Variation Rules Research Articles

Analysis and Enlightenment on the Relationships between Two Kinds of Cutter Life Evaluation Indexes and Installation Radius: A Case Study

Accurate evaluation of cutter life at different cutter positions on the cutter head is helpful to determine the time of cutter change and reduce the time of cutter wear measurement, which is of great significance to improve the tunneling efficiency of tunnel boring machine (TBM) projects. Unfortunately, there is no unified cutter life evaluation index now. The field data of cutter wear are collected from a section of a long TBM tunneling water conveyance tunnel in China. Two kinds of cutter life evaluation indexes (based on the radial wear extent of cutter rings and replacement number of cutter rings) are selected and the variation rule between these two kinds of indexes with cutter installation radius is statistically analyzed. The results show that the regression relationships between the two kinds of cutter life evaluation indexes and installation radius mainly present linear functions and quadratic functions. Those regression relationships are affected by factors such as wear type, installation angle, cutter spacing, influence width, and allowable limit wear extent of cutter rings. Considering the calculation accuracy of the evaluation index, the actual working conditions of the disc cutter, and ignoring the influence of tunnel diameter, it is recommended to preferentially choose the radial wear extent of cutter rings per unit rolling distance as the evaluation index of cutter life. The research results can provide a reference for the selection of cutter life evaluation index, prediction of disc cutter life at different cutter positions, and establishment of cutter life prediction mode.

Ultra-slow-light and dynamically quantitative optical storage modulation via quasi-BICs.

We achieve dynamically tunable dual quasi-bound states in the continuum (quasi-BICs) by implementing them in a silicon-graphene multilayer composite structure and utilize the quasi-BIC modes to achieve ultra-large group delays (velocity of light slows down 105 times), showing 2-3 orders of magnitude higher than the group delays of previous electromagnetically induced transparency modes. The double-layer graphene holds great tuning capability and leads to the dramatically reduced group delay from 1929.82 to 1.58 ps with only 100 meV. In addition, the log-linear variation rule of group delay with Fermi level (Ef) in the range of 0-10 meV is analyzed in detail, and the double-logarithmic function relationship between the group delay and quality factor (Q-factor) is theoretically verified. Finally, the quantitative modulation of the optical storage is further realized in this basis. Our research provides ideas for the reform and upgrading of slow optical devices.

Dynamic Characteristics of Magnetorheological Mounted Metal Rubber Structures Under Multi-physics Coupling Conditions

To accurately predict the dynamic characteristics of MR mounting, the nonlinear electromagnetic coupling law between MR liquid and soft magnetic material and the solid-liquid interaction, the electromagnetic coupling and fluid-structure coupling mathematical models and numerical simulation models of MR mounting are established. Through the magnetorheological mounting test, the simulation results are compared with the experimental results, and the validity of the numerical simulation model is verified. On this basis, the distribution effect of electromagnetic coupling in a magnetic circuit is analyzed. According to the Bingham model, the variation rule of magnetorheological fluid damping force was deduced. The magnetic field simulation results are introduced into the fluid model and the fluid-solid model, and the fluid-solid coupling effect of the numerical model of magnetorheological mounting is calculated. The dynamic and static characteristics of magnetorheological mounting under different current excitation conditions are simulated. It provides the basis for designing and simulating multi-physical field simulation of MR mounting.

Analysis of lattice deformation originated from residual stress on performance of aluminum nitride-based bulk acoustic wave resonators

With the development of MEMS technology to the nanometer scale, the influence of different process conditions on the performance of nano-devices can be calculated through the microscopic changes of materials. During the manufacturing process, the large residual stress from the film stack significantly influences the performance of devices, thereby reducing the wafer yield. Herein, we apply density functional theory to MEMS processes to reveal the intrinsic mechanism of how residual stress affects the performance of aluminum nitride-based bulk acoustic wave (BAW) resonators on an 8-inch high-resistance silicon wafer. The variation rule of physical properties of piezoelectric material aluminum nitride with different residual stresses is calculated via first-principles calculations. Through theory formula derivation, the piezoelectric-coupling constant (Kt2) of the bulk acoustic wave resonator is positively correlated with tensile residual stress, and the resonant frequency (fp, fs) is negatively correlated with tensile residual stress. The measurement results show that the average shifts of Keff2 is 0.12 % within −137 MPa and 183 Mpa residual stress, which is an excellent match with the theory prediction.

Collision characteristics of coal particles in arc-shaped plug elbow for pneumatic conveying

Particle collisions are one of the main causes of elbow wear. In this study, an arc-shaped plug elbow was proposed. Combined with the pneumatic conveying experiment of coal particles and the computational fluid dynamics and discrete element method (CFD–DEM) simulation of Euler–Lagrangian bilateral coupling, the variation rules of particle distribution, elbow wear, particle velocity, and collision energy loss were analyzed, the weakening characteristics of the arc-shaped plug on particle collision and elbow wear were revealed, and the criterion of the optimal structure was deduced. The results show that the arc angle is the main factor influencing particle collision and elbow wear in arc-shaped plugs, which determines the reasonable range of the dimensionless height. The average particle velocity of the arc-shaped plug elbow decreased rapidly during the plug-filling stage and was much lower than that of an ordinary elbow during the stable conveying stage. The growth rate of the collision energy loss tends to stabilize after stable particle accumulation. This is an important criterion for the optimal structure, in which the arc angle satisfies the condition that the plug completely contains the radiation area of the wear center, and the dimensionless height satisfies the condition that stable particle accumulation is formed in the plug.

Modeling and health feature extraction method for lithium-ion batteries state of health estimation by distribution of relaxation times

Accurate state of health (SOH) estimation of lithium batteries (LIBs) depends on the accuracy of LIBs modeling and the correlation of extracted health features (HFs). Aiming at the problems of a priori assumptions for existing battery modeling and poor correlation of HFs, this paper proposes a SOH estimation method for LIBs based on distribution of relaxation times (DRT). Firstly, we deduce and establish the developed DRT-based impedance model from battery electrochemical impedance spectroscopy (EIS), and the model parameters are calculated by EIS split-frequency domain method based on the principle of parsimony. Then, we analyze the variation rules of the peak and valley information in the distribution function of relaxation times curve with the capacity decay, and we extract multiple features strongly correlated with SOH as HFs. The extracted HFs are subjected to Weighted Principal Component Analysis (WPCA) to obtain indirect health features (IHFs), which achieve the estimation of SOH for LIBs. Finally, the effectiveness of the proposed modeling and health feature extraction method is validated by SOH estimation using the public dataset from Nature subseries. The results indicated that the EIS fitting accuracy R2 of the developed model is the best and the RMSE of SOH estimation is within 0.873 %.

Mechanism analysis of injection technique of water composition modification for enhanced oil recovery

ABSTRACT By adjusting the composition of injection water, including ionic type and strength, the goal of enhance oil recovery rate can be achieved. However, there is no clear understanding of which factor, ionic type or strength, has a greater impact. In this paper, based on the formation water of the offshore G oilfield, various brines with different ionic strengths and types were prepared. By measuring the zeta potential of rock powder and oil droplets, three-phase contact angle, interfacial tension between oil and water, emulsification properties of brines, and film strength of oil-water interface, the variation rules of the core wettability and emulsification performance of brine were systematically analyzed when the ionic strength and ionic type were changed. The experimental results showed that ionic strength has a greater impact than that of ionic type. For the oil-water-solid (rock) system of the G oilfield, an ionic strength of 82 mM/kg is the threshold for low salinity effect. Reducing ionic strength resulted in an increase in the hydrophilicity of rock and the ability of water flooding to emulsify oil droplets, which contribute to the improvement of oil displacement efficiency. Theoretically, water flooding to enhance oil recovery can be achieved by only reducing the ionic strength. This understanding was verified by dual polarization interferometry (DPI) experiments and low-field nuclear magnetic resonance experiments, which showed that reducing the salinity of the injection water from 42,000 mg/L (ionic strength of 820 mM/kg) to 4200 mg/L (ionic strength of 82 mM/kg) enhanced the oil recovery by 7.9%.

Wake mode identification of rotating triangle with machine learning approaches

The moving body usually leaves different forms of wake trails in fluids, and these wake fields contain physical information such as the state and geometry of the moving body. Recognizing and extracting these information from the wake can provide new insights for non-acoustic detection technology. Traditional methods do not easily extract the flow state, geometry, and other information directly from the wake structure. This work mainly uses convolutional neural network algorithms for intelligent recognition of the wake types of rotating triangles. Based on the flow field visualization technology of the soap film tunnel, the wake types of the flow around a structure controlled by external excitation of sinusoidal rotation are studied. The winding characteristics of the rotating triangle and the variation rule of the wake with control parameters are analyzed. At last, the recognition rate of the wake types on the test set is above 90%. The recognition rates of the experimental data not involved in the training conditions are all above 80%, demonstrating the generalizability of the model. This method provides a reference for further utilizing artificial intelligence in extracting physical information from wakes, playing a crucial role in advancing wake detection technology.

Calculating the number of radial cracks around a wellbore fractured by liquid CO2 phase transition blasting technology

Integrating liquid CO2 phase transition blasting (LCPTB) technology with hydraulic fracturing (HF) methods can help reduce wellbore damage, create multiple radial fractures, and establish a complex fracture network. This approach significantly increases the recovery efficiency of low-permeability oil and gas fields. Accurately calculating the number of fractures caused by LCPTB is necessary to predict production enhancement effects and optimize subsequent HF designs. However, few studies are reported on large-scale physical model experiments in terms of a method for calculating the number of fractures. This study analyzed the initiation and propagation of cracks under LCPTB, derived a calculation formula for crack propagation radius under stress waves, and then proposed a new, fast, and accurate method for calculating the number of fractures using the principle of mass conservation. Through ten rock-breaking tests using LCPTB, the study confirmed the effectiveness of the proposed calculation approach and elucidated the variation rule of explosion pressure, rock-breaking scenario, and the impact of varying parameters on number of fractures. The results show that the new calculation method is suitable for fracturing technologies with high pressure rates. Recommendations include enlarging the diameter of the fracturing tube and increasing the liquid CO2 mass in the tube to enhance fracture effectiveness. Moreover, the method can be applied to other fracturing technologies, such as explosive fracturing (EF) within HF formations, indicating its broader applicability and potential impact on optimizing unconventional resource extraction technologies.

Macro-micro correlation analysis of rheological characteristics for composite modified asphalt

Purpose This study aims to investigate the micro mechanism of macro rheological characteristics for composite modified asphalt.Grey relational analysis (GRA) was used to analyze the correlation between macro rheological indexes and micro infrared spectroscopy indexes. Design/methodology/approach First, a dynamic shear rheometer and a bending beam rheometer were used to obtain the evaluation indexes of high- and low-temperature rheological characteristics for asphalt (virgin, SBS/styrene butadiene rubber [SBR], SBS/rubber and SBR/rubber) respectively, and its variation rules were analyzed. Subsequently, the infrared spectroscopy test was used to obtain the micro rheological characteristics of asphalt, which were qualitatively and quantitatively analyzed, and its variation rules were analyzed. Finally, with the help of GRA, the macro-micro evaluation indexes were correlated, and the improvement efficiency of composite modifiers on asphalt was explored from rheological characteristics. Findings It was found that the deformation resistance and aging resistance of SBS/rubber composite modified asphalt are relatively good, and the modification effect of composite modifier and virgin asphalt is realized through physical combination, and the rheological characteristics change with the accumulation of functional groups. The correlation between macro rutting factor and micro functional group index is high, and the relationship between macro Burgers model parameters and micro functional group index is also close. Originality/value Results reveal the basic principle of inherent-improved synergistic effect for composite modifiers on asphalt and provide a theoretical basis for improving the composite modified asphalt.

Comparative Study of Joint Estimation of State of Charge (SOC) and State of Health (SOH) of Lithium-ion Batteries Based on Different Tree Models

The realization of accurate State of Health (SOH) and State of Charge (SOC) estimation is a prerequisite to ensure the safe use of energy storage batteries, which helps to further improve the energy utilization efficiency effectively. Data-driven methods are efficient, accurate, and do not rely on accurate battery models, which is a hot direction in battery state estimation research. However, the relationships between variables in the lithium-ion battery dataset are mostly nonlinear, which largely affects the prediction of the model. In addition, the model also has a series of defects, such as large computation, strong data dependence, and long consumption time. In this paper, a joint online estimation method of battery SOC-SOH based on tree modeling algorithm is proposed to solve the above problems. Based on NASA battery sample data, this study explores the changing law between SOC and discharge voltage and temperature under different State of Health (SOH). Subsequently, a combination of RFR, GBDT and XGBoost tree modeling algorithms are used for battery SOC-SOH estimation based on the above variation rules. The experimental results show that the R<sup>2</sup> scores of the XGBoost algorithm in predicting both SOC and SOH are more than 0.995, indicating its good adaptability and feasibility.

Effect of chord-cut defects on the collapse response of thick-walled pipelines

Corrosion defects can significantly reduce the ultimate bearing capacity of thick-walled pipelines in deep water. Uneven depth defects pose a serious threat to the integrity of pipeline structures. However, in the study of uneven depth defects, the influence of chord-cut defects is often overlooked. To study the impact of chord-cut corrosion defect on pipeline collapse response, a dynamic model is established. Two sets of full-scale pipeline experiments are conducted to verify the model. The validated model is used to obtain the pipeline collapse responses under different defect parameters, which include defect length, defect depth, defects’ location, and pipeline ovality. The changes in pipeline collapse pressure and collapse mode under different defect parameters are analyzed. The research shows the increase in defect length and the decrease in diameter-to-thickness ratio (D/t) will enhance the influence of defect angle θ on pipeline collapse configuration. And the change of collapse mode will lead to abnormal changes in collapse pressure. With the increase of internal defect length, the collapse mode variation rule is “∞” - “∩” - “P” - “U”. A collapse pressure empirical formula for pipeline with chord-cut corrosion defects is obtained. The empirical formula fits well with the numerical simulation results.

Experimental Investigation of the Impact of Blended Fibers on the Mechanical Properties and Microstructure of Aeolian Sand Concrete.

To investigate the effect of hybrid fibers on the compressive strength of aeolian sand concrete, compressive strength tests were conducted on aeolian sand concrete with single polypropylene fibers and aeolian sand concrete with mixed polypropylene fibers and calcium carbonate whisker, and their variation rules were studied. Using scanning electron microscopy and nuclear magnetic resonance, the microstructure and pore structure of specimens were analyzed, and a mathematical model of the relationship between compressive strength and pore structure was established with gray entropy analysis. The results show that the compressive strength of hybrid fiber aeolian sand concrete first increases and then decreases with an increase in whisker content. When the replacement rate of wind-accumulated sand is 80% and the fiber content is 0.1%, the optimal volume content of whisker is 0.4%, and the 28 d compressive strength of whisker is 24.8% higher than that of aeolian sand concrete. The average relative errors of compressive strength at 7 d and 28 d are 8.16% and 7.48%, respectively, using the GM (1,3) model. This study can provide effective theoretical support for the application of calcium carbonate whisker and polypropylene fibers in aeolian sand concrete.

Using Ensemble Learning for Remote Sensing Inversion of Water Quality Parameters in Poyang Lake

Inland bodies of water, such as lakes, play a crucial role in sustaining life and supporting ecosystems. However, with the rapid development of socio-economics, water resources are facing serious pollution problems, such as the eutrophication of water bodies and degradation of wetlands. Therefore, the monitoring, management, and protection of inland water resources are particularly important. In past research, empirical models and machine learning models have been widely used for the water quality assessment of inland lakes. Due to the complexity of the optical properties of inland lake water bodies, the performance of these models is often limited. To overcome the limitations of these models, this study uses in situ water quality data from 2017 to 2018 and multispectral (MS) remote sensing data from Sentinel-2 to construct experimental samples of Poyang Lake. Based on these experimental samples, we constructed a spatio-temporal ensemble model (STE) to evaluate four common water quality parameters: chlorophyll-a (Chl-a), total phosphorus (TP), total nitrogen (TN), and chemical oxygen demand (COD). The model adopts an ensemble learning strategy, improving the model’s performance by merging multiple advanced machine learning algorithms. We introduced several indices related to water quality parameters as auxiliary variables, such as NDCI and Enhanced Three, and used band data and these auxiliary variables as predictive variables, thereby greatly enhancing the predictive potential of the model.The results show that the inversion accuracy of these four inversion models is high (R2 of 0.94, 0.88, 0.92, and 0.93; RMSE of 1.15, 0.01, 0.02, and 0.02; MAE of 0.81, 0.01, 0.09, and 0.10), indicating that the STE model has good evaluation accuracy. Meanwhile, we used the STE model to reveal the spatio-temporal distribution of Chl-a, TP, TN, and COD from 2017 to 2018, and analyzed their seasonal and spatial variation rules. The results of this study not only provide an effective and practical method for monitoring and managing water quality parameters in inland lakes, but also provide water security for socio-economic and ecological environmental safety.

Experimental Study on Tailings Deposition Distribution Pattern and Sedimentation Characteristics.

Tailings pond accidents frequently occur during an extended period, resulting in loss of life and property, wastage of resources, and environmental pollution. Relying on tailings pond engineering, this paper carried out sample particle fragmentation experiments and settling column experiments to explore the deposition distribution pattern of tailings in both horizontal and vertical directions as well as the impact of particle size distribution on the sedimentation stratification effect. The results show that the median particle size on the dry beach surface in the horizontal direction slowly decreased with the increase in the distance from the subdam. The particle size of tailings showed great fluctuations in the vertical direction, which gradually became finer with the increase in the depth overall. At the same time, saturated sedimentation experiments suggested the inconsistent variation rule with the field test, namely, coarse on the bottom and fine at the top, and the change in particle size greatly affected the tailing sedimentation stratification effect. With the increase in fine particle content in tailings, the appearance time of the water-sand interface was shortened to within 30 min, but the sedimentation and consolidation completion times were delayed to about 1400 min. The settling column results indicate that the increase in fine particle content gradually weakened the sedimentation stratification effect, and the sedimentation pattern transformed from independent sedimentation to floc-type average sedimentation, which led to the enhanced water-retaining property of the settled layer. This may lead to an increase in the saturation line and a decrease in the length of the dry beach, seriously affecting the safe operation of the tailings pond. The research results provide some theoretical guidance and basic data for analyzing the consolidation efficiency of tailings and the stability of the tailings pond.

Fractal Characteristics and Microstructure of Coal with Impact of Starch-Polymerized Aluminum Sulfate Fracturing Fluids

The degree of irregularity and complexity of the pore structure are comprehensively reflected in the fractal dimension. The porosity of coal was determined by its fractal dimension, where a larger dimension indicates a lower porosity. Fractal theory and the Frenkel–Halsey–Hill (FHH) model were applied to explore the variation rules of concentration on functional groups and pore structure in this study. Combined with infrared spectroscopy (FTIR) and low-temperature nitrogen adsorption, a starch-polymerized aluminum sulfate composite fracturing fluid was prepared, which plays an important role in methane adsorption and permeability of coal samples. The test results showed that, compared with the original coal, the pore volume and specific surface area of each group of coal samples were reduced, the average pore diameter was initially enlarged and then declined, and fractal dimension D1 dropped by 5.4% to 15.4%, while fractal dimension D2 gained 1.2% to 7.9%. Moreover, the nitrogen adsorption of each group of coal samples was obviously lower than the original coal, and the concentration of starch-polymerized aluminum sulfate solution existed at a critical optimal concentration for the modification of the coal samples, and the nitrogen adsorption reached a minimum value of 0.6814 cm3/g at a concentration of 10%. The novel composite solution prepared by the combination of starch and flocculant in this paper enhanced the permeability of the coal seam, which is of great significance in improving the efficiency of coalbed methane mining.

Effect of frother on dynamic detachment of rising bubble-coarse particle aggregates at gas-liquid interface

In the flotation process, the bubble-coarse particle aggregates easily undergo detachment at the gas-liquid interface, resulting in low mineral recovery. This paper tested the variation rule of surface tension with a concentration in the solution of four alcohols frother, namely, n-pentanol (NPA), methyl isobutyl carbinol (MIBC), 2-octanol, and polypropylene glycol (PPG). The effects of frothers on the motion characteristics of rising bubble-coarse particle aggregates and the dynamic detachment of aggregates at the gas-liquid interface were investigated separately using a high-speed dynamic camera system and a dynamic detachment device. The results showed that the solution surface tension decreased and then tended to be stabilized with the increase of frother concentration. Under the same concentration, the stronger the surface activity of the frother, the smaller the rising velocity of the bubble-coarse particle aggregates, and the more stable the motion state of the aggregates, with a smaller velocity fluctuation. The lower rising velocity reduced the particle detachment probability when aggregates collided with the gas-liquid interface. The merger time of the bubble-coarse particle aggregates was extended with the improved surface activity of the frother, increasing by more than 1 s compared to the solution without the frother. The study will contribute to effectively reduce the dynamic detachment probability of bubbles-coarse particle aggregates at the gas-liquid interface by selecting the type and concentration of frothers, meanwhile optimizing the reagent regime to enhance the coarse particle flotation recovery in the practical production process.

Climate, litter quality and radiation duration jointly regulate the net effect of UV radiation on litter decomposition

Photodegradation via ultraviolet (UV) radiation is an important factor driving plant litter decomposition. Despite increasing attention to the role of UV photodegradation in litter decomposition, the specific impact of UV radiation on the plant litter decomposition stage within biogeochemical cycles remains unclear at regional and global scales. To clarify the variation rules of magnitude of UV effect on plant litter decomposition and their regulatory factors, we conducted a meta-analysis based on 54 published papers. Our results indicated that UV significantly promoted the mass loss of litter by facilitating decay of carbonaceous fractions and release of nitrogen and phosphorus. The promotion effect varied linearly or non-linearly with the time that litter exposed to UV, and with climatic factors. The UV effect on litter decomposition decreased first than increased on precipitation and temperature gradients, reaching its minimum in the area with a precipitation of 400–600 mm, and a temperature of 15–20 °C. This trend might be attributed to a potential equilibrium between the photofacilitation and photo-inhibition effects of UV under this condition. This variation in UV effect on precipitation gradient was in agreement with the fact that UV photodegradation effect was weakest in grassland ecosystems compared to that in forest and desert ecosystems. In addition, initial litter quality significantly influenced the magnitude of UV effect, but had no influence on the correlation between UV effect and climate gradient. Litter with lower initial nitrogen and lignin content shown a greater photodegradation effect, whereas those with higher hemicellulose and cellulose content had a greater photodegradation effect. Our study provides a comprehensive understanding of photodegradation effect on plant litter decomposition, indicates potentially substantial impacts of global enhancements of litter decomposition by UV, and highlights the necessity to quantify the contribution of photochemical minerallization pathway and microbial degradation pathway in litter decomposition.

Influence of magma intrusion on coal geochemical characteristics: a case study of Tiefa Daxing coal mine

Magma intrusion has an important influence on the physical and mechanical properties of coal and rock. In the area of magma intrusion, disasters such as gas outburst are prone to occur. Revealing its invasion law will be conducive to disaster management and energy development. For this purpose, changes in industrial analysis components of coal, mineral composition, major oxides, trace elements, and rare earth elements of coal under the thermal metamorphism of magma intrusion were analyzed. It is found that the moisture and volatile matter contents of the thermally affected coals in the mining face are generally lower than that of normal coals, while moisture and volatile matter contents are reduced towards to the magma intrusion contact. For example, the moisture and volatile matter of coal sample M01 decreased by 64.6% and 38.6% respectively compared with coal sample M05. During magma intrusion, some minerals remain on the surface of the coal body, resulting in changes in the mineral composition of the coal body. The decrease in carbon atom net spacing, the increase in crystallite aggregation and ductility, and aromaticity in thermally affected coals have a positive impact on the improvement of coal metamorphism. Due to the influences of magmatic intrusion, the variation rules of major oxides in coal are different, and the closer to the magmatic intrusion zone, the easier the major oxides are to be depleted. However, magma intrusion will not lead to the loss of all major oxides in thermally affected coals, such as content of CaO is 54.8%, which is higher than that of coal not affected by magmatic hydrothermal fluid. Most of the trace elements in the thermally affected coals of the No. 9 coal seam are depleted. The contents of rare earth elements are low on the whole coalbasis, with an average of 29.48 μg/g, and the distribution pattern towards to magmatic intrusion shows a wide and gentle “V” curve with left high and right low, showing the characteristics of enrichment of light rare earth elements.

Mechanical characteristics and application of cement-soil wrapped pile support structures for soil-rock combination pit in coastal area

In order to explore the mechanical properties of cement-soil wrapped pile support system in soil-rock combination foundation pit support. In this paper, based on a deep foundation pit project in Qingdao, the horizontal displacement monitoring test of cement-soil wrapped pile support system was carried out. Combined with ABAQUS finite element numerical simulation, the foundation support model of cement-soil wrapped pile in soil-rock combination foundation was established. The variation rule of bending moment and displacement of cement-soil wrapped pile under different influencing factors is explored, And the reasonable position of the micro steel pipe piles in the cement-soil pile is clarified. The results of the study show that the micro steel pipe piles have the best support with less horizontal displacement when they are located on the excavation side of the foundation pit. With the gradual increase of excavation depth, the horizontal stress of the soil basically increases linearly, which is consistent with the change rule of active soil pressure along the depth direction. Increasing the strength of cement-soil can significantly improve the deformation resistance of the supporting structure. The research results can provide reference for the design and construction of foundation support for soil-rock combination foundations.