0.996, while the influence weight of retaining wall thickness is the least. The retaining wall structure of geocele has good seismic performance under earthquake action, and the retaining wall structure has a certain attenuation effect on seismic energy, which can meet the requirements of seismic fortification. The research results provide guidance for the seismic design and engineering application of flexible retaining wall of geocell under earthquake action.