Method for determining maintenance time of geopolymer improved soil subgrade based on damage self-repairing rate

Abstract

The application discloses a geopolymer improved soil subgrade maintenance time determination method based on damage self-repairing rate, which comprises the following steps: establishing a prediction model of unconfined compressive strength and elastic modulus of improved soil under different maintenance times; establishing a finite element mechanics simulation model of improved soil subgrade considering overlying base construction, and determining micro-damage stress level of the improved soil subgrade caused by construction machinery under different maintenance times; designing a pre-micro-damage dynamic triaxial test, and establishing a prediction model of unconfined compressive strength and elastic modulus of improved soil after pre-micro-damage under different maintenance times; introducing damage self-repairing rate, determining the maintenance time of improved soil before pre-micro-damage which meets the self-repairing requirements of unconfined compressive strength and elastic modulus, and taking the larger value of the two maintenance times as the final maintenance time of the improved soil. The application obtains the maintenance time before pre-micro-damage which meets the micro-damage self-repairing rate requirements, meets the construction bearing requirements, improves the construction efficiency, and is simple to operate and scientific and reasonable.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of subgrade construction and relates to a method for determining maintenance time of geopolymer improved soil subgrade based on damage self-repairing rate. BACKGROUND

[0002] Traditional materials such as lime and cement are usually used in the construction of existing improved soil subgrade. These materials usually need to be maintained for 7 days after construction to ensure that the improved soil subgrade reaches a certain bearing capacity, so as to meet the requirements of subsequent semi-rigid base construction. However, if the maintenance time is too short, the bearing capacity of the improved soil subgrade is insufficient, and when the semi-rigid base construction is carried out on the upper layer, it will cause micro-damage to the improved soil subgrade, which will affect the development of the unconfined compressive strength and elastic modulus of the subgrade and further damage the subgrade. On the contrary, if the maintenance time is too long, it will affect the progress of the project and delay the construction period. Geopolymer materials have a faster development speed of unconfined compressive strength, and compared with lime and cement materials, they can make the improved soil subgrade reach the bearing capacity required for semi-rigid base construction in a shorter time. The present application takes 7d (168h) as the standard maintenance time, which corresponds to the final unconfined compressive strength and elastic modulus of the improved soil.

[0003] When geopolymer materials are used to improve the subgrade soil, the existing method is to refer to the lime and cement improved soil and take 7 days as the maintenance time. However, geopolymer materials have early strength effect, and 7 days of maintenance time is no longer applicable. Therefore, it is necessary to find a maintenance time that ensures that the progress of the project is not delayed and the unconfined compressive strength of the subgrade is not damaged during the base construction. SUMMARY

[0004] In order to solve the above problems, the present application provides a method for determining the maintenance time of geopolymer improved soil subgrade based on damage self-repairing rate, which obtains the maintenance time before pre-adding micro-damage that meets the requirements of micro-damage self-repairing rate, meets the construction bearing requirements while improving the construction efficiency, is simple to operate, and is scientific and reasonable.

[0005] The technical solution adopted by the present application is a method for determining the maintenance time of geopolymer improved soil subgrade based on damage self-repairing rate, which comprises the following steps:

[0006] Step 1: Determine the geopolymer dosage a and the volumetric porosity of the improved soil based on the engineering improvement scheme, and substitute the geopolymer dosage a, the volumetric porosity of the improved soil and the standard maintenance time into the improved soil unconfined compressive strength prediction model and the improved soil elastic modulus prediction model with maintenance time, volumetric porosity and geopolymer dosage as variables, see formula (1) and formula (2), to obtain the final unconfined compressive strength and elastic modulus of the improved soil without pre-adding micro-damage, respectively;

[0007]

[0008] In the formula: a0, b0, c1, d1, e1, f1, c2, d2, e2 and f2 are constant coefficients; E is the elastic modulus of the improved soil; UCS is the unconfined compressive strength of the improved soil; t is the curing time; a is the geopolymer content; and η is the volume porosity of the improved soil.

[0009] Step 2, the final unconfined compressive strength and elastic modulus of the improved soil without pre-damage are multiplied by the micro-damage self-repairing rate, to obtain the unconfined compressive strength and elastic modulus of the improved soil after pre-damage micro-damage and meeting the self-repairing rate requirement;

[0010] Step 3, the unconfined compressive strength and elastic modulus of the improved soil after pre-damage micro-damage and meeting the self-repairing rate requirement obtained in step 2 are substituted into the prediction models of the final unconfined compressive strength and elastic modulus of the improved soil after pre-damage micro-damage with respect to the curing time before pre-damage micro-damage, see formula (3) and (4):

[0011] UCS' = a'ln(t') + b' (3)

[0012] E' = c'ln(t') + d' (4)

[0013] In the formula: a', b', c' and d' are constant coefficients; UCS' is the final unconfined compressive strength of the improved soil after pre-damage micro-damage; E' is the final elastic modulus of the improved soil after pre-damage micro-damage; and t' is the curing time of the improved soil before pre-damage micro-damage;

[0014] Thus, the curing time before pre-damage micro-damage is obtained, and the larger value of the two curing times is taken as the final curing time of the improved soil.

[0015] Further, the method for determining the unconfined compressive strength prediction model and the elastic modulus prediction model of the improved soil with the curing time, the volume porosity and the geopolymer content as variables in step 1 comprises the following steps:

[0016] Step 11, preparing geopolymer, obtaining the unconfined compressive strength at different curing times through experiments, based on the corresponding relationship between the unconfined compressive strength of the geopolymer and the curing time, and through a data programming solving method, selecting the form with the highest fitting degree, and establishing a prediction model of the unconfined compressive strength of the geopolymer with respect to the curing time;

[0017] Step 12, preparing improved soil test pieces with different geopolymer contents, obtaining the volume porosity of the improved soil test pieces and the unconfined compressive strength and elastic modulus of the improved soil test pieces at different curing times through experiments;

[0018] Step 13, based on the influence law of the curing time, the volume porosity and the geopolymer content of the modified soil sample on the unconfined compressive strength of the modified soil sample, a prediction model form conforming to the influence law is obtained through multiple linear regression combined with artificial neural network algorithm, and then the geopolymer unconfined compressive strength prediction model obtained in step 11 is coupled, so as to establish a modified soil unconfined compressive strength prediction model taking the curing time, the volume porosity and the geopolymer content as variables;

[0019] Based on the influence law of the curing time, the volume porosity and the geopolymer content of the modified soil sample on the elastic modulus of the modified soil sample, a prediction model form conforming to the influence law is obtained through multiple linear regression combined with artificial neural network algorithm, and then the geopolymer unconfined compressive strength prediction model obtained in step 11 is coupled, so as to establish a modified soil elastic modulus prediction model taking the curing time, the volume porosity and the geopolymer content as variables.

[0020] Further, in step 11, the prediction model of the geopolymer unconfined compressive strength with respect to the curing time is:

[0021] s=a0 ln(t)+b0

[0022] In the formula, a0 and b0 are constant coefficients, and s is the geopolymer unconfined compressive strength, and t is the curing time.

[0023] Further, in step 11, the determination method of the constant coefficient is:

[0024] Based on the measured geopolymer unconfined compressive strength, the coefficients are obtained according to the least square method when the fitting error is the smallest according to the prediction model form, so that:

[0025] s=13.942 ln(t)-37.630

[0026] In the formula, t is the curing time.

[0027] Further, in step 1, the determination method of the constant coefficient is: based on the measured modified soil unconfined compressive strength, the coefficients are obtained according to the least square method when the fitting error is the smallest according to the prediction model formula (1), so that:

[0028]

[0029] Based on the measured modified soil elastic modulus, the coefficients are obtained according to the least square method when the fitting error is the smallest according to the prediction model formula (2), so that:

[0030]

[0031] In the formula, t is the curing time.

[0032] Further, in step 2, the micro-damage self-repairing rate is determined according to the highway grade, wherein the micro-damage self-repairing rate of expressway or first-class highway is 80%, the micro-damage self-repairing rate of second-class highway is 70%, and the micro-damage self-repairing rate of third-class or fourth-class highway is 60%.

[0033] Further, in step 3, the method for determining the prediction model of the ultimate unconfined compressive strength and elastic modulus of the improved soil after the pre-added micro-damage with respect to the curing time before the pre-added micro-damage comprises the following steps:

[0034] Step 31, a finite element mechanics simulation model of the improved soil subgrade considering the construction of the overlying base layer is established in the ABAQUS finite element calculation software, the predicted elastic modulus of the improved soil under different curing times is input, the self-weight load of the base layer and the force of the mechanical compaction on the improved soil subgrade during the construction of the base layer are input according to the construction method of the semi-rigid base layer, and the maximum vertical stress response σ1 and the lateral confining pressure stress σ3 generated in the improved soil subgrade during the construction of the semi-rigid base layer are calculated by using the ABAQUS finite element calculation software;

[0035] Step 32, the maximum vertical stress response σ1 and the lateral confining pressure stress σ3 calculated in step 31 are taken as the pre-added micro-damage stress level, the pre-added micro-damage duration and frequency are converted according to the construction method of the semi-rigid base layer, the pre-added micro-damage dynamic triaxial test of the improved soil is carried out after different curing times, and then the curing is continued to the standard curing time; the ultimate unconfined compressive strength and elastic modulus of the improved soil after the pre-added micro-damage under different curing times before the pre-added micro-damage are obtained through the experiment; based on the corresponding relationship between the ultimate unconfined compressive strength and elastic modulus of the improved soil after the pre-added micro-damage and the curing time before the pre-added micro-damage, the prediction model of the ultimate unconfined compressive strength and elastic modulus of the improved soil after the pre-added micro-damage with respect to the curing time before the pre-added micro-damage is established by using the data planning solution method and selecting the form with the highest fitting degree.

[0036] Further, in step 3, the method for determining the constant coefficient comprises the following steps: based on the measured unconfined compressive strength of the improved soil after the pre-added micro-damage, the coefficient is obtained according to the least square method when the fitting error is the smallest according to the form of the prediction model formula (3), so that:

[0037] UCS′=0.941ln(t′)-2.766

[0038] Based on the measured elastic modulus of the improved soil after the pre-added micro-damage, the coefficient is obtained according to the least square method when the fitting error is the smallest according to the form of the prediction model formula (4), so that:

[0039] E′=236.770ln(t ′ )-410.810

[0040] In the formula, t' is the curing time before the modified soil is pre-damaged.

[0041] The beneficial effects of the present application are:

[0042] The present application determines the shortest curing time that can meet the requirements of the construction bearing capacity of semi-rigid base and ensure the long-term performance stability of the roadbed by analyzing the unconfined compressive strength and stiffness variation of the geopolymer modified soil roadbed with and without pre-damage at different curing times, and combining with the actual engineering requirements.

[0043] The present application forms the unconfined compressive strength and elastic modulus prediction model of the modified soil by fitting a large number of test results of the geopolymer content, curing time, modified soil porosity, and unconfined compressive strength of geopolymer, wherein the unconfined compressive strength prediction model of geopolymer is coupled, the influence of the development trend of the unconfined compressive strength of the cementitious material in the modified soil is considered, and the porosity and geopolymer content are equivalent to considering the influence of the soil sample itself and the influence of the composition ratio of the soil sample and geopolymer in the modified soil. The present application can scientifically and reasonably determine the curing time of the geopolymer modified soil roadbed, fill the technical gap, improve the construction efficiency, adopt the double-control indexes of the unconfined compressive strength and stiffness (elastic modulus) damage self-repairing rate, and ensure the quality and long-term stability of the modified soil roadbed. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0045] Figure 1 is the curing time determination method flowchart in the embodiments of the present application.

[0046] Figure 2 is the geopolymer unconfined compressive strength prediction model in the embodiments of the present application.

[0047] Figure 3 is the fitting result of the modified soil unconfined compressive strength prediction model in the embodiments of the present application.

[0048] Figure 4 is the fitting result of the modified soil elastic modulus prediction model in the embodiments of the present application.

[0049] Figure 5 is the base construction load action model in the embodiments of the present application.

[0050] Figure 6 is the finite element calculation stress output result in the embodiments of the present application.

[0051] Figure 7 is a schematic diagram of a pre-damage triaxial test in an embodiment of the present application.

[0052] Figure 8 is a final unconfined compressive strength prediction model of the pre-damage improved soil in an embodiment of the present application.

[0053] Figure 9 is a final elastic modulus prediction model of the pre-damage improved soil in an embodiment of the present application.

[0054] Figure 10 is a geopolymer improved soil curing time determined by the unconfined compressive strength micro-damage self-repair rate index in an embodiment of the present application.

[0055] Figure 11 is a geopolymer improved soil curing time determined by the elastic modulus micro-damage self-repair rate index in an embodiment of the present application.

[0056] In the figure, 1 is a base, 2 is an improved soil sample, 3 is a water-permeable stone, 4 is a confining pressure chamber, and 5 is a loading device. DETAILED DESCRIPTION

[0057] The technical solutions in the embodiments of the present application will be described below in conjunction with the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0058] A geopolymer improved soil subgrade curing time determination method based on damage self-repair rate, as shown in Figure 1 , comprises the following steps:

[0059] S1, prepare a geopolymer, test the unconfined compressive strength of the geopolymer material under 24h, 48h, 72h, 96h, 120h, 144h, and 168h curing times, and establish a prediction model of the unconfined compressive strength s of the geopolymer with respect to the curing time t according to the data obtained from a large number of tests (a total of 7 different curing times, 3 parallel samples for each curing time, and the average of 3 sets of test results, a total of 21 sets of experiments), the data being the geopolymer measured data in Table 1, and using a data programming solution method to select the form with the highest fitting degree:

[0060] s=a0ln(t)+b0 (1)

[0061] In the formula, a0 and b0 are constant coefficients, s is the unconfined compressive strength of the geopolymer (MPa), and t is the curing time (h).

[0062] Meanwhile, the logarithmic model conforms to the objective law of the change of unconfined compressive strength with time, and the early strength unconfined compressive strength grows rapidly, and the unconfined compressive strength grows slowly with the lapse of time.

[0063] Table 1 measured unconfined compressive strength of geopolymer and predicted unconfined compressive strength of geopolymer

[0064] Curing time t (h) Measured s (MPa) Predicted s (MPa) 24 8.2 6.7 48 15.2 16.3 72 20.9 22.0 96 25.1 26.0 120 28.3 29.1 144 32.8 31.7 168 35.1 33.8

[0065] Based on the test data (measured s of geopolymer) in Table 1, according to the form of the prediction model formula (1), the coefficients are obtained when the fitting error is minimum by the least square method, and thus formula (2) is obtained:

[0066] s = 13.942 ln(t) - 37.630 (2)

[0067] The predicted data of geopolymer in Table 1 is obtained according to formula (2).

[0068] Figure 2 The solid line in the middle is the measured data in Table 1, the dashed line is the predicted data of geopolymer calculated by formula (2), and the fitting accuracy R 2 is 0.983.

[0069] S2, prepare modified soil test pieces with different geopolymer contents, and test and calculate the unconfined compressive strength UCS and elastic modulus E of the modified soil (geopolymer modified soil) at 24h, 48h, 72h, 96h, 120h, 144h and 168h curing time. The specific data are shown in Table 2 measured UCS of modified soil and Table 3 measured E of modified soil;

[0070] S3, after the modified soil sample is saturated, test its wet weight G w , then dry it and test its dry weight G d , based on the mass difference between the dry weight and the wet weight, calculate the volume porosity η (%) of the modified soil by formula (3):

[0071]

[0072] In the formula, γ w represents the density of water (g / cm 3 ), V s represents the total volume of the sample (cm 3 ), G w is the wet weight of the modified soil test piece after saturation (g), and G d is the dry weight of the modified soil test piece after drying (g).

[0073] S4, based on a large number of experimental data (a total of 35 different working conditions, each working condition doing 3 parallel samples, taking 3 sets of test results average, a total of 105 groups of experiments), using neural network algorithm and multiple linear regression analysis method, directly output the prediction model form in line with a large number of test data law, and then coupling the geopolymer unconfined compressive strength prediction model obtained in S1 (i.e. the geopolymer unconfined compressive strength prediction model is part of the improved soil unconfined compressive strength prediction model), the improved soil unconfined compressive strength prediction model is established with curing time t, improved soil volume porosity η, geopolymer content α as variable, that is, formula (4) is obtained:

[0074]

[0075] In the formula, a0, b0, c1, d1, e1, f1 are constant coefficients; UCS is the unconfined compressive strength of the improved soil (MPa); t is the curing time (h) (the geopolymer is mixed with the soil sample immediately after preparation to prepare the improved soil, so the curing time of the improved soil is consistent with the curing time of the geopolymer); α is the geopolymer content (%); η is the volume porosity of the improved soil (%).

[0076] Table 2 measured unconfined compressive strength and predicted unconfined compressive strength of geopolymer improved soil

[0077]

[0078] Based on the experimental data (measured UCS of improved soil) in Table 2, the coefficients are obtained according to the form of prediction model formula (4) according to the least square method when the fitting error is minimum, so formula (5) is obtained:

[0079]

[0080] The predicted unconfined compressive strength of the geopolymer improved soil in Table 2 is obtained by formula (5).

[0081] Figure 3 The longitudinal coordinate of the improved soil predicted UCS is calculated by formula (5), and the fitting accuracy R 2 is 0.953.

[0082] S5, based on a large number of experimental data (a total of 35 different working conditions, each working condition doing 3 parallel samples, taking 3 sets of test results average, a total of 105 groups of experiments), using neural network algorithm and multiple linear regression analysis method, output the prediction model form in line with a large number of test data law, and then coupling the geopolymer unconfined compressive strength prediction model obtained in S1 (i.e. the geopolymer unconfined compressive strength prediction model is part of the improved soil elastic modulus prediction model), the improved soil elastic modulus prediction model is established with curing time t, improved soil porosity η, geopolymer content α as variable, that is, formula (6) is obtained:

[0083]

[0084] In the formula: a0, b0, c2, d2, e2, f2 are constant coefficients; E is the elastic modulus of the improved soil (MPa); t is the curing time (h); α is the geopolymer content (%); η is the volume porosity of the improved soil (%).

[0085] As the unconfined compressive strength of the geopolymer increases, the unconfined compressive strength and the elastic modulus of the geopolymer improved soil increase; the embodiment of the present application couples the unconfined compressive strength formula of the geopolymer, and reflects the relationship between the unconfined compressive strength and the elastic modulus of the improved soil and the unconfined compressive strength prediction model of the geopolymer through the coefficients c1 and c2, respectively.

[0086] Table 3 Elastic modulus test and prediction data of geopolymer improved soil

[0087]

[0088]

[0089] Based on the test data (measured E of the improved soil) in Table 3, according to the form of the prediction model formula (6), the coefficients are obtained when the fitting error is the smallest according to the least square method, so as to obtain formula (7):

[0090]

[0091] Figure 4 The longitudinal coordinate of the improved soil prediction E is calculated according to formula (7), and the fitting accuracy R is 2 0.951.

[0092] In the embodiment, the soil sample is high-liquid-limit silt, and the improved soil is composed of high-liquid-limit silt and geopolymer with different contents.

[0093] S6, in the ABAQUS finite element calculation software, a finite element mechanics simulation model of the improved soil subgrade considering the construction of the overlying base layer is established, the improved soil prediction elastic modulus (E) under different curing times is input, according to the semi-rigid base layer construction method, the base layer self-weight action load and the force of the mechanical compaction on the improved soil subgrade during the construction of the base layer are input, and the ABAQUS finite element calculation software is used to calculate the maximum vertical stress response σ1 and the lateral confining pressure stress σ3 generated in the improved soil subgrade during the construction of the semi-rigid base layer;

[0094] S7, the maximum vertical stress response σ1 and lateral confining stress σ3 as the pre-damage stress level of improved soil pre-damage dynamic triaxial test, according to the semi-rigid base construction method conversion pre-damage duration and frequency. The specific method: according to the weight of the roller as the load size, according to the roller steel wheel and the contact area of the construction surface as the load area, according to the travel speed of the roller and the roller steel wheel contact width calculation time, according to the number of compaction roller as the load frequency. Equivalent to the influence of the site construction on the roadbed is replaced by indoor pre-damage dynamic triaxial test, and then test the development of unconfined compressive strength and elastic modulus of improved soil after pre-damage dynamic triaxial test, that is, the development of unconfined compressive strength and elastic modulus of improved soil in the field. In this way, the indoor test can accurately and efficiently guide the field construction.

[0095] The semi-rigid base uses 20cm layer thickness of 6% cement content (mass fraction) of cement stabilized gravel, the density is 2.4g / cm 3 , the base weight converted into uniform load applied in the entire ABAQUS finite element calculation roadbed model, the base compaction process uses 20 tons of single steel wheel roller, the rolling speed is 2km / h, the rolling is 6 times, the steel wheel and the roadbed contact area is about 0.6m 2 (steel wheel load range). The compaction process parameters are converted into load applied in the ABAQUS finite element calculation roadbed model, the results are shown in Figures 5-6 .

[0096] The finite element calculation results show that the maximum vertical stress σ1 generated by the roadbed is 4.307×10 4 Pa; the confining pressure σ3 is 2.635×10 4 Pa, which is used as the pre-damage stress level; according to the compaction process, the pre-damage load duration is 6 seconds, the loading interval is 60 seconds, the action is 6 times, see Figure 7 ; the pre-damage dynamic triaxial test device comprises a base 1, an improved soil test piece 2 placed on the base 1, a water permeable stone 3 arranged at the upper end and the lower end of the improved soil test piece 2, an external confining pressure chamber 4 arranged outside the improved soil test piece 2 for applying lateral confining stress σ3; a loading device 5 arranged at the upper end of the improved soil test piece 2 for applying maximum vertical stress response σ1.

[0097] S8, respectively, after curing for 24h, 48h, 72h, 96h, 120h, 144h, 168h, the modified soil pre-micro damage dynamic triaxial test, and then continue to cure to the standard curing time (7d, i.e. 168h), the ultimate unconfined compressive strength and elastic modulus of the modified soil after pre-micro damage are tested, see Tables 4 and 5. According to a large number of test results (3 parallel samples for each curing time, and the average of 3 groups of test results, 21 groups of experiments in Tables 4 and 5), a data programming solution method is used, the highest fitting form is selected, and the ultimate unconfined compressive strength and elastic modulus prediction model of the modified soil after pre-micro damage is constructed with the curing time before pre-micro damage of the modified soil as the independent variable;

[0098] UCS' = a'ln(t') + b' (8)

[0099] In the formula: a', b' are constant coefficients; UCS' is the ultimate unconfined compressive strength of the modified soil after pre-micro damage (MPa); t' is the curing time before pre-micro damage of the modified soil (h).

[0100] E' = c'ln(t') + d' (9)

[0101] In the formula: c', d' are constant coefficients; E' is the ultimate elastic modulus of the modified soil after pre-micro damage (MPa); t' is the curing time before pre-micro damage of the modified soil (h).

[0102] Formula (8) is the ultimate unconfined compressive strength prediction model of the modified soil after pre-micro damage under different curing times before pre-micro damage, formula (1) is the geopolymer unconfined compressive strength prediction model, the only influencing factor of formula (8) is the curing time before pre-micro damage, formula (1) is the curing time, and the essence is the curing time, so the form is consistent with formula (1). The unconfined compressive strength and elastic modulus of the modified soil are in line with the logarithmic change trend with time in objective law, so formula (9) is the same as formula (8) in form, and both are logarithmic models.

[0103] Table 4 Test and prediction data of unconfined compressive strength of modified soil with pre-micro damage

[0104]

[0105] Based on the test data (measured UCS') in Table 4, according to the form of prediction model formula (8), the coefficients are obtained when the fitting error is minimum according to the least square method, and formula (10) is obtained:

[0106] UCS' = 0.941 ln(t') - 2.766 (10)

[0107] The predicted UCS' data in Table 4 is obtained according to formula (10).

[0108] Figure 7 The middle solid line is the measured UCS' in Table 4, and the dotted line is the predicted UCS' calculated by formula (10), and the fitting accuracy R 2 is 0.991.

[0109] Table 5 Test and prediction data of pre-damage improved soil elastic modulus

[0110]

[0111] Based on the test data (measured E') in Table 5, according to the form of the prediction model formula (9), the coefficients are obtained according to the least square method when the fitting error is minimum, so as to obtain formula (11):

[0112] E' = 236.770 ln(t ′ )-410.810 (11)

[0113] The predicted E' data in Table 5 is obtained according to formula (11).

[0114] Figure 8 The middle solid line is the measured E' in Table 5, and the dotted line is the predicted E' calculated by formula (11), and the fitting accuracy R 2 is 0.989.

[0115] S9, the size of the micro-damage self-repairing rate index is determined according to the highway engineering grade (referring to the classification of each highway grade in Highway Subgrade Design Specification JTG30-2015)

[0116] Table 6 Micro-damage self-repairing rate index requirements

[0117] Road class Microdamage self-repair rate requirement Motorway, primary road 80％ Secondary road 70％ Tertiary, quaternary road 60％

[0118] In practical application, when the improvement scheme and the base construction scheme of the actual project are consistent, the self-repairing rate is constant. According to the requirements that the micro-damage self-repairing rates of the unconfined compressive strength and the elastic modulus meet 80%, the final curing time of the polymer improved soil is determined as 103h.

[0119] Specific calculation method: according to the requirement that the micro-damage self-repairing rate meets 80%, such as Figures 9-10As shown, according to the parameters (geopolymer content α, volume porosity of improved soil η) determined according to the engineering improvement scheme, the final unconfined compressive strength and elastic modulus of the improved soil without pre-damage are obtained by substituting the standard curing time (t = 168h) into formula (5) and formula (7), multiplied by the self-repairing rate of 80%, the unconfined compressive strength and elastic modulus of the improved soil meeting the self-repairing rate requirement after pre-damage are obtained, and substituted into formula (10) and formula (11), the curing time meeting the self-repairing rate requirement before pre-damage is obtained, and the larger of the two curing times is taken as the final curing time of the improved soil.

[0120] The micro-damage self-repairing rate introduced in the embodiment of the present application can reflect the recovery effect of the geopolymer improved soil on resisting the influence of base construction, and can highlight the characteristics of the performance of the geopolymer improved soil developing over time to a certain extent.

[0121] The embodiment of the present application determines the influence law of the base construction on the unconfined compressive strength and elastic modulus of the improved soil based on the pre-damage mode, establishes a prediction model, and finally determines the curing time by taking the micro-damage self-repairing rate as the judgment condition. The influence of the field construction on the subgrade is equivalent to the pre-damage test in the laboratory, and then the development of the unconfined compressive strength and elastic modulus of the improved soil after the pre-damage test is tested, which can reflect the development of the unconfined compressive strength and elastic modulus of the improved soil in the field. Under the condition of ensuring not to affect the field construction, the laboratory test state is closer to the actual construction state, thereby improving the accuracy of the laboratory test in guiding the field construction.

[0122] In the method of the embodiment of the present application, all the model fitting correlation coefficients R 2 are higher than 0.95, indicating that the model fitting accuracy is high, reflecting the accuracy of the method; and the influence of the field construction is obtained by numerical simulation calculation, and the laboratory test method is combined, so that the laboratory test state is closer to the actual construction state, and the accuracy of the method is improved to a great extent. The micro-damage self-repairing rate is directly related to the engineering design requirements, making the index more scientific and reasonable.

[0123] The above only describes the preferred embodiments of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining a maintenance time of a geopolymer improved soil subgrade based on a damage self-repair rate, characterized by, The method comprises the following steps: Step 1, determining the geopolymer content α and the volume porosity η of the improved soil according to the engineering improvement scheme, and substituting the geopolymer content α, the volume porosity η of the improved soil and the standard curing time into the improved soil unconfined compressive strength prediction model and the improved soil elastic modulus prediction model with curing time, volume porosity and geopolymer content as variables, see formula (1) and formula (2), to obtain the final unconfined compressive strength and elastic modulus of the improved soil without pre-damage; In the formula, a0, b0, c1, d1, e1, f1, c2, d2, e2 and f2 are constant coefficients; E is the elastic modulus of the improved soil; UCS is the unconfined compressive strength of the improved soil; t is the curing time; α is the geopolymer content; and η is the volume porosity of the improved soil; Step 2, multiplying the final unconfined compressive strength and elastic modulus of the improved soil without pre-damage by the micro-damage self-repairing rate to obtain the unconfined compressive strength and elastic modulus of the improved soil after pre-damage that meet the self-repairing rate requirement; Step 3, substituting the unconfined compressive strength and elastic modulus of the improved soil after pre-damage that meet the self-repairing rate requirement obtained in step 2 into the prediction model of the final unconfined compressive strength and elastic modulus of the improved soil after pre-damage about the curing time before pre-damage, see formula (3) and (4): UCS' = a'ln(t') + b' (3) E' = c'ln(t') + d' (4) In the formula, a', b', c' and d' are constant coefficients; UCS' is the final unconfined compressive strength of the improved soil after pre-damage; E' is the final elastic modulus of the improved soil after pre-damage; and t' is the curing time of the improved soil before pre-damage; Thus, the curing time before pre-damage is obtained, and the larger one of the two curing times is taken as the final curing time of the improved soil. In step 1, the determination method of the improved soil unconfined compressive strength prediction model and the improved soil elastic modulus prediction model with curing time, volume porosity and geopolymer content as variables comprises the following steps:

2. The method for determining the maintenance time of the geopolymer improved soil subgrade based on the damage self-repairing rate according to claim 1, characterized in that, Step 11, preparing geopolymer, obtaining unconfined compressive strength at different curing times through experiments, and based on the corresponding relationship between the unconfined compressive strength of the geopolymer and the curing time, selecting the form with the highest fitting degree through a data programming solving method to establish a prediction model of the unconfined compressive strength of the geopolymer about the curing time; Step 12, preparing improved soil test pieces with different geopolymer contents, and obtaining the volume porosity of the improved soil test pieces and the unconfined compressive strength and elastic modulus of the improved soil test pieces at different curing times through experiments; Step 13, based on the influence law of the curing time, the volume porosity and the geopolymer content of the improved soil test pieces on the unconfined compressive strength of the improved soil test pieces, obtaining a prediction model form conforming to the influence law through multivariate linear regression combined with an artificial neural network algorithm, and then coupling the geopolymer unconfined compressive strength prediction model obtained in step 11 to establish the improved soil unconfined compressive strength prediction model with curing time, volume porosity and geopolymer content as variables. ​ Based on the influence law of the curing time, the volume porosity and the geopolymer content on the elastic modulus of the modified soil sample, a prediction model form conforming to the influence law is obtained by multivariate linear regression combined with artificial neural network algorithm, and then the geopolymer unconfined compressive strength prediction model obtained in step 11 is coupled to establish a modified soil elastic modulus prediction model with curing time, volume porosity and geopolymer content as variables.

3. The method for determining the maintenance time of the geopolymer improved soil subgrade based on the damage self-repairing rate according to claim 2, characterized in that, In step 11, the prediction model of the geopolymer unconfined compressive strength with respect to the curing time is: s = a0ln(t) + b0 In the formula, a0 and b0 are constant coefficients, s is the geopolymer unconfined compressive strength, and t is the curing time.

4. The method for determining the maintenance time of the geopolymer improved soil subgrade based on the damage self-repairing rate according to claim 3, characterized in that, In step 11, the determination method of the constant coefficient is: Based on the measured geopolymer unconfined compressive strength, the coefficient is obtained according to the least square method when the fitting error is the smallest, so that: s = 13.942ln(t) - 37.630 In the formula, t is the curing time.

5. The method for determining the maintenance time of the geopolymer improved soil subgrade based on the damage self-repairing rate according to claim 1, characterized in that, In step 1, the determination method of the constant coefficient is: based on the measured modified soil unconfined compressive strength, the coefficient is obtained according to the least square method when the fitting error is the smallest according to the form of the prediction model formula (1), so that: Based on the measured modified soil elastic modulus, the coefficient is obtained according to the least square method when the fitting error is the smallest according to the form of the prediction model formula (2), so that: In the formula, t is the curing time.

6. The method for determining the maintenance time of the geopolymer improved soil subgrade based on the damage self-repairing rate according to claim 1, characterized in that, In step 2, the micro-damage self-repairing rate is determined according to the highway grade, and the micro-damage self-repairing rate of the expressway or the first-class highway is 80%; the micro-damage self-repairing rate of the second-class highway is 70%; and the micro-damage self-repairing rate of the third or fourth-class highway is 60%.

7. The method for determining the maintenance time of the geopolymer improved soil subgrade based on the damage self-repairing rate according to claim 1, characterized in that, In step 3, the determination method of the prediction model of the final unconfined compressive strength and the elastic modulus of the modified soil after the pre-added micro-damage with respect to the curing time before the pre-added micro-damage includes the following steps: Step 31, a modified soil subgrade finite element mechanics simulation model considering the construction of the overlying base layer is established in the ABAQUS finite element calculation software, the predicted elastic modulus of the modified soil under different curing times is input, the self-weight load of the base layer and the force of the mechanical compaction on the modified soil subgrade during the construction of the base layer are input according to the semi-rigid base layer construction method, and the maximum vertical stress response σ1 and the lateral confining pressure stress σ3 generated in the modified soil subgrade during the construction of the semi-rigid base layer are calculated by using the ABAQUS finite element calculation software; Step 32, taking the maximum vertical stress response σ1 and the lateral confining stress σ3 calculated in step 31 as the pre-damage stress level, performing a pre-damage dynamic triaxial test on the improved soil, and converting the pre-damage time and number of times according to the semi-rigid base construction method; performing a pre-damage dynamic triaxial test on the improved soil after different curing times, and then continuing to cure until the standard curing time; obtaining the final unconfined compressive strength and elastic modulus of the improved soil after pre-damage through experiments; based on the corresponding relationship between the final unconfined compressive strength and elastic modulus of the improved soil after pre-damage and the curing time before pre-damage, selecting the form with the highest fitting degree through a data planning solution method, and respectively establishing prediction models of the final unconfined compressive strength and elastic modulus of the improved soil after pre-damage with respect to the curing time before pre-damage.

8. The method for determining the maintenance time of the geopolymer improved soil subgrade based on the damage self-repairing rate according to claim 1, characterized in that, In step 3, the determination method of the constant coefficient: based on the measured unconfined compressive strength of the improved soil after pre-damage, the coefficient is obtained according to the least square method when the fitting error is the smallest according to the form of the prediction model formula (3), thereby obtaining: UCS' = 0.941ln(t') - 2.766 Based on the measured elastic modulus of the improved soil after pre-damage, the coefficient is obtained according to the least square method when the fitting error is the smallest according to the form of the prediction model formula (4), thereby obtaining: E' = 236.770 ln(t) - 410.810 ′ - 410.810 In the formula: t' is the curing time of the improved soil before pre-damage.

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