A method for preparing an engineering slag precast pile and a variable frequency micro-amplitude vibration two-way compaction device

Abstract

This invention discloses a method and apparatus for preparing precast piles from engineering waste soil. The waste soil is sieved according to particle size. Based on the particle size composition of the waste soil, particle flow numerical simulation is used to simulate the compaction characteristics of waste soil with different particle sizes under ideal conditions, obtaining the maximum compaction density and gradation. Based on the maximum compaction density gradation under ideal conditions and the characteristic particle size of the cementitious material, different amounts of cementitious material are added to prepare the waste soil mixture. According to the evolution model of compaction density with pressure, the close packing gradation of the waste soil and cementitious material mixture is obtained. Experiments are conducted on the variation of compaction dry density with moisture content, clay mineral content, and cementitious material water demand under different pressure conditions. Based on a multi-parameter artificial neural network machine learning model, a model of dry density with moisture content, clay mineral content, and cementitious material water demand is constructed to obtain the optimal moisture content and maximum dry density under different pressure conditions. A variable frequency micro-amplitude vibration bidirectional compaction device is used for compaction and molding using a four-stage process: static pressure-strong vibration-weak vibration-static pressure.

Description

Technical Field

[0001] This invention belongs to the field of geotechnical engineering technology, specifically relating to a method for preparing precast piles for engineering waste soil and a variable frequency micro-amplitude vibration bidirectional compaction device. Background Technology

[0002] Waste construction waste is widely sourced, has a large stockpile, grows rapidly, and has a low utilization rate. It is mainly disposed of through landfilling, becoming a significant problem restricting rapid economic development and urbanization. Waste construction waste possesses multiphase media (water, soil, organic matter, microorganisms, etc.), with complex interfacial processes. During recycling, its structure is prone to instability, its framework is easily compressed, and the efficiency of solidification interface modification and control is low. This results in solidified waste products with low strength, easy agglomeration, and difficulty in compaction, leading to a low degree of recycling.

[0003] Traditional slag solidification technologies fail to fully understand the complex interfacial interactions between water, soil, and solidifying agents in multiphase media. This makes it difficult to effectively control these interactions during the modification process, affecting the stability and structural integrity of the slag. Regarding particle size control, existing technologies and processes consider the impact of particle size on the performance of recycled products (ZL201910143702.8, ZL201910535360.4, 201810290666.3), but have not yet achieved a theoretical and model-based breakthrough in slag particle size control technology, thus failing to meet the optimal gradation requirements for high-strength products.

[0004] Furthermore, in compaction molding, using traditional geotechnical engineering testing methods under constant compaction work conditions (light, heavy, and variable work ZL 202322163609.8), the obtained compaction parameters are insufficient to guide the preparation of solidified slag products using high-pressure (>600kN) processes. Moreover, when the solidifying agent dosage is greater than 5%, the influence of solidifying agent particle size on the gradation of the solidified slag product is not considered. Regarding moisture content control, the long-used limit moisture content provides an empirical reference for soil treatment and construction in geotechnical engineering. However, the optimal moisture content obtained through compaction based on the limit moisture content fails to consider the influence of slag composition, particle gradation, interfacial moisture form, moisture required during cementitious material hydration, and the interaction of hydration products at the interface. Therefore, it cannot meet the requirements for high-strength slag products formed through solidification and compaction. How to precisely control the moisture content of slag solidification materials and the influence of interparticle ion concentration and type on interfacial repulsion has become a key challenge.

[0005] In preform compaction molding, traditional processes include static compaction and vibration compaction. Static compaction (CN202410134060.6, ZL 202211024430.8) often relies on gravity and mold pressure, making it impossible to apply pressure evenly in all directions. Furthermore, unidirectional pressure due to frictional resistance leads to uneven internal density of the product, affecting overall performance. While vibration compaction (CN202410468285.5) can help the material particles to align more closely and reduce porosity through vibration, excessive vibration or improper processing can cause microcracks within the structure, affecting the stability of the cured product.

[0006] In summary, as a type of environmental soil, the existing technologies for the modification, solidification, and resource utilization of engineering waste soil have not yet addressed the interfacial properties such as the interaction relationships of multiphase media, particle size optimization, moisture content control, and the adjustment of particle spacing by external forces. There is an urgent need to develop a control method and equipment that can solve key problems such as low compaction, low strength, and poor stability of precast engineering waste soil products. This is of great significance for improving the resource utilization and high-value utilization of engineering waste soil. Summary of the Invention

[0007] To address the limitations of existing solidification and modification methods for construction waste soil, such as poor particle size distribution, inadequate moisture control, and poor control of solidification and compaction processes and equipment, which result in loose structure, low strength, and poor stability of construction waste soil products, this invention provides a method for preparing precast piles from construction waste soil. Based on "environmental soil interface mechanical modification and control technology," it innovates particle flow numerical simulation and compaction density evolution model with pressure, constructing the most compact packing gradation of construction waste soil and cementitious materials. A multi-parameter artificial neural network machine learning model is established to control the free water between construction waste soil particles, allowing for phase reconstruction of cementitious materials while further reducing the repulsive force between construction waste soil particles. A variable frequency micro-amplitude vibration bidirectional compaction device and a static pressure-strong vibration-weak vibration-static pressure process are developed, forming a new technical system for interface modification and control of precast solidified soil pile foundation treatment.

[0008] To achieve the above objectives, the following technical solution is adopted:

[0009] A method for preparing precast piles from engineering waste soil includes gradation optimization, moisture content control, and bidirectional compaction molding using variable frequency micro-amplitude vibration.

[0010] (1) The gradation optimization includes: pre-treating the slag soil and screening it according to the particle size; according to the particle size composition of the slag soil, using particle flow numerical simulation to simulate the compaction characteristics of slag soil with different particle sizes under ideal conditions, and obtaining the maximum compaction density and gradation; according to the gradation of the maximum compaction density under ideal conditions and the characteristic particle size of the cementitious material, adding different amounts of cementitious material to configure the slag soil mixture, and obtaining the close packing gradation of the slag soil and cementitious material mixture according to the evolution model of compaction density with pressure;

[0011] (2) The moisture content control includes: conducting tests on the change of compaction dry density with moisture content, clay mineral content and cementitious material water demand under different pressure conditions; establishing a dry density model with moisture content, clay mineral content and cementitious material water demand based on a multi-parameter artificial neural network machine learning model; and obtaining the optimal moisture content and maximum dry density under different pressure conditions.

[0012] (3) The variable frequency micro-amplitude vibration bidirectional compaction molding includes: according to the compaction resistance characteristics of the slag, the variable frequency alternating coil is controlled by the negative feedback control system, and the alternating electromagnetic induction under pressure generates micro-amplitude high frequency vibration to the slag mixture. The compaction bucket is equipped with the same frequency amplitude rods at the top and bottom, and the bidirectional vibration compaction molding is carried out. The specific compaction molding process includes a four-stage molding process of static pressure-strong vibration-weak vibration-static pressure.

[0013] According to the above scheme, the pretreatment of the slag soil in step 1 involves screening the slag soil according to particle size, including the following steps:

[0014] The slag was dried using a double-roll crusher, with the maximum particle size controlled to be <4.75mm. A multi-stage vibrating screen was then used to screen the crushed slag. The particle size ranges were as follows: coarse soil: 4.75–2.36mm, 2.36–1.18mm, 1.18–0.6mm, 0.6–0.15mm, 0.15–0mm; medium soil: 2.36–1.18mm, 1.18–0.6mm, 0.6–0.15mm, 0.15–0mm; fine soil: 1.18–0.6mm, 0.6–0.15mm, 0.15–0mm.

[0015] According to the above scheme, step 1, which uses particle flow numerical simulation to simulate the compaction characteristics of slag with different particle sizes under ideal conditions to obtain the maximum compaction density and gradation, includes the following steps:

[0016] The particles are set as rigid clusters (clump). Based on the single-interval components after the slag is screened, the log-normal distribution mode within the interval is adopted to generate a model with more than 1 million particles. The ideal compaction density of each single component under ideal conditions is calculated. Then the ideal compaction density of the slag under the full particle size component can be calculated by formula (1).

[0017] ρ0'=a∑ki ·ρ i ' (1)

[0018] In the formula: ρ0' is the ideal compacted density of different graded slag soils, in g / cm³. 3 ;a is a correction factor, dimensionless;k i ρ represents the mass percentage of each individual component, dimensionless; i ' is the ideal compacted density of each component (g / cm³). 3 .

[0019] Given the ideal compaction density and ideal compaction degree of each component, the maximum value of ρ0' is iteratively solved, and the mass proportion of each component is determined to establish the gradation. Based on the proportion of each component, the correction coefficient 'a' is determined using the single-component simulation method described above, thereby obtaining the maximum compaction degree under the optimal gradation of the slag. (When the slag gradation is poor, the dosage of a certain particle size component can be fixed, and the optimal gradation under special conditions can be determined using the above method to ensure the utilization rate of slag for precast piles of different types.)

[0020] According to the above scheme, the characteristic particle size of the cementitious material in step 1 is coarse-grained soil: d 90 ≤100μm, medium-grained soil: d 90 ≤45μm, fine-grained soil: d 90 ≤10μm; the amount of cementitious material is 5-15% of the dry weight of coarse soil, 8-18% of the dry weight of medium soil, and 12-24% of the dry weight of fine soil; the pressure range is 10-15MPa for coarse soil, 12-16MPa for medium soil, and 13-17MPa for fine soil.

[0021] According to the above scheme, the evolution model of compaction density with pressure described in step 1 is fitted with a general formula based on the density-pressure curve relationship, as shown in equation (2):

[0022] ρ(p)=a+1 / (b+c -p (2)

[0023] In the formula: ρ is the compaction density value with different cementitious material admixtures, p is the pressure value, c is the fitting parameter, a+1 / (b+1) is the loose bulk density value, a+1 / b is the maximum compaction density value, and the above formula is a general formula for fitting dimensionless values.

[0024] According to the above scheme, the different pressure conditions used in step 2 are: 9, 11, 13, and 15 MPa for coarse-grained soil, 10, 12, 14, and 16 MPa for medium-grained soil, and 11, 13, 15, and 17 MPa for fine-grained soil.

[0025] According to the above scheme, the moisture content mentioned in step 2 is in the range of w0-4% to w0+4%, where w0 is the baseline moisture content in the particle flow simulation calculation where all the pores of the slag are filled with water.

[0026] According to the above scheme, the water requirement of the cementitious material in step 2 is determined based on the material type and the paste test. The cementitious material is a hydraulic inorganic cementitious material with a 28-day paste strength > 32.5 MPa.

[0027] According to the above scheme, the artificial neural network machine learning model in step 2 has two hidden layers. The first hidden layer has 7 neurons, and the second hidden layer has 2 neurons. The input vector of the first hidden layer is calculated using equation (3):

[0028] z1=W1x+b1 (3)

[0029] In Equation 3, x is the input vector from the input layer, is the weight matrix of the first hidden layer, and W1 and b1 are the training parameters, where b1 is the bias vector.

[0030] The neuron is activated by the nonlinear function (4) and transmitted to the next layer:

[0031] a1=f(z1) (4)

[0032] a1 represents the output vector of the hidden layer, and f represents the non-linear activation function, which is the rectified linear unit (ReLU) function.

[0033] According to the above scheme, the four-stage molding process of static pressure-strong vibration-weak vibration-static pressure in step 3 includes: the first-stage static pressure range is 8-13 MPa for coarse-grained soil, 10-14 MPa for medium-grained soil, and 11-15 MPa for fine-grained soil; the static pressure time is 10-15 s for coarse-grained soil, 15-20 s for medium-grained soil, and 20-25 s for fine-grained soil; the second-stage strong vibration frequency is 100-300 Hz; the third-stage weak vibration frequency is 10-30 Hz; the fourth-stage static pressure range is 10-15 MPa for coarse-grained soil, 12-16 MPa for medium-grained soil, and 13-17 MPa for fine-grained soil; the static pressure time is 30-40 s for coarse-grained soil, 40-60 s for medium-grained soil, and 60-90 s for fine-grained soil. The process involves: first-stage static pressure to initially remove air between particles; second-stage strong vibration to adjust particle positions, allowing fine particles to quickly fill the pores between coarse particles; third-stage weak vibration to finely adjust particle positions, changing the particle contact of each component from point-to-surface to surface-to-surface, resulting in a dense matrix; and fourth-stage static pressure to dissipate pore water pressure, further stabilizing the highly dense matrix.

[0034] A variable frequency micro-amplitude vibration bidirectional compaction device for precast piles of engineering waste soil includes a negative feedback mode control system 1, an alternating coil generator 2, an amplitude rod 3, a blow-suction hole 4, a resistance-reducing sleeve 5, a vibration chamber 6, a hydraulic pressure plate 7, and a cable 8.

[0035] The two sides of the drag-reducing sleeve 5 are slidably connected to two amplitude rods 3. The other end of the amplitude rod 3 is coaxially threaded to the vibration chamber 6. The other end of the vibration chamber 6 is welded to the hydraulic pressure plate 7 to form a whole.

[0036] The negative feedback mode control system 1 is connected to the vibration chamber 6 via cable 8 to control the alternating coil generator 2;

[0037] The drag-reducing sleeve 5 has a blow-suction hole 4 at the middle position ±0.5m, which is connected to the blow-suction device. The blow-suction hole 4 is snap-fit ​​connected to the conduit of the external blow-suction device.

[0038] According to the above scheme, the alternating coil generator 2 includes an alternating coil 201, a winding iron block 202, and a guide disk 203; the alternating coil 201 is bonded to the iron pillars on both sides of the winding iron block 202 with sealing wax according to the right-hand screw rule, and one end of the winding iron pillar 202 is riveted to the upper part of the inner cavity of the vibration chamber 6, and the other end is welded to the guide disk 203.

[0039] According to the above scheme, the amplitude rod 3 includes an amplitude rod outer body 301, a disk 302, a spring 303, a movable pad 304, a fixed disk 305, and an inner impact rod 306; the amplitude rod outer body 301, spring 303, and movable pad 304 are configured to slide in contact with the inner impact rod 306, the disk 302 is threadedly connected to the inner impact rod 306, and the fixed disk 305 and the inner impact rod 306 are formed into a whole by welding.

[0040] The control system with negative feedback mode adopts an adaptive control algorithm with a response time of less than 20ms. The electromagnetic force generated by the alternating coil vibration is 0.3 to 0.5 times the pressure. The limit of the amplitude rod connecting the spring is 1 to 10mm. The drag-reducing sleeve and the compaction chamber include a porous design, with the porous structure arranged at ±0.5m in the middle of the pile length. The blowing and suction device is used to blow in lubricating oil or release agent and to suck out the air generated during the compaction of the precast pile under negative pressure. The orifice diameter of the blowing and suction device is 0.1-2mm.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] As a type of environmental soil, engineering waste soil requires consideration of interfacial property control during its modification, solidification, and resource utilization, taking into account the interaction relationships of multiphase media, particle size distribution optimization, moisture content control, and external force adjustment of particle spacing. This invention discloses a method and apparatus for preparing precast piles using a gradation optimization, moisture content control, variable frequency micro-amplitude vibration bidirectional compaction device, and a four-stage forming process of static pressure-strong vibration-weak vibration-static pressure. In the gradation optimization process, crushing and screening are first performed to classify different types of waste soil, providing a prerequisite for particle size control. Optimal gradation and ideal compaction degree are obtained through particle flow numerical simulation, overcoming the limitations of traditional methods. The technology, which relies on empirical trial mixing, further considers the impact of particle size and dosage of cementitious materials on compaction based on a constant pressure compaction density evolution model for different gradations. This clarifies the required particle size and dosage of cementitious materials for different types of slag, providing support for subsequent slag compaction processes. In the moisture content control process, a multi-parameter artificial neural network machine learning model was constructed, incorporating parameters such as clay mineral content, particle size distribution, mass fractal dimension, and water demand of cementitious materials. This model precisely controls the free water between slag particles, further reducing inter-particle repulsion while satisfying the phase reconstruction requirements of the cementitious materials. This method not only considers the influence of clay mineral content and particle morphology on moisture content, but also incorporates the water required for cementitious material hydration, precisely controlling the moisture content required for densified products. Compared to traditional methods that rely on experience, obtaining the optimal moisture content and maximum dry density through compaction tests using compaction curves is more scientifically sound. The developed variable frequency micro-amplitude vibration bidirectional compaction device overcomes the shortcomings of traditional molding methods, such as the inability to apply pressure uniformly in all directions and the uneven internal density of the product due to unidirectional pressure caused by frictional resistance, which affects overall performance. The proprietary high-frequency micro-amplitude device design not only improves the compactness between particles and reduces porosity, but also solves the problems of excessive vibration or excessive processing. Improper processing can lead to microcracks within the structure. The porous design allows for gas drainage, reducing energy consumption and improving the economic efficiency of precast slag pile fabrication. The accompanying four-stage molding process—static pressure-strong vibration-weak vibration-static pressure—initially removes gas between particles through the first stage of static pressure; the second stage of strong vibration adjusts particle positions, allowing fine particles to quickly fill the pores between coarse particles; the third stage of weak vibration finely adjusts particle positions, changing the particle contact from point-to-surface to surface-to-surface, resulting in a dense matrix; and the fourth stage of static pressure dissipates pore water pressure, further stabilizing the highly dense matrix and modifying the fabrication of high-performance slag piles. This process solves key problems such as low compaction, low strength, and poor stability in slag precast products. Attached Figure Description

[0043] Figure 1 Compaction density curves and fitting curves under different pressure ranges.

[0044] Figure 2 Artificial neural network machine learning model.

[0045] Figure 3Schematic diagram of a variable frequency micro-amplitude vibration bidirectional compaction device.

[0046] Figure 4 Schematic diagram of an alternating coil generator.

[0047] Figure 5 Schematic diagram of the amplitude bar structure.

[0048] Figure reference numerals: 1-Negative feedback mode control system; 2-Alternating coil generator; 3-Amplitude bar; 4-Blow-suction hole; 5-Resistance reducing sleeve; 6-Vibration chamber; 7-Hydraulic pressure plate; 8-Cable; 201-Alternating coil; 202-Winding iron block; 203-Guide disk; 301-Amplitude bar outer body; 302-Disk; 303-Spring; 304-Modible pad; 305-Fixed disk; 306-Inner impact rod of amplitude bar. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0050] The specific implementation provides a method for preparing precast piles from engineering waste soil based on environmental soil interface mechanical modification and control technology. The engineering waste soil used is sampled from the construction site. According to the soil properties, the waste soil is coarse-grained soil. The waste soil is pretreated by screening according to particle size, drying the waste soil at laboratory scale, using a double-roll crusher to control the maximum particle size of the waste soil to <4.75mm, and using a multi-stage vibrating screen to screen the crushed waste soil. The screened particle groups are 4.75~2.36mm, 2.36~1.18mm, 1.18~0.6mm, 0.6~0.15mm, and 0.15~0mm, respectively, with the mass proportions of each component being 0.11, 0.18, 0.33, 0.20, and 0.18.

[0051] The compaction characteristics of slag with different particle sizes under ideal conditions were simulated by particle flow numerical simulation. The particles were set as rigid clusters. Based on the single-interval components after slag screening, the log-normal distribution mode within the interval was adopted to generate a model with more than 1 million particles. The ideal compaction density of each single component under ideal conditions was calculated. Then the ideal compaction density of slag under all particle size components can be calculated by equation (1).

[0052] ρ0'=a∑k i ·ρ i ' (1)

[0053] In the formula: ρ0' is the ideal compacted density of different graded slag soils, a is the correction coefficient, and k i ρ represents the mass percentage of each individual component. i ' represents the ideal compaction density of each individual component.

[0054] Based on the above simulation calculations, the ρ0' of the five single components in the ranges of 4.75–2.36 mm, 2.36–1.18 mm, 1.18–0.6 mm, 0.6–0.15 mm, and 0.15–0 mm are respectively 2.23 g / cm³. 3 2.26 g / cm 3 2.44 g / cm 3 2.21 g / cm 3 2.12 g / cm 3 The correction factor a is 1.07, and the ideal compaction density ρ0' of the slag soil under all particle size components is 2.44.

[0055] Using the characteristic particle size d of cementitious materials 90 The compaction density is 85 μm, with a cementitious material content of 12%. The compaction density curves and fitted curves under different pressure ranges (10-15 MPa) are shown below. Figure 1 As shown. The maximum compacted density is 2.51 g / cm³. 3 .

[0056] In the particle flow simulation calculation, the pores of the slag were completely filled with water as the baseline moisture content of 21.3%. The moisture content range used in the experiment was 17.3% to 24.3%, and the constant pressures were 9, 11, 13, and 15 MPa. The cementing material was 425 cement, with a 28-day neat cement paste strength of 44.3 MPa and a water requirement of 26.5% of the cementing material.

[0057] A specific implementation provides an artificial neural network machine learning model, see appendix. Figure 2 As shown. (0 Cementitious material content, 1 Clay mineral content, 2 Required water content of cementitious material, 3 Input vector (3), 4-10 First hidden layer nodes, 11 Nonlinear activation function, 12-13 Second hidden layer nodes, 14 Output function)

[0058] The artificial neural network machine learning model has two hidden layers. The first hidden layer has 7 neurons, and the second hidden layer has 2 neurons. The input vector of the first hidden layer is calculated using equation (3):

[0059] z1=W1x+b1 (3)

[0060] In Equation 3, x is the input vector from the input layer, is the weight matrix of the first hidden layer, and W1 and b1 are the training parameters, where b1 is the bias vector.

[0061] The neuron is activated by the nonlinear function (4) and transmitted to the next layer:

[0062] a1=f(z1) (4)

[0063] a1 represents the output vector of the hidden layer, and f represents the non-linear activation function, which is the rectified linear unit (ReLU) function.

[0064] The training process is as follows: First, at a pressure of 9 MPa, a set of input data is given to the neural network. In this model, the data are: 5% cementitious material content, 2.3% clay mineral content, and 12% water required for cementitious material. The network is then propagated forward to obtain an optimal moisture content output. Next, the optimal moisture content output is compared with the expected result to calculate an error value. Then, the error value is propagated backward along the network. Based on the contribution of each node and connection to the error value (input vector), the gradient value of each node and connection is calculated. Finally, based on the gradient values ​​of each node and connection, the weight and bias values ​​of each node and connection are updated to reduce the error value. When the error is controlled within an acceptable range, the prediction result is output.

[0065] The optimal moisture content and maximum dry density under various pressure levels predicted using the aforementioned artificial neural network model are shown in Table 1.

[0066] Table 1

[0067] Pressure (MPa) Optimal moisture content (%) <![CDATA[Maximum dry density (g / cm 3 )]]> 9 22.4 2.48 11 21.3 2.53 13 19.7 2.55 15 18.6 2.56

[0068] To facilitate the implementation of the variable frequency micro-amplitude vibration bidirectional compaction molding process, a specific embodiment provides a variable frequency micro-amplitude vibration bidirectional compaction device, as shown in the attached figure. Figures 3 to 5 The device includes a negative feedback mode control system 1, an alternating coil generator 2, an amplitude bar 3, a blow-suction hole 4, a drag-reducing sleeve 5, a vibration chamber 6, a hydraulic pressure plate 7, and a cable 8.

[0069] The two sides of the drag-reducing sleeve 5 are slidably connected to two amplitude rods 3. The other end of the amplitude rod 3 is coaxially threaded to the vibration chamber 6. The other end of the vibration chamber 6 is welded to the hydraulic pressure plate 7 to form a whole.

[0070] The negative feedback mode control system 1 is connected to the vibration chamber 6 via cable 8 to control the alternating coil generator 2;

[0071] The drag-reducing sleeve 5 has a blow-suction hole 4 at the middle position ±0.5m, which is connected to the blow-suction device. The blow-suction hole 4 is snap-fit ​​connected to the conduit of the external blow-suction device.

[0072] Reference Appendix Figure 4The alternating coil generator 2 includes an alternating coil 201, a winding iron block 202, and a guide disk 203. The alternating coil 201 is bonded to the iron pillars on both sides of the winding iron block 202 with sealing wax according to the right-hand screw rule. One end of the winding iron block 202 is riveted to the upper part of the inner cavity of the vibration chamber 6, and the other end is welded to the guide disk 203.

[0073] Reference Appendix Figure 5 The amplitude rod 3 includes an outer body 301, a disk 302, a spring 303, a movable pad 304, a fixed disk 305, and an inner impact rod 306. The outer body 301, spring 303, and movable pad 304 are in sliding contact with the inner impact rod 306. The disk 302 is threadedly connected to the inner impact rod 306. The fixed disk 305 and the inner impact rod 306 are welded together to form a whole.

[0074] The specific usage method of this device includes the following steps:

[0075] (1) Before preparing the precast pile, lubricating oil or release agent is injected into the inner wall of the resistance-reducing sleeve 5 through the blow-suction hole 4. The injection time is 1s-2s, and the amplitude rod 3 is moved to make the lubricating oil or release agent evenly distributed. The blow-suction hole 4 is located at the middle position of the pile length ±0.5m, and the hole diameter range is 0.1-2mm.

[0076] (2) When the precast pile is started, put the engineering slag material that has been optimized in terms of gradation and optimal moisture content into the cavity of the drag-reducing sleeve 5 which has been coated with lubricating oil or release agent. Open the hydraulic pressure plate 7 and push the amplitude rod 3 into the cavity of the drag-reducing sleeve 5 until it touches the engineering slag material.

[0077] (3) During the precast pile compaction process, the high-pressure gas generated during the precast pile preparation process is removed through the blow-suction hole 4 until the amplitude rods 3 on both sides of the resistance-reducing sleeve 5 can no longer be pressed in.

[0078] (4) During the micro-amplitude high-frequency vibration of the precast pile, the alternating coil 201 is controlled by the negative feedback mode control system 1 to generate a changing magnetic field around the winding iron block 202. The guide disk 203 drives the disk 302 to drive the impact rod 306 inside the amplitude rod to perform micro-amplitude high-frequency simple harmonic motion in the outer body 301 of the amplitude rod to generate an axial additional force. The guide disk 203 and disk 302 are limited to 10mm. The negative feedback mode control system adopts an adaptive control algorithm with a response time of less than 20ms. The axial additional force generated by the alternating coil generator is 0.3 to 0.5 times the set pressure.

[0079] (5) After the precast pile is prepared by bidirectional impact extrusion and micro-amplitude high-frequency vibration, the resistance-reducing sleeve 5 is placed into the demolding machine for demolding treatment, and the precast pile preparation is completed.

[0080] According to the different pressure conditions in Table 1, the moisture content of the slag was controlled, and the precast pile mixture was prepared and put into the pressure chamber. The variable frequency micro-amplitude vibration bidirectional compaction device was turned on. The electromagnetic force generated by the alternating coil generator was 0.35 times the set pressure. The limit of the amplitude rod connecting the spring was 8mm. The design of the resistance-reducing sleeve and the compaction chamber hole was at the middle position of the pile length, and the hole diameter was 1.5mm. Bidirectional compaction vibration molding was performed. The first level static pressure was 11MPa, and the static compaction time was 12s for coarse-grained soil. The second level strong vibration frequency was 150Hz, the third level weak vibration frequency was 15Hz, and the fourth level static pressure was 13MPa, and the static compaction time was 35s for coarse-grained soil. After demolding, curing was carried out, and the single pile strength was tested after 7 days and was 15.6MPa.

[0081] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for preparing precast piles from engineering waste soil, characterized in that... This includes gradation optimization, moisture content control, and bidirectional compaction molding using variable frequency micro-amplitude vibration. (1) The gradation optimization includes: pre-treating the slag soil and screening it according to the particle size; according to the particle size composition of the slag soil, using particle flow numerical simulation to simulate the compaction characteristics of slag soil with different particle sizes under ideal conditions, and obtaining the maximum compaction density and gradation; according to the gradation of the maximum compaction density under ideal conditions and the characteristic particle size of the cementitious material, adding different amounts of cementitious material to prepare the slag soil mixture, and obtaining the close packing gradation of the slag soil and cementitious material mixture according to the evolution model of compaction density with pressure; The method of using particle flow numerical simulation to simulate the compaction characteristics of slag with different particle sizes under ideal conditions, and to obtain the maximum compaction density and gradation, includes the following steps: The particles are set as rigid clusters (clump). Based on the single-interval components after the slag is screened, the log-normal distribution mode within the interval is adopted to generate a model with more than 1 million particles. The ideal compaction density of each single component under ideal conditions is calculated. Then the ideal compaction density of the slag under the full particle size component can be calculated by formula (1). ρ 0 ＇ =a∑k i · ρ i ＇ Equation (1) In the formula: ρ 0 ＇ The ideal compaction density of different gradations of slag soil, g / cm³ 3 ;a is a correction factor, dimensionless;k i The mass percentage of each individual component is dimensionless. ρ i ＇ The ideal compaction density of each component (g / cm³) 3 ; Given the ideal compacted density and ideal compaction degree of each component, solve iteratively. ρ 0 ＇ The maximum value is determined, and the mass ratio of each component is determined to determine the gradation. Based on the proportion of each component, the above single-component simulation method is used to determine the correction coefficient 'a', and then the maximum compaction degree under the optimal gradation of the slag soil is obtained. The evolution model of compaction density with pressure is fitted with a general formula based on the density-pressure curve relationship, as shown in equation (2): ρ ( p ) = a + 1 / (b + c) -p Equation (2) In the formula: ρ These represent the compaction density values ​​for different cementitious material admixtures. p Here, c is the pressure value, a+1 / (b+1) is the loose bulk density value, and a+1 / b is the maximum compacted density value. The above formula is a general formula for fitting dimensionless values. (2) The moisture content control includes: conducting tests on the change of compaction dry density with cementitious material dosage, clay mineral content and cementitious material water demand under different pressure conditions; establishing a dry density model with cementitious material dosage, clay mineral content and cementitious material water demand based on a multi-parameter artificial neural network machine learning model; and obtaining the optimal moisture content and maximum dry density under different pressure conditions. (3) The variable frequency micro-amplitude vibration bidirectional compaction molding includes: using a variable frequency micro-amplitude vibration bidirectional compaction device to carry out a four-stage molding process of static pressure-strong vibration-weak vibration-static pressure.

2. The method for preparing precast piles from engineering waste soil as described in claim 1, characterized in that... The pre-treated slag soil described in step 1 involves screening the slag soil according to particle size, including the following steps: The slag was dried using a double-roll crusher, with the maximum particle size controlled to be <4.75 mm. A multi-stage vibrating screen was then used to screen the crushed slag. The particle size ranges were as follows: coarse soil: 4.75~2.36 mm, 2.36~1.18 mm, 1.18~0.6 mm, 0.6~0.15 mm, 0.15~0 mm; medium soil: 2.36~1.18 mm, 1.18~0.6 mm, 0.6~0.15 mm, 0.15~0 mm; fine soil: 1.18~0.6 mm, 0.6~0.15 mm, 0.15~0 mm.

3. The method for preparing precast piles from engineering waste soil as described in claim 1, characterized in that... The characteristic particle size of the cementitious material mentioned in step 1 is as follows: coarse soil: d90≤100 μm, medium soil: d90≤45 μm, fine soil: d90≤10 μm; the cementitious material dosage is 5-15% of the dry weight of coarse soil, 8-18% of the dry weight of medium soil, and 12-24% of the dry weight of fine soil; the pressure range is 10-15 MPa for coarse soil, 12-16 MPa for medium soil, and 13-17 MPa for fine soil.

4. The method for preparing precast piles from engineering waste soil as described in claim 1, characterized in that... The different pressure conditions used in step 2 are: 9, 11, 13, and 15 MPa for coarse-grained soil, 10, 12, 14, and 16 MPa for medium-grained soil, and 11, 13, 15, and 17 MPa for fine-grained soil; the moisture content range is... w 0-4%~ w 0+4%, of which w 0 represents the baseline moisture content in the particle flow simulation, where all pores of the slag are filled with water. 。 5. The method for preparing precast piles from engineering waste soil as described in claim 1, characterized in that... The water requirement of the cementitious material in step 2 is determined based on the material type and the neat paste test. The cementitious material is a hydraulic inorganic cementitious material with a neat paste strength of >32.5 MPa after 28 days.

6. The method for preparing precast piles from engineering waste soil as described in claim 1, characterized in that... The artificial neural network machine learning model described in step 2 has two hidden layers. The first hidden layer has 7 neurons, and the second hidden layer has 2 neurons. The input vector of the first hidden layer is calculated using equation (3): z 1=W1 x +b1(3) In Equation 3, x is the input vector from the input layer, is the weight matrix of the first hidden layer, and W1 and b1 are the training parameters, where b1 is the bias vector. The neuron is activated by the nonlinear function (4) and transmitted to the next layer: a1= f (z1) (4) a1 represents the output vector of the hidden layer. f The representative nonlinear activation function is the rectified linear unit (ReLU) function.

7. The method for preparing precast piles from engineering waste soil as described in claim 1, characterized in that... The four-stage molding process of static pressure-strong earthquake-weak earthquake-static pressure described in step 3 includes: Level 1 static pressure range of 8-13 MPa for coarse-grained soil, 10-14 MPa for medium-grained soil, and 11-15 MPa for fine-grained soil; static pressure time of 10-15 s for coarse-grained soil, 15-20 s for medium-grained soil, and 20-25 s for fine-grained soil; Level 2 strong earthquake frequency of 100-300 Hz; Level 3 weak earthquake frequency of 10-30 Hz; Level 4 static pressure range of 10-15 MPa for coarse-grained soil, 12-16 MPa for medium-grained soil, and 13-17 MPa for fine-grained soil; static pressure time of 30-40 s for coarse-grained soil, 40-60 s for medium-grained soil, and 60-90 s for fine-grained soil.

8. The method for preparing precast piles from engineering waste soil as described in claim 1, characterized in that... The variable frequency micro-amplitude vibration bidirectional compaction device described in step 3 includes a negative feedback mode control system 1, an alternating coil generator 2, an amplitude rod 3, a blow-suction hole 4, a resistance-reducing sleeve 5, a vibration chamber 6, a hydraulic pressure plate 7, and a cable 8. The two sides of the drag-reducing sleeve 5 are slidably connected to two amplitude rods 3. The other end of the amplitude rod 3 is coaxially threaded to the vibration chamber 6. The other end of the vibration chamber 6 is welded to the hydraulic pressure plate 7 to form a whole. The negative feedback mode control system 1 is connected to the vibration chamber 6 via cable 8 to control the alternating coil generator 2; The drag-reducing sleeve 5 has a blow-suction hole 4 at the middle position ±0.5m, which is connected to the blow-suction device. The blow-suction hole 4 is snap-fit ​​connected to the conduit of the external blow-suction device.

9. The method for preparing precast piles from engineering waste soil as described in claim 8, characterized in that... The alternating coil generator 2 includes an alternating coil 201, a winding iron block 202, and a guide disk 203. The alternating coil 201 is bonded to the iron pillars on both sides of the winding iron block 202 with sealing wax according to the right-hand screw rule. One end of the winding iron block 202 is riveted to the upper part of the inner cavity of the vibration chamber 6, and the other end is welded to the guide disk 203.

10. The method for preparing precast piles from engineering waste soil as described in claim 8, characterized in that... The amplitude rod 3 includes an outer body 301, a disk 302, a spring 303, a movable pad 304, a fixed disk 305, and an inner impact rod 306. The outer body 301, spring 303, and movable pad 304 are in sliding contact with the inner impact rod 306. The disk 302 is threadedly connected to the inner impact rod 306. The fixed disk 305 and the inner impact rod 306 are welded together to form a whole.

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