Method for evaluating moraine soil dynamic compaction effect based on dynamic compaction method

Abstract

The invention discloses a moraine soil dynamic compaction effect evaluation method based on a dynamic compaction method, and relates to the technical field of moraine soil compaction, and the moraine soil dynamic compaction effect evaluation method comprises the following steps: constructing a moraine soil foundation physical model, and simulating a dynamic compaction construction process according to the constructed moraine soil foundation physical model to obtain corresponding construction simulation parameters; comparing the obtained construction simulation parameters with actual construction process parameters to obtain a corresponding parameter comparison table; evaluating the compaction effect of the moraine soil in the dynamic compaction construction process based on the obtained parameter comparison table; the dynamic evolution process of particles in the moraine soil under the impact load and the influence of the particles on the overall compaction effect are determined, the microstructure change rule in the compaction process is revealed, and a scientific basis is provided for the moraine soil dynamic compaction reinforcement technology; the key process parameters influencing the compaction effect of the moraine soil accumulation body are identified and optimized by combining tests and numerical simulation, and an optimal reinforcement strategy aiming at the characteristics of moraine soil is provided.

Description

Technical Field

[0001] The invention relates to the technical field of moraine soil compaction, in particular to a method for evaluating the compaction effect of moraine soil compaction based on a dynamic compaction method. Background Art

[0002] As a special geological sediment widely distributed in southeastern Tibet, moraine soil has the characteristics of looseness, low density and poor stability due to its extremely poor particle grading and significant changes in physical and mechanical properties, which brings great risks to engineering construction. The construction of engineering facilities on moraine soil accumulation bodies requires effective reinforcement methods to ensure that they have sufficient bearing capacity and stability to avoid disasters such as landslides. Therefore, the study of the macro- and micro-mechanical properties of moraine soil and its compaction methods, especially the study of the compaction mechanism of moraine soil foundation reinforcement by dynamic compaction, has important scientific significance and engineering application value. It can not only solve the safety problems in actual engineering, but also provide a scientific basis for the development and utilization of moraine soil accumulation bodies. How to effectively evaluate the compaction effect of moraine soil by dynamic compaction method, so as to assist in optimizing the key process parameters in the dynamic compaction process of moraine soil, is a problem we need to solve. To this end, a method for evaluating the compaction effect of moraine soil by dynamic compaction method is provided. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for evaluating the compaction effect of moraine soil based on the dynamic compaction method.

[0004] The object of the present invention can be achieved by the following technical solution: A method for evaluating the compaction effect of moraine soil based on the dynamic compaction method, comprising: Construct a physical model of moraine foundation, and simulate the dynamic compaction construction process based on the constructed physical model of moraine foundation to obtain the corresponding construction simulation parameters; Based on the comparison of the obtained construction simulation parameters with the actual construction process parameters, a corresponding parameter comparison table is obtained; Based on the obtained parameter comparison table, the compaction effect of the dynamic compaction construction process on moraine soil was evaluated.

[0005] Furthermore, the process of constructing the physical model of moraine foundation includes: Moraine soil was selected as the sample, and the particle composition of the moraine soil was determined by particle sieving method. The particles were flattened to obtain the particle gradation data. By vertically photographing the tiled particles, the two-dimensional image of each particle is determined, and the particle edge morphology is extracted; According to the obtained edge morphological characteristics, the morphological characteristics of the particles are obtained; Based on the obtained particle morphology, the particle failure load is obtained through the discrete element numerical model; Then, the particles are subjected to particle strength analysis to obtain corresponding particle strength indexes; According to the particle gradation data of moraine soil, the corresponding alternative materials are selected, and the obtained alternative materials are mixed and configured to obtain the corresponding test materials; A model box is constructed, and the obtained test materials are filled into the model box in layers. At the same time, corresponding sensors are arranged to complete the construction of the physical model of the moraine foundation.

[0006] Furthermore, the particle gradation data is the proportion of particles in different particle size ranges in the sample.

[0007] Furthermore, the process of obtaining the particle failure load of the particle through the discrete element numerical model is as follows: Apply external force or displacement boundary conditions to each obtained particle, and obtain the motion equation of each particle through implicit time integration method, and then update the position and velocity of the particle; According to the obtained motion equations of each particle and the changes in particle position and velocity, the actual stress conditions are simulated to obtain the particle failure load corresponding to each particle.

[0008] Furthermore, the dynamic compaction construction process is simulated based on the constructed moraine foundation physical model, and the process of obtaining the corresponding construction simulation parameters includes: Set model rammers of different weights, and set high and low rammer drop points; The construction simulation parameters are generated by setting different model rammers at different landing points; The construction simulation parameters include the number of tamping times, the landing height of each tamping, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping; Based on the obtained construction simulation parameters, the actual construction parameters are called to generate the corresponding parameter comparison table.

[0009] Furthermore, the corresponding similarity coefficient is obtained based on the landing point height, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping of the construction simulation parameters and the landing point height, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping of the actual construction parameters; A mechanical property prediction model of particle characteristics is constructed based on the obtained similarity coefficients.

[0010] Furthermore, the process of constructing the mechanical property prediction model of particle characteristics includes: Obtaining the stress exerted on each sensor arranged in the model box during each tamping, and obtaining the corresponding radial strain field and vertical strain field based on the obtained stress exerted on each sensor; At the same time, the displacement field of the soil at different time points and the displacement data of each position during each tamping are obtained through the image acquisition device; Then the local volume strain field corresponding to the soil is obtained; Summarize the data obtained from each tamping, use the data summarized from each tamping as sample data, and divide the sample data into a training set and a test set; Constructing a multiple regression analysis model, inputting the obtained training set into the constructed multiple regression analysis model to train the multiple regression analysis model, and completing the training of all sample data in the training set; The training results of each training are then evaluated using the test set. If the evaluation results meet expectations, the training is terminated. If the evaluation results do not meet expectations, a second round of training is carried out, and so on, until the evaluation results meet expectations or the number of training times reaches the preset upper limit.

[0011] Furthermore, the process of evaluating the compaction effect of the dynamic compaction construction process on moraine soil based on the obtained parameter comparison table includes: Acquire real-time construction parameters corresponding to the dynamic compaction construction process, wherein the real-time construction parameters include tamping hammer parameters, number of tamping blows, landing point height corresponding to each tamping blow, and effective reinforcement depth corresponding to each tamping blow; The parameters of the rammer include weight and diameter; The obtained real-time construction parameters are input into the trained multiple regression analysis model, and the corresponding compaction prediction evaluation results are output in combination with the obtained similarity coefficients corresponding to the parameter comparison table.

[0012] Compared with the prior art, the present invention has the following beneficial effects: Clarify the dynamic evolution process of particles inside moraine under impact loads and its influence on the overall compaction effect, reveal the law of microstructural changes during the compaction process, and provide a scientific basis for the dynamic compaction reinforcement technology of moraine soil; optimize the dynamic compaction process parameters to improve the reinforcement effect of moraine soil accumulation: by combining experiments and numerical simulations, identify and optimize the key process parameters (such as hammer weight, drop distance, and tamping energy) that affect the compaction effect of moraine soil accumulation, and propose the best reinforcement strategy based on the characteristics of moraine soil. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0014] Figure 1 Flowchart of the present invention. DETAILED DESCRIPTION

[0015] like Figure 1 As shown in the figure, the evaluation method of the compaction effect of moraine soil based on the dynamic compaction method includes: Construct a physical model of moraine foundation, and simulate the dynamic compaction construction process based on the constructed physical model of moraine foundation to obtain the corresponding construction simulation parameters; Based on the comparison of the obtained construction simulation parameters with the actual construction process parameters, a corresponding parameter comparison table is obtained; Based on the obtained parameter comparison table, the compaction effect of the dynamic compaction construction process on moraine soil was evaluated.

[0016] It should be further explained that, in the specific implementation process, the process of constructing the physical model of moraine foundation includes: Moraine soil was selected as the sample, and the particle composition of the moraine soil was determined by particle sieving method. The particles were flattened to obtain the particle gradation data. It should be noted that the particle gradation data is the proportion of particles of different particle size ranges in the sample; By vertically photographing the tiled particles, the two-dimensional image of each particle is determined, and the particle edge morphology is extracted; According to the obtained edge morphological characteristics, the morphological characteristics of the particles are obtained, and the morphological characteristics include roundness R, edge angle L, and elongation Y, wherein: ; ; ; Where A is the area of ​​the particle projection image, AC is the area of ​​the minimum convex shape circumscribed by the particle projection image, FL and FT are Feret length and width respectively; Based on the obtained particle morphology, the particle failure load is obtained through the discrete element numerical model; Then, the particle strength analysis is performed on the particles to obtain the corresponding particle strength index, which is recorded as ,in: ; Among them, F f is the particle failure load, d is the particle size; According to the particle gradation data of moraine soil, the corresponding alternative materials are selected, and the obtained alternative materials are mixed and configured to obtain the corresponding test materials; A model box is constructed, and the obtained test materials are filled into the model box in layers. At the same time, corresponding sensors are arranged to complete the construction of the physical model of the moraine foundation.

[0017] It should be further explained that the process of obtaining the particle failure load of particles through the discrete element numerical model is as follows: Apply external forces (such as gravity, pressure, etc.) or displacement boundary conditions to each obtained particle to simulate the actual force conditions of the particle. Through the implicit time integration method, the motion equation of each particle is obtained, and then the position and velocity of the particle are updated; According to the obtained motion equations of each particle and the changes in particle position and velocity, the actual stress conditions are simulated to obtain the particle failure load corresponding to each particle.

[0018] In the specific implementation process, the model box is usually divided into several layers and loaded in layers, and the thickness of the test material in each layer is the same.

[0019] It should be further explained that, in the specific implementation process, the dynamic compaction construction process is simulated according to the constructed moraine foundation physical model, and the process of obtaining the corresponding construction simulation parameters includes: Set model rammers of different weights, and set high and low rammer drop points; The construction simulation parameters are generated by setting different model rammers at different landing points; The construction simulation parameters include the number of tamping times, the landing height of each tamping, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping; Based on the obtained construction simulation parameters, the actual construction parameters are called to generate a corresponding parameter comparison table, wherein the parameter comparison table includes a plurality of comparison items, and the construction simulation parameters and the actual construction parameters are imported into the corresponding parameter items; Here is a set of parameter comparison tables for specific implementation process for reference, as shown in Table 1:

[0020] Table 1 According to the obtained parameter comparison table, the similarity coefficient between the construction simulation parameters and the actual construction parameters is obtained; The construction simulation parameters of each landing point height, each tamping energy and each tamping effective reinforcement depth are recorded as 、 、 ; The landing point height corresponding to the actual construction parameters, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping are recorded as 、 、 ; The corresponding similarity coefficients are recorded as 、 as well as ; A mechanical property prediction model of particle characteristics is constructed based on the obtained similarity coefficients.

[0021] It should be further explained that, in the specific implementation process, the construction process of the mechanical property prediction model of particle characteristics includes: Obtaining the stress exerted on each sensor arranged in the model box during each tamping, and obtaining the corresponding radial strain field and vertical strain field based on the obtained stress exerted on each sensor; At the same time, the displacement field of the soil at different time points and the displacement data of each position during each tamping are obtained through the image acquisition device; Then the local volume strain field corresponding to the soil is obtained, namely: ; in represents the local volume strain field, represents the radial strain field, represents the vertical strain field; Summarize the data obtained from each tamping, use the data summarized from each tamping as sample data, and divide the sample data into a training set and a test set; Constructing a multiple regression analysis model, inputting the obtained training set into the constructed multiple regression analysis model to train the multiple regression analysis model, and completing the training of all sample data in the training set; The training results of each training are then evaluated using the test set. If the evaluation results meet expectations, the training is terminated. If the evaluation results do not meet expectations, a second round of training is carried out, and so on, until the evaluation results meet expectations or the number of training times reaches the preset upper limit.

[0022] It should be further explained that, in the specific implementation process, the process of evaluating the compaction effect of the dynamic compaction construction process on moraine soil based on the obtained parameter comparison table includes: Acquire real-time construction parameters corresponding to the dynamic compaction construction process, wherein the real-time construction parameters include tamping hammer parameters, number of tamping blows, landing point height corresponding to each tamping blow, and effective reinforcement depth corresponding to each tamping blow; The parameters of the rammer include weight and diameter; The obtained real-time construction parameters are input into the trained multiple regression analysis model, and the corresponding compaction prediction evaluation results are output in combination with the obtained similarity coefficients corresponding to the parameter comparison table.

[0023] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any modification or equivalent replacement of the above embodiments made according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention.

Claims

1. A method for evaluating the compaction effect of moraine soil based on dynamic compaction, characterized in that: include: Construct a physical model of moraine foundation, and simulate the dynamic compaction construction process based on the constructed physical model of moraine foundation to obtain the corresponding construction simulation parameters; Based on the comparison of the obtained construction simulation parameters with the actual construction process parameters, a corresponding parameter comparison table is obtained; Based on the obtained parameter comparison table, the compaction effect of the dynamic compaction construction process on moraine soil was evaluated.

2. The method for evaluating the compaction effect of moraine soil based on dynamic compaction method according to claim 1, characterized in that: The process of constructing a physical model of moraine foundation includes: Moraine soil was selected as the sample, and the particle composition of the moraine soil was determined by particle sieving method. The particles were flattened to obtain the particle gradation data. By vertically photographing the tiled particles, the two-dimensional image of each particle is determined, and the particle edge morphology is extracted; According to the obtained edge morphological characteristics, the morphological characteristics of the particles are obtained; Based on the obtained particle morphology, the particle failure load is obtained through the discrete element numerical model; Then, the particles are subjected to particle strength analysis to obtain corresponding particle strength indexes; According to the particle gradation data of moraine soil, the corresponding alternative materials are selected, and the obtained alternative materials are mixed and configured to obtain the corresponding test materials; A model box is constructed, and the obtained test materials are filled into the model box in layers. At the same time, corresponding sensors are arranged to complete the construction of the physical model of the moraine foundation.

3. The method for evaluating the compaction effect of moraine soil based on dynamic compaction method according to claim 2, characterized in that: The particle gradation data is the proportion of particles in different particle size ranges in the sample.

4. The method for evaluating the compaction effect of moraine soil based on dynamic compaction method according to claim 3, characterized in that: The process of obtaining the particle failure load of particles through the discrete element numerical model is as follows: Apply external force or displacement boundary conditions to each obtained particle, and obtain the motion equation of each particle through implicit time integration method, and then update the position and velocity of the particle; According to the obtained motion equations of each particle and the changes in particle position and velocity, the actual stress conditions are simulated to obtain the particle failure load corresponding to each particle.

5. The method for evaluating the compaction effect of moraine soil based on dynamic compaction method according to claim 4, characterized in that: The dynamic compaction construction process is simulated based on the constructed moraine foundation physical model. The process of obtaining the corresponding construction simulation parameters includes: Set model rammers of different weights, and set high and low rammer drop points; The construction simulation parameters are generated by setting different model rammers at different landing points; The construction simulation parameters include the number of tamping times, the landing height of each tamping, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping; Based on the obtained construction simulation parameters, the actual construction parameters are called to generate the corresponding parameter comparison table.

6. The method for evaluating the compaction effect of moraine soil based on dynamic compaction according to claim 5, characterized in that: Obtain the corresponding similarity coefficient according to the landing point height, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping of the construction simulation parameters and the landing point height, the tamping energy corresponding to each tamping, and the effective reinforcement depth corresponding to each tamping of the actual construction parameters; A mechanical property prediction model of particle characteristics is constructed based on the obtained similarity coefficients.

7. The method for evaluating the compaction effect of moraine soil based on dynamic compaction according to claim 6, characterized in that: The process of constructing a mechanical property prediction model for particle characteristics includes: Obtaining the stress exerted on each sensor arranged in the model box during each tamping, and obtaining the corresponding radial strain field and vertical strain field based on the obtained stress exerted on each sensor; At the same time, the displacement field of the soil at different time points and the displacement data of each position during each tamping are obtained through the image acquisition device; Then the local volume strain field corresponding to the soil is obtained; Summarize the data obtained from each tamping, use the data summarized from each tamping as sample data, and divide the sample data into a training set and a test set; Constructing a multiple regression analysis model, inputting the obtained training set into the constructed multiple regression analysis model to train the multiple regression analysis model, and completing the training of all sample data in the training set; The training results of each training are then evaluated using the test set. If the evaluation results meet expectations, the training is terminated. If the evaluation results do not meet expectations, a second round of training is carried out, and so on, until the evaluation results meet expectations or the number of training times reaches the preset upper limit.

8. The method for evaluating the compaction effect of moraine soil based on dynamic compaction according to claim 7, characterized in that: The process of evaluating the compaction effect of dynamic compaction on moraine soil based on the obtained parameter comparison table includes: Acquire real-time construction parameters corresponding to the dynamic compaction construction process, wherein the real-time construction parameters include tamping hammer parameters, number of tamping blows, landing point height corresponding to each tamping blow, and effective reinforcement depth corresponding to each tamping blow; The parameters of the rammer include weight and diameter; The obtained real-time construction parameters are input into the trained multiple regression analysis model, and the corresponding compaction prediction evaluation results are output in combination with the obtained similarity coefficients corresponding to the parameter comparison table.

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