Rebound modulus prediction model, method and model construction method of MICP modified expansive soil

Abstract

The present invention proposes a model, method, and model construction method for estimating the modulus of resilience of MICP-modified expansive soil. The model constructed by the present method comprehensively considers the effects of the number of MICP treatments, maximum dry density, optimal moisture content, plasticity index, CBR, free expansion rate, expansion force, cohesion, internal friction angle, confining pressure, and deviatoric stress. Furthermore, the model has clear physical meaning and a simple structure. The required parameters can be obtained simply through a series of basic indoor tests, greatly reducing experimental time and difficulty. This provides significant engineering benefits for organizations lacking triaxial testing conditions and has high market value. Compared with existing methods, the model and method of the present invention can conveniently and accurately obtain the modulus of resilience of MICP-modified expansive soil under different conditions, more conveniently guiding the design and construction of MICP-modified expansive soil in road structures.

Description

Technical Field

[0001] The present invention belongs to the technical field of road engineering and relates to a rebound modulus estimation model and method for MICP modified expansive soil and a model construction method. Background Art

[0002] Expansive soil is widely distributed in the humid and hot regions of southern my country. With the rapid development of transportation infrastructure in this region, the use of expansive soil as roadbed filler in areas with scarce road construction materials is inevitable. However, expansive soil is a typical special clay soil with fissures and dilatation-contraction properties. Under the influence of natural factors, it is highly susceptible to water expansion and water loss contraction, which can lead to reduced bearing capacity, increased deformation, and structural damage in the roadbed. Therefore, the effective improvement of this special soil, expansive soil, has become a hot topic of widespread concern among scholars both domestically and internationally. Currently, the improvement methods for expansive soil generally include replacement, physical modification, chemical modification, and biological modification. Because traditional modification methods are labor-intensive, long construction periods, high project costs, and have certain environmental pollution issues, biological modification methods are gaining increasing attention. The microbially induced carbonate precipitation (MICP) method is a very promising method for the microbial improvement of roadbed expansive soil.

[0003] The rebound modulus is an important mechanical indicator that characterizes the stiffness characteristics of the roadbed. It is defined as the ratio of the stress generated by the material under load to its corresponding elastic strain. Currently, there are three commonly used methods for determining the rebound modulus: the first is the empirical method, but the recommended rebound modulus values given vary widely, making quantitative analysis impossible. The second method is to calculate the rebound modulus value of the roadbed based on the CBR and rebound modulus empirical formula, but its applicability is questionable. The third method is to conduct indoor triaxial tests to determine the rebound modulus value, but triaxial tests are expensive, time-consuming, require professional personnel to operate, and are difficult to promote. In view of this, it is necessary to establish a simple but effective method for quickly estimating the rebound modulus of MICP-modified expansive soil, so as to quickly determine the rebound modulus of MICP-modified expansive soil. Summary of the Invention

[0004] Based on the problems existing in the prior art, the present invention proposes a method for constructing a rebound modulus prediction model for MICP-modified expansive soil, which includes the following steps:

[0005] A: Expansive soil was subjected to MICP modification treatments 0, 1, 3, 6, and 10 times, and then cured for 12 days. After curing, the soil was subjected to compaction tests, critical moisture content tests, CBR tests, free expansion rate tests, expansion force tests, and shear tests, respectively. The maximum dry density, optimal moisture content, liquid limit, plastic limit, plasticity index, CBR, free expansion rate, expansion force, cohesion, and internal friction angle of the expansive soil after different MICP modification times were obtained.

[0006] B: Conduct a rebound modulus test to determine the dynamic rebound modulus of the modified expansive soil under different MICP modification treatment times;

[0007] C: The rebound modulus data were fitted using the NCHRP 1-28A three-parameter model to obtain the k1, k2, k3 and R under different MICP modification times. 2 ;

[0008] D: Based on step A, the performance parameters of the MICP-modified expansive soil are obtained, and the contribution ratios of the above performance parameters to the three model parameters k1, k2, and k3 of the NCHRP 1-28A model are determined using the Bootstrap forest method in JMP statistical software. Then, a stepwise multiple regression analysis method is used to detect the correlation between the model parameters (k1, k2, and k3) and each performance parameter, thereby obtaining the model parameters k1, k2, and k3 in the rapid prediction model of the resilient modulus of expansive soil considering the number of MICP modifications.

[0009] E: Substitute the model parameters k1, k2, and k3 obtained in step D into the NCHRP 1-28A three-parameter model to obtain the rebound modulus estimation model of MICP-modified expansive soil.

[0010] The NCHRP 1-28A three-parameter model is as follows:

[0011]

[0012] Among them, E y Indicates the axial (specimen loading direction) rebound modulus; θ bs represents the body stress, or the first invariant of the stress tensor, which is the algebraic sum of the three principal stresses; τ oct represents the octahedral shear stress; P a is the reference atmospheric pressure; k1, k2 and k3 are model parameters.

[0013] Because different bacteria produce different results when modifying expansive soil, to make the model more accurate, in specific applications, the model can be used to predict the resilience modulus of expansive soil modified with MICP using the same bacteria used in the model. In other words, the above technical solution can generate a prediction model specific to a specific modified bacteria.

[0014] Based on the above technical solution, the present application provides a modification method for a specific modified bacteria, thereby obtaining a model construction method for this bacteria and a model constructed by this method.

[0015] Specifically, the MICP modification treatment method is as follows:

[0016] The CaCl2 solution is evenly added to the expansive soil and air-dried. Then, a microbial solution (Bacillus pastoris) with an absorbance of OD600 = 1 is evenly sprayed on the treated expansive soil, allowing the soil to fully react with the urease hydrolyzate in the Bacillus pastoris metabolites, thereby completing the mineralization process during the MICP modification process. Finally, the MICP-treated expansive soil sample is placed under natural conditions to air-dry and appropriately crushed. The above process is a single MICP modification process. The amount of bacterial solution added is selected to be equivalent to the optimal water content.

[0017] Based on the MICP modification treatment of Bacillus subtilis, this application provides a dedicated estimation model as follows:

[0018]

[0019] Among them, E y Indicates the axial (specimen loading direction) rebound modulus; θ bs represents the body stress, or the first invariant of the stress tensor, which is the algebraic sum of the three principal stresses; τ oct represents the octahedral shear stress; P a is the reference atmospheric pressure; k1, k2 and k3 are model parameters, specifically:

[0020] k1=0.067[(95.515ρ dmax 2 -64.307ρ dmax -93.524)-28.655I p -38.795

[0021] +(4.369ln(e+CBR)-93.524)+(2.131R fs -93.524)]

[0022] k2=1.748+0.025ω omc+0.047CBR-0.004F e -0.019c

[0023]

[0024] Where, ρ dmax is the maximum dry density, ω OMC is the optimal moisture content, I P is the plasticity index, CBR is the California bearing ratio, R fs is the free expansion rate, F e is the expansion force, c is the cohesive force, is the internal friction angle.

[0025] In the method for quickly estimating the rebound modulus of MICP modified expansive soil using the above-mentioned model of the present application, the maximum dry density ρ obtained by actual measurement is input into the model. dmax , optimal moisture contentω OMC , is the plasticity index I P , California load ratio CBR, free expansion rate R fs , expansion force F e , cohesion c, internal friction angle The estimated elastic modulus of expansive soil can be obtained.

[0026] In addition to the method for constructing a model for quickly estimating the rebound modulus of MICP-modified expansive soil, the model, and the method for quickly estimating the rebound modulus of MICP-modified expansive soil using the model, the present application also provides a server, specifically comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to quickly estimate the rebound modulus of MICP-modified expansive soil. During the estimation, the maximum dry density ρ obtained by actual measurement is respectively input into the model stored in the server. dmax , optimal moisture contentω OMC , is the plasticity index I P , California load ratio CBR, free expansion rate R fs , expansion force F e , cohesion c, internal friction angle The estimated elastic modulus of expansive soil can be obtained.

[0027] The present application also provides a computer-readable storage medium, which stores a computer program, characterized in that when the computer program is executed by a processor, it can achieve rapid estimation of the rebound modulus of MICP-modified expansive soil.

[0028] The beneficial effects of the present invention are:

[0029] The present invention discloses a method for constructing a model for estimating the modulus of resilience of MICP-modified expansive soil and an estimation model constructed by the method, which comprehensively considers the effects of the number of MICP treatments, maximum dry density, optimum moisture content, plasticity index, CBR, free expansion rate, expansion force, cohesion, internal friction angle, confining pressure, and deviatoric stress. Furthermore, the model has clear physical meaning and a simple structure, and the required parameters can be obtained only through a series of indoor basic tests, greatly reducing the time and difficulty of the test. This provides significant engineering convenience for units that do not have triaxial test conditions and has high market promotion value. Furthermore, compared with existing methods, the model and method of the present invention can conveniently and accurately obtain the modulus of resilience of MICP-modified expansive soil under different conditions, more conveniently guiding the design and construction of MICP-modified expansive soil in road structures, and can be extended to the design and testing of other similar materials, thus having broad application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 : These are the experimental results of expansive soil corresponding to different MICP modification treatment times in Example 2 of the present invention; wherein (a) is a graph showing the compaction test results corresponding to different MICP modification treatment times; (b) is a graph showing the limit moisture content test results corresponding to different MICP modification treatment times; (c) is a graph showing the CBR test results corresponding to different MICP modification treatment times; (d) is a graph showing the free expansion rate test results corresponding to different MICP modification treatment times; (e) is a graph showing the expansion force test results corresponding to different MICP modification treatment times; and (f) is a graph showing the shear test results corresponding to different MICP modification treatment times.

[0031] Figure 2 : The dynamic rebound modulus curves corresponding to different MICP modification treatment times in Example 2; wherein (a) is a dynamic rebound modulus curve corresponding to 0 MICP modification treatment times; (b) is a dynamic rebound modulus curve corresponding to 1 MICP modification treatment times; (c) is a dynamic rebound modulus curve corresponding to 3 MICP modification treatment times; (d) is a dynamic rebound modulus curve corresponding to 6 MICP modification treatment times; (e) is a dynamic rebound modulus curve corresponding to 10 MICP modification treatment times;

[0032] Figure 3 Schematic diagram of the contribution ratio of each performance parameter to the model parameters in Example 2; wherein (a) is a schematic diagram of the contribution ratio of each performance parameter to k1; (b) is a schematic diagram of the contribution ratio of each performance parameter to k2; (c) is a schematic diagram of the contribution ratio of each performance parameter to k3;

[0033] Figure 4 This is a diagram of the robustness verification results of the model built by the present invention. DETAILED DESCRIPTION

[0034] Example 1

[0035] The present application provides a method for constructing a model for estimating the elastic modulus of MICP-modified expansive soil, comprising the following steps:

[0036] A: The expansive soil was subjected to MICP modification treatments 0, 1, 3, 6, and 10 times, and the modified expansive soil was cured for 12 days. After curing, the soil was subjected to compaction tests, critical moisture content tests, CBR tests, free expansion rate tests, expansion force tests, and shear tests (specifically, all of the above tests were conducted in accordance with the "Highway Geotechnical Test Code" (JTG3430-2020)). The maximum dry density, optimal moisture content, liquid limit, plastic limit, plasticity index, CBR, free expansion rate, expansion force, cohesion, and internal friction angle of the expansive soil after different MICP modification times were obtained.

[0037] B: Conduct a rebound modulus test to determine the dynamic rebound modulus of modified expansive soil under different MICP modification treatment times; specifically, the rebound modulus test uses the loading sequence recommended in the specification JTG 3430-2020

[0038] C: The NCHRP 1-28A three-parameter model recommended in the AASHTO-2002 standard was used to fit the rebound modulus data, and the k1, k2, k3 and R under different MICP modification treatment times were obtained. 2 ;

[0039] D: Based on step A, the performance parameters of the MICP-modified expansive soil are obtained, and the contribution ratios of the above performance parameters to the three model parameters k1, k2, and k3 of the NCHRP 1-28A model are determined using the Bootstrap forest method in JMP statistical software. Then, a stepwise multiple regression analysis method is used to detect the correlation between the model parameters (k1, k2, and k3) and each performance parameter, thereby obtaining the model parameters k1, k2, and k3 in the rapid prediction model of the resilient modulus of expansive soil considering the number of MICP modifications.

[0040] E: Substitute the model parameters k1, k2, and k3 obtained in step D into the NCHRP 1-28A three-parameter model to obtain the rebound modulus estimation model of MICP-modified expansive soil.

[0041] Specifically, the NCHRP 1-28A three-parameter model is as follows:

[0042]

[0043] Among them, E y Indicates the axial (specimen loading direction) rebound modulus; θbs represents the body stress, or the first invariant of the stress tensor, which is the algebraic sum of the three principal stresses; τ oct represents the octahedral shear stress; P a is the reference atmospheric pressure; k1, k2 and k3 are model parameters.

[0044] The model constructed using the above method can be used to quickly estimate the rebound modulus of MICP-modified expansive soil.

[0045] Example 2

[0046] Based on Example 1, the present invention provides a method for constructing a rapid estimation model of the rebound modulus of expansive soil modified by MICP using a specific bacteria, comprising the following steps:

[0047] Step a: Add CaCl2 solution evenly to the expansive soil and air-dry it (the concentration of the CaCl2 solution in this embodiment is 2 mol / L); then, use a Bacillus pasteurii solution with an absorbance of OD600 = 1 (the Bacillus pasteurii used in this embodiment, also known as pasteurii spore Sarcina, was purchased from the China General Culture Collection Management Center (CGMCC) and is numbered ATCC11859.) to evenly spray the treated expansive soil so that the expansive soil can fully react with the urease hydrolyzate in the Bacillus pasteurii metabolite and complete the mineralization process in the MICP modification process; finally, the expansive soil sample that has been modified by MICP is placed under natural conditions to air dry and crush. The above process is a one-time MICP modification process. Among them, the amount of bacterial solution added is selected to be equivalent to the optimal water content.

[0048] Step b: The expansive soil is subjected to MICP modification treatment for 0, 1, 3, 6, and 10 times, and the MICP modified expansive soil that has been treated for the preset number of times is placed in a constant temperature and moisture-keeping cylinder at 25°C for 12 days of curing. After the curing is completed, based on the specification "Highway Geotechnical Test Code" (JTG 3430-2020), indoor basic tests such as compaction test, limit moisture content test, CBR test, free expansion rate test, expansion force test, and shear test are carried out. The results of compaction test, limit moisture content test, CBR test, free expansion rate test, expansion force test and shear test with different MICP modification treatment times (0, 1, 3, 6, 10) are shown as follows: Figure 1 shown.

[0049] Step c: The loading sequence recommended in the specification JTG 3430-2020 (Table T0194-2, as shown in Table 1) was used to conduct the rebound modulus test, and then the dynamic rebound modulus of the modified expansive soil under different MICP modification times (0, 1, 3, 6, 10) was measured. The results are shown in Figure 2. Figure 2On this basis, the NCHRP 1-28A three-parameter model (as shown in Equation 1) recommended in the AASHTO-2002 standard was used to fit the rebound modulus data, and the results are shown in Table 2.

[0050]

[0051] Where, E y Indicates the axial (specimen loading direction) rebound modulus; θ bs represents the body stress, or the first invariant of the stress tensor, which is the algebraic sum of the three principal stresses; τ oct represents the octahedral shear stress; P a is the reference atmospheric pressure; k1, k2 and k3 are model parameters.

[0052] Table 1 Loading sequence

[0053]

[0054] Table 2 Model parameter statistics

[0055]

[0056] Then, the performance parameters of the MICP modified expansive soil were obtained based on step b, and the contribution ratios of the above performance parameters to the three model parameters k1, k2, and k3 of the NCHRP 1-28A model were obtained by the Bootstrap forest method model in the JMP statistical software, as shown in Fig. Figure 4 Then, the stepwise multiple regression analysis method was used to detect the correlation between the model parameters (k1, k2 and k3) and the performance parameters, thereby obtaining a rapid prediction formula for the elastic modulus of expansive soil considering the number of MICP modification, as shown in formulas (2)-(4):

[0057]

[0058] k2=1.748+0.025ω omc +0.047CBR-0.004F e -0.019c (Equation 3)

[0059]

[0060] Where, ρ dmax is the maximum dry density, ω OMC is the optimal moisture content, I P is the plasticity index, CBR is the California bearing ratio, R fs is the free expansion rate, F e is the expansion force, c is the cohesive force, is the internal friction angle.

[0061] The above formula 1-4 is a rapid estimation model for the rebound modulus of Bacillus pastoris MICP-modified expansive soil constructed in this embodiment. This model can be used to quickly estimate the rebound modulus of the same type of Bacillus pastoris MICP-modified expansive soil. When estimating, it is only necessary to measure the maximum dry density ρ in the room. dmax , optimal moisture contentω OMC , is the plasticity index I P , California load ratio CBR, free expansion rate R fs , expansion force F e , cohesion c, internal friction angle The estimated elastic modulus of expansive soil can be obtained by the basic performance parameters such as α, β and β.

[0062] In addition, through Figure 1 and Figure 2 It can be seen that with the increase of the number of MICP modification, the bearing capacity of the modified expansive soil increases (CBR increases), the expansion performance weakens (free expansion rate and expansion rate decrease), and the stiffness performance increases (rebound modulus increases).

[0063] In order to determine the accuracy and applicability of the rapid estimation model of the rebound modulus of Bacillus pasteurianus MICP modified expansive soil constructed in this embodiment, the rebound modulus data of the working conditions shown in Table 3 were used to verify the robustness of models (1-4). Among them, a scatter plot was drawn with the measured value of the rebound modulus as the horizontal axis and the estimated value as the vertical axis. The results are shown in Figure 3. Figure 4 As shown. It can be seen that most of the scattered points are concentrated around the straight line y=x, R 2 =0.94, which shows a good fitting effect. Therefore, the estimated value of the elastic modulus obtained by the model constructed in this embodiment is highly representative and meets engineering needs.

[0064] Table 3 Robustness verification loading sequence

[0065]

[0066]

[0067] 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 above in terms of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can, without departing from the scope of the technical solution of the present invention, make some changes or modifications to equivalent embodiments using the technical contents disclosed above. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A method for constructing a model for estimating the rebound modulus of MICP-modified expansive soil, characterized in that: The steps include: A: The expansive soil was subjected to MICP modification treatments for 0, 1, 3, 6, and 10 times, and the MICP-modified expansive soil was cured for 12 days; After curing, compaction test, limit moisture content test, CBR test, free expansion rate test, expansion force test, and shear test were carried out to obtain the maximum dry density, optimum moisture content, liquid limit, plastic limit, plasticity index, CBR, free expansion rate, expansion force, cohesion, and internal friction angle of the expansive soil after different MICP modification times. B: Conduct a rebound modulus test to determine the dynamic rebound modulus of the modified expansive soil under different MICP modification treatment times; C: The rebound modulus data were fitted using the NCHRP 1-28A three-parameter model to obtain k1, k2, and k3 under different MICP modification treatment times; D: Based on step A, the performance parameters of the MICP-modified expansive soil were obtained. The contribution ratios of these performance parameters to the three model parameters k1, k2, and k3 of the NCHRP 1-28A model were determined using the Bootstrap forest method in JMP statistical software. Then, the correlation between the model parameters k1, k2, and k3 and each performance parameter was tested using stepwise multiple regression analysis to obtain the model parameters k1, k2, and k3 in the rapid prediction model for the resilient modulus of expansive soil considering the number of MICP modifications. Specifically: k1=0.067[(95.515ρ dmax 2 -64.307r dmax -93.524)-28.655I p -38.795 +(4.369ln(e+CBR)-93.524)+(2.131R fs -93,524)] k2=1.748+0.025ω omc +0.047CBR-0.004F e -0.019c Where, ρ dmax is the maximum dry density, ω OMC is the optimal moisture content, I P is the plasticity index, CBR is the California bearing ratio, R fs is the free expansion rate, F e is the expansion force, c is the cohesive force, is the internal friction angle; E: Substitute the model parameters k1, k2, and k3 obtained in step D into the NCHRP 1-28A three-parameter model to obtain the rebound modulus estimation model of MICP-modified expansive soil.

2. The method for constructing a rebound modulus estimation model for MICP modified expansive soil according to claim 1, wherein The NCHRP 1-28A three-parameter model is as follows: Among them, E y Indicates the axial rebound modulus of the specimen in the loading direction; θ bs represents the body stress, or the first invariant of the stress tensor, which is the algebraic sum of the three principal stresses; τ oct represents the octahedral shear stress; P a is the reference atmospheric pressure; k1, k2 and k3 are model parameters.

3. The method for constructing a rebound modulus estimation model for MICP modified expansive soil according to claim 1, wherein The method of MICP modification treatment in step A is as follows: The CaCl2 solution is evenly added to the expansive soil and air-dried; then, the treated expansive soil is evenly sprayed with a Bacillus pastoris bacterial solution with an absorbance of OD600=1, so that the expansive soil can fully react with the urease hydrolyzate in the Bacillus pastoris metabolites and thus complete the mineralization effect in the MICP modification process; finally, the expansive soil sample that has been MICP-modified is placed under natural conditions for air drying and appropriately crushed; wherein, the above process is a one-time MICP modification process; wherein, the amount of bacterial solution added is selected to be equivalent to the optimal water content.

4. The elastic modulus estimation model of MICP modified expansive soil constructed by the method of claim 1 or 2.

5. The resilience modulus estimation model of MICP modified expansive soil constructed by the method according to claim 3 is characterized in that: The estimation model is as follows: Among them, E y Indicates the axial rebound modulus of the specimen in the loading direction; θ bs represents the body stress, or the first invariant of the stress tensor, which is the algebraic sum of the three principal stresses; τ oct represents the octahedral shear stress; P a is the reference atmospheric pressure; k1, k2 and k3 are model parameters, specifically: k1=0.067[(95.515ρ dmax 2 -64.307r dmax -93.524)-28.655I p -38.795 +(4.369ln(e+CBR)-93.524)+(2.131R fs -93,524)] k2=1.748+0.025ω omc +0.047CBR-0.004F e -0.019c Where, ρ dmax is the maximum dry density, ω OMC is the optimal moisture content, I P is the plasticity index, CBR is the California bearing ratio, R fs is the free expansion rate, F e is the expansion force, c is the cohesive force, is the internal friction angle.

6. A method for estimating the modulus of resilience of MICP-modified expansive soil, characterized in that: Use the prediction model of claim 4 or 5.

7. The method for estimating the modulus of resilience of MICP-modified expansive soil according to claim 6, wherein: When estimating, the maximum dry density ρ obtained by actual measurement is input into the model. dmax , optimal moisture contentω OMC , is the plasticity index I P , California load ratio CBR, free expansion rate R fs , expansion force F e , cohesion c, internal friction angle The estimated elastic modulus of expansive soil can be obtained.

8. A server comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: The processor implements the method steps of claim 7 when executing the computer program.

9. A computer-readable storage medium storing a computer program, characterized in that: The computer program implements the method steps of claim 7 when executed by a processor.

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