A method for constructing a stress-strain response prediction model for soil-soil mixture considering tunnel waste residue content and the constructed model

Abstract

The present invention relates to a method for constructing a stress-strain response prediction model for a slag-soil mixture that takes into account the content of tunnel waste slag, and the constructed model. The method for constructing the prediction model comprehensively considers the effects of factors such as slag content, compaction degree, and confining pressure on its stress-strain response, enabling rapid prediction of the stress-strain response relationship of the slag-soil mixture under different conditions. Furthermore, the model has clear physical meaning and a simple structure; it only requires inputting the corresponding operating conditions into the model to obtain the stress-strain response relationship of the slag-soil mixture under the coupling effect of the corresponding operating conditions. This significantly reduces experimental time and difficulty, provides significant engineering convenience for organizations that lack experimental conditions, and has high market promotion value.

Description

Technical Field

[0001] The present invention belongs to the technical field of engineering construction, and in particular relates to a method for constructing a slag mixture stress-strain response prediction model taking into account tunnel waste slag content, and the constructed model. Background Art

[0002] With the continuous advancement of infrastructure construction, the number and scale of tunnel projects are constantly expanding. The large amount of byproducts generated during tunnel construction, especially the treatment of tunnel slag, has gradually become a focus of attention in the engineering community. Tunnel slag is a mixture of rock or soil produced during tunnel excavation. Due to its huge output, traditional disposal methods such as direct stacking or simple treatment no longer meet environmental protection requirements and also occupy a large amount of land resources. Based on this, an increasing number of studies have begun to explore how to rationally utilize this tunnel slag, especially in areas where filling materials are scarce or the cost of replacement soil is high. By mixing tunnel slag with soil for roadbed filling, it can effectively reduce project costs, minimize environmental pollution, and realize the resource utilization of waste slag.

[0003] As tunnel slag and soil mixtures are widely used in roadbed filling, studying their stress-strain response characteristics has become an important engineering task. The stress-strain response characteristic refers to the relationship between stress and strain exhibited by a material under the action of external force. This characteristic directly affects the bearing capacity and long-term stability of the roadbed. Existing research mainly relies on indoor tests and numerical simulation methods to determine the stress-strain relationship of slag-soil mixtures. However, these methods have their own limitations. For example, indoor test methods are time-consuming and labor-intensive and it is difficult to fully cover various actual working conditions, while numerical simulations rely on model assumptions and parameter selection, and often cannot accurately reflect the true behavior of complex materials. Therefore, finding a more accurate and convenient method to predict the stress-strain response characteristics of slag-soil mixtures is of great engineering significance.

[0004] Against this backdrop, it is crucial to develop a method for predicting the stress-strain response of slag-soil mixtures that considers tunnel slag content. The physical and mechanical properties of tunnel slag vary significantly depending on its composition and particle size distribution. Changes in slag content alter the overall mechanical properties of the slag-soil mixture. Therefore, when predicting the stress-strain response of slag-soil mixtures, the slag content must be fully considered as a crucial variable. Establishing a prediction method that accounts for variations in slag content would not only more accurately reflect the material's actual behavior but also provide a more reliable theoretical basis for engineering design, ensuring the safety and economic efficiency of roadbed construction. Furthermore, the development and application of this method will promote the development of tunnel slag resource utilization technologies and provide new approaches for the treatment and reuse of tunnel engineering byproducts. Summary of the Invention

[0005] To solve the above problems, the present invention provides a method for constructing a stress-strain response prediction model for a slag-soil mixture taking into account the tunnel waste content, comprising the following steps:

[0006] S1: Tunnel waste slag of 5mm-10mm particles is mixed with soil in different proportions to prepare a slag-soil mixture, with the mass percentages of the waste slag in the slag-soil mixture being 0%, 30%, 40%, 50%, and 60% respectively;

[0007] The slag soil mixture is made into a mixture sample; the target compaction degree is 90%, 93%, and 96%, and the moisture content is the optimal moisture content;

[0008] S2: Perform static triaxial (UU) tests on samples with different slag contents and compaction conditions. The test is stopped when the axial strain of the sample reaches 15%. The stress-strain test results of different samples under different compaction degrees and confining pressures are obtained.

[0009] S3: Use the following formula to analyze the stress-strain test results and then calculate different model parameters x1, x2, x3 under various conditions;

[0010]

[0011] Where ε is the axial strain; x1, x2, x3 are model parameters; σ1 is the major principal stress; σ3 is the minor principal stress - that is, the confining pressure; σ1-σ3=σd, which represents the axial deviatoric stress;

[0012] S4: Establish the corresponding regression relationship between the model parameters and the influencing factors, and obtain the relationship between different model parameters x1, x2, x3 and slag content C TSW , compaction degree D C and the relationship function of confining pressure σ3;

[0013] S5: Different model parameters x1, x2, x3 and slag content C will be obtained TSW , compaction degree D C Substituting the function of σ and confining pressure σ3 into the formula in step S3, the stress-strain response prediction model of slag-soil mixture considering the tunnel waste content can be obtained.

[0014] On the basis of the above scheme, in step S1, when preparing the sample, the slag mixture is equally divided into 5 layers, and the sample is a cylindrical sample with a diameter of 100 mm and a height of 200 mm.

[0015] On the basis of the above scheme, after the specimens were prepared, they were wrapped with plastic film to prevent moisture loss during the test and placed at room temperature for 24 hours.

[0016] On the basis of the above scheme, in step S2, the conditions of the static triaxial test are: confining pressures of 30 kPa, 60 kPa, 90 kPa, and 120 kPa, respectively; and a loading rate of 0.5% / min.

[0017] Based on the above scheme, before step S1, firstly based on the Highway Geotechnical Test Code (JTG

[0018] 3430-2020), the tunnel waste materials generated on site were screened, and the particles with a size of less than 0.075 mm were classified as fine particles, and the particles with a size greater than 60 mm were classified as coarse particles. The types of fine and coarse components were then confirmed through basic physical experiments, and a prediction model suitable for this type of mixed tunnel waste was obtained.

[0019] The present application also provides a model for predicting the stress-strain response of slag-soil mixture considering the content of tunnel waste slag, which is

[0020]

[0021] The tunnel waste slag is a mixed type of tunnel waste slag composed of a fine-grained component of high liquid limit clay (CH) and a coarse-grained component of gravel (GW).

[0022] The beneficial effects of the present invention are:

[0023] The method of the present invention can better realize the mixing of tunnel waste slag and soil for roadbed filling, thereby effectively reducing the cost of the project, especially in areas where filling materials are scarce or the cost of replacing backfill soil is high. At the same time, the resource utilization of tunnel waste slag reduces the amount of waste slag stacking, reduces the negative impact on the environment, realizes the reuse of waste resources, and improves the overall environmental protection benefits of the project. The present invention provides a method for constructing a stress-strain response prediction model of a slag-soil mixture considering the content of tunnel waste slag, which comprehensively considers the influence of factors such as slag content, compaction degree, and confining pressure on its stress-strain response, and realizes the rapid prediction of the stress-strain response relationship of the slag-soil mixture under different conditions; at the same time, the model has clear physical meaning and simple structure, and only needs to input the corresponding working conditions into the model to obtain the stress-strain response relationship of the slag-soil mixture under the coupling of the corresponding working conditions, which greatly reduces the time consumption of the test and reduces the difficulty of the test, and provides obvious engineering convenience for units that do not have the test conditions, and has high market promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 This is a schematic diagram of the gradation curve of the slag in Example 2 of the present application;

[0026] Figure 2 Schematic diagram of the slag-soil mixture gradation curve under various slag content conditions in Example 2 of the present application;

[0027] Figure 3 The results of the compaction test of the slag-soil mixture under various slag content conditions in Example 2 of the present application are as follows;

[0028] Figure 4 This is a stress-strain curve diagram of different slag contents (0%, 30%, 40%, 50%, 60%) under the conditions of 30 kPa confining pressure and 93% compaction degree in Example 2 of the present application;

[0029] Figure 5 This is a stress-strain curve diagram of different compaction degrees (90%, 93%, and 96%) under the conditions of 30 kPa confining pressure and 40% slag content in Example 2 of the present application;

[0030] Figure 6 Stress-strain curves of different confining pressures (30 kPa, 60 kPa, 90 kPa, and 120 kPa) under the conditions of 0% slag content and 93% compaction in Example 2 of the present application;

[0031] Figure 7 The parameter (a) of the modified hyperbolic model in Example 2 of the present application is 10 5 x1; (b) 10 5 x2; (c) 10 3 x3;

[0032] Figure 8 To verify the model in Example 2 of this application: comparison of stress-strain curves;

[0033] Figure 9 This is the model verification in Example 2 of this application: robustness verification. DETAILED DESCRIPTION

[0034] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] Example 1

[0036] The embodiment of the present invention provides a method for constructing a stress-strain response prediction model for a slag-soil mixture taking into account the content of tunnel waste slag. The specific process is as follows:

[0037] Step a: Based on the particle group classification standards in the "Highway Geotechnical Test Code" (JTG 3430-2020), the tunnel waste material generated on site was screened and classified into a fine particle group with a particle size of less than 0.075 mm and a coarse particle group with a particle size greater than 60 mm.

[0038] Then, the fine particle components were subjected to particle analysis experiments, limit moisture content tests, specific gravity tests, and compaction tests respectively; the clay content (particles smaller than 0.002 mm), liquid limit, plastic limit, plasticity index, specific gravity, maximum dry density, and optimum moisture content were obtained;

[0039] The type of fine-grained components of tunnel waste slag is obtained through basic tests on fine-grained components.

[0040] The coarse-grained components were subjected to particle analysis experiments, specific gravity tests and Los Angeles abrasion tests; the unevenness coefficient, curvature coefficient, specific gravity and Los Angeles abrasion were obtained respectively, and finally the type of the coarse-grained components was obtained.

[0041] Step b: selecting tunnel waste slag of 5mm-10mm particles and mixing it with soil in different proportions to prepare a slag-soil mixture, wherein the mass percentages of the slag in the slag-soil mixture are: 0%, 30%, 40%, 50%, and 60% respectively;

[0042] Obtain the corresponding gradation curve and compaction test results (obtain the maximum dry density and optimal moisture content) based on the slag-soil mixture with different waste residue contents;

[0043] Then, for each mixture sample with any waste residue content, cylindrical specimens with a diameter of 100 mm and a height of 200 mm were prepared by dividing the sample into five equal layers. The target compaction levels were 90%, 93%, and 96%, and the moisture content was the optimal moisture content. This compaction range was selected to simulate the transition from a loose to a dense state in actual roadbed construction. After sample preparation, the sample was wrapped in plastic film to prevent moisture loss during testing and placed at room temperature (approximately 20°C) for 24 hours before the static triaxial test.

[0044] Tunnel waste with a particle size of less than 5 mm can also be used as soil.

[0045] Step c: Static triaxial (UU) testing was performed on samples with varying slag contents and compaction levels at confining pressures of 30 kPa, 60 kPa, 90 kPa, and 120 kPa, and a loading rate of 0.5% / min. Testing was terminated when the axial strain reached 15%. The specific test conditions are shown in Table 1.

[0046] Table 1 Static triaxial test scheme

[0047]

[0048] The present invention uses the controlled variable test method to conduct the test, which only requires 28 samples. If a full-operating condition test is performed, 5*4*3=60 samples are required. In addition, the 40% slag content is in the middle of the variable range and can be used as a good representative operating condition.

[0049] The stress-strain test results of different samples under different compaction degrees and confining pressures were obtained through static triaxial (UU) tests.

[0050] Step d: First, use the following formula to analyze the stress-strain test results, and then calculate different model parameters x1, x2, and x3 under various conditions.

[0051]

[0052] Where ε is the axial strain; x1, x2, and x3 are model parameters; σ1 is the major principal stress, and σ3 is the minor principal stress—the confining pressure. σ1-σ3=σd, which represents the axial deviatoric stress.

[0053] Then, a corresponding regression relationship is established between the model parameters and the influencing factors, wherein the influencing factors refer to the slag content C TSW , compaction degree D C , confining pressure σ3; and then obtain different model parameters x1, x2, x3 and slag content C TSW , compaction degree D C , a function of the confining pressure σ3;

[0054] Step e:

[0055] Different model parameters x1, x2, x3 and slag content C will be obtained TSW , compaction degree D C Substituting the function of σ3 and confining pressure into formula (2), the stress-strain response prediction model of slag-soil mixture considering the tunnel waste content of the present invention can be obtained.

[0056] Example 2

[0057] Based on the method in Example 1, this application uses waste residue from a highway tunnel project in southern China to provide a method for constructing a stress-strain response prediction model for a slag-soil mixture that takes into account the content of tunnel waste residue. The specific process is as follows:

[0058] Step a: Determine the basic physical performance indicators of each component of the slag-soil mixture through a series of basic physical performance tests. The details are as follows:

[0059] Based on the particle group classification standards in the "Highway Geotechnical Test Code" (JTG 3430-2020), the tunnel waste generated at the tunnel site was screened, and the particle size <0.075mm was classified as the fine particle group, and the particle size >60mm>>0.075mm was classified as the coarse particle group.

[0060] Based on the "Highway Geotechnical Test Code" (JTG 3430-2020), particle analysis experiments, limit moisture content tests, specific gravity tests, and compaction tests were conducted. It was found that the clay content (particles less than 0.002 mm) was 63.43%, the liquid limit was 51.8%, the plastic limit was 24.1%, the plasticity index was 27.7, the specific gravity was 2.65, and the maximum dry density was 1.78 g / cm 3 The optimum moisture content is 17.3%. The fine-grained component is named high liquid limit clay (CH).

[0061] The coarse-grained component is the slag produced by the relevant tunnel project. The gradation curve is as follows: Figure 1 As shown, the coefficient of uniformity and curvature are 5.13 and 1.37, respectively. Therefore, it can be classified as well-graded gravel (GW). Furthermore, the specific gravity is 2.92 and the Los Angeles abrasion loss is 16.9%, indicating that this component has high resistance to degradation.

[0062] Step b: According to the definition of soil-slag mixture, it contains two components: soil and slag. Medley (1994) proposed the soil / rock threshold D when studying soil-slag mixture in Franciscan and other places. s / r =0.05Lc (Formula 1), Lc is the engineering characteristic scale of the soil mixture. For different research areas, the value of Lc is different. For the slope, Lc is equal to the slope height; for the direct shear test, Lc is the height of a single test box; for the triaxial test, Lc is the diameter of the specimen. Since the present invention requires a triaxial test, the diameter of a single specimen is 100 mm, so D s / r The particle size is 5mm, that is, particles smaller than 5mm are defined as "soil" and particles larger than 5mm are defined as "slag".

[0063] At the same time, the "Highway Geotechnical Test Code" (JTG 3430-2020) stipulates that in the triaxial test, the maximum particle size in the triaxial specimen with a diameter of 100 mm shall not exceed 1 / 10 of the diameter. Therefore, the particle size range of "slag" in the present invention is selected as 5-10 mm, and the particle size range of "soil" is selected as <5 mm.

[0064] Based on this, soil and slag were mixed in different proportions (0%, 30%, 40%, 50%, 60%, defined as the ratio of slag mass to mixture mass) to prepare slag-soil mixture. The corresponding gradation curves and compaction test results are shown in Figure 2. Figure 2 、 Figure 3 These slag contents were chosen to represent a wide range of mix proportions, from pure clayey soils to slag-rich mixes dominated by coarse particles.

[0065] Then, for any mixture sample containing any slag content, cylindrical specimens with a diameter of 100 mm and a height of 200 mm were prepared by dividing the sample into five equal layers. The target compaction levels were 90%, 93%, and 96%, and the moisture content was the optimal value. This compaction range was selected to simulate the transition from a loose to a dense state in actual roadbed construction. After sample preparation, the sample was wrapped in plastic film to prevent moisture loss during testing and placed at room temperature (approximately 20°C) for 24 hours before the static triaxial test.

[0066] Step c: Static triaxial (UU) testing was performed on samples with varying slag contents and compaction levels at confining pressures of 30 kPa, 60 kPa, 90 kPa, and 120 kPa, and a loading rate of 0.5% / min. Testing was terminated when the axial strain reached 15%. The specific test conditions are shown in Table 1.

[0067] The stress-strain test results of different samples under different compaction degrees and confining pressures were obtained through static triaxial (UU) tests. Among them, the stress-strain curves of different slag contents (0%, 30%, 40%, 50%, 60%) under the conditions of 30kPa confining pressure and 93% compaction degree are as follows: Figure 4 As shown in the figure; under the conditions of 30kPa confining pressure and 40% slag content, the stress-strain curves of different compaction degrees (90%, 93%, 96%) are as shown in the figure. Figure 5 As shown in the figure; under the conditions of 40% slag content and 93% compaction degree, the stress-strain curves of different confining pressures (30kPa, 60kPa, 90kPa, 120kPa) are as follows: Figure 6 shown.

[0068] Step d: The present invention uses the classical hyperbola model (as shown in formula 2) to describe the stress-strain response of the slag-soil mixture. However, considering the influence of factors such as slag content and compaction degree, the hyperbola model with only stress variables cannot satisfy the unified description of the stress-strain curve. In order to uniformly express the stress-strain relationship of the slag-soil mixture under various conditions, the present invention first uses formula (2) to analyze the stress-strain test results (as shown in formula 2). Figure 4-6 The results are shown in Figure 2. The model parameters x1, x2, and x3 are calculated for different scenarios. A regression relationship is then established between the model parameters and the influencing factors.

[0069]

[0070] Where ε is the axial strain; x1, x2, and x3 are model parameters; σ1 is the major principal stress, and σ3 is the minor principal stress—the confining pressure. σ1-σ3=σd, which represents the axial deviatoric stress.

[0071] The stress-strain responses corresponding to the 28 operating conditions in Table 1 were divided into two parts. In the first part, 24 operating conditions were used to modify the hyperbolic model; in the second part, 4 operating conditions were used to verify the modified hyperbolic model. The second part includes operating conditions A: 30% slag content, 60 kPa confining pressure, 93% compaction; B: 50% slag content, 30 kPa confining pressure, 93% compaction; C: 40% slag content, 30 kPa confining pressure, 90% compaction; and D: 0% slag content, 120 kPa confining pressure, 93% compaction. These operating conditions cover the types of stress-strain responses under the influence of various factors and provide a comprehensive assessment of the accuracy and applicability of the modified hyperbolic model.

[0072] Formula (2) was used to fit the stress-strain test results of 24 working conditions. Due to space limitations, the fitting results are not listed. Due to magnitude reasons, appropriate coefficients were set before the model parameters, and the regression relationship between the parameters x1, x2, x3 of the modified hyperbolic model shown in formulas (3)-(5) and the slag content, compaction degree and confining pressure was established. The prediction accuracy is shown in Figure 7 .

[0073] 10 5 x1=67.67(-26.57D C 2 +48.78D C -22.24)(68.67σ3 -1.14 )ln(e+C TSW ) -1.43 (3)

[0074] 10 5 x2=-0.01(113.96D C 2-216.90D C +103.88)(1.73σ3-527.45)(-0.09C TSW +75.77)(4)

[0075] 10 3 x3=7.35(144.69D C 2 -276.02D C +132.47)(11.02σ3 -0.62 )ln(e+C TSW ) -0.58 (5)

[0076] Where C TSW is the slag content; D C is the degree of compaction; σ3 is the confining pressure; e is a mathematical constant with a value of 2.718; the meanings of other symbols are the same as above.

[0077] Substituting formulas (3)-(5) into formula (2), the stress-strain response prediction model of the slag-soil mixture considering the tunnel waste content of the present invention can be obtained (as shown in formula 6).

[0078]

[0079] In the formula, the symbols have the same meaning as above.

[0080] In order to evaluate the accuracy and applicability of the model, we selected the triaxial test data of working conditions A, B, C and D for verification. The results are as follows: Figure 8 and Figure 9 shown.

[0081] Depend on Figure 8 It can be seen that the calculated results are in good agreement with the measured results from the laboratory test. Figure 8 Here, M stands for measure, i.e., data from indoor tests, and P stands for predict, i.e., data predicted by the formula. A, B, C, and D are the operating conditions described above.

[0082] In addition, by Figure 9 It can be seen that most of the data points are concentrated near the y=x line, R 2 =0.9, which indicates a good fitting effect. Therefore, the model constructed by the present invention has high accuracy and applicability and can be effectively used to predict the stress-strain response relationship of slag-soil mixtures under different working conditions.

[0083] Based on the determination of the basic physical property indicators of each component of the slag-soil mixture through a series of basic physical property tests in step a, it can be seen that the model constructed in this embodiment is suitable for mixed tunnel waste slag composed of a fine-grained component of high liquid limit clay (CH) and a coarse-grained component of gravel (GW).

[0084] Each embodiment in this specification is described in a related manner. The same or similar parts between the embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences from other embodiments. The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of protection of the present invention.

Claims

1. A method for constructing a stress-strain response prediction model for slag-soil mixture considering the content of tunnel waste slag, characterized in that: The steps include: S1: Tunnel waste slag with a particle size of 5mm-10mm was mixed with soil in different proportions to prepare a slag-soil mixture. The mass percentages of the slag in the slag-soil mixture were 0%, 30%, 40%, 50%, and 60% respectively. The slag soil mixture is made into a mixture sample; the target compaction degree is 90%, 93%, and 96%, and the moisture content is the optimal moisture content; S2: Conduct static triaxial tests on samples with different slag contents and compaction conditions. Stop the test when the axial strain of the sample reaches 15%; obtain stress-strain test results of different samples under different compaction degrees and confining pressures. S3: Use the following formula to analyze the stress-strain test results and calculate different model parameters under various conditions: x 1, x 2, x 3; Where, ε is the axial strain; x 1, x 2, x 3 is the model parameter; σ1 is the major principal stress; σ3 is the minor principal stress - that is, the confining pressure; σ1-σ3=σd, which represents the axial deviatoric stress; S4: Establish corresponding regression relationships between model parameters and influencing factors to obtain different model parameters x 1, x 2, x 3 and slag content C TSW , compaction D C and confining pressure σ 3 relational function; S5: Different model parameters will be obtained x 1, x 2, x 3 and slag content C TSW , compaction D C , confining pressure σ Substituting the function of 3 into the formula in step S3, we can obtain the stress-strain response prediction model of the slag-soil mixture considering the tunnel waste content; In step S1, when preparing the sample, the soil mixture is divided into 5 equal layers. The sample is a cylindrical sample with a diameter of 100 mm and a height of 200 mm; In step S2, the conditions of the static triaxial test are: confining pressures of 30 kPa, 60 kPa, 90 kPa, and 120 kPa, respectively; loading rate of 0.5% / min; The model is: The tunnel waste slag is a mixed type of tunnel waste slag composed of a fine-grained component of high liquid limit clay and a coarse-grained component of gravel.

2. The method for constructing a stress-strain response prediction model for soil-soil mixture considering tunnel waste residue content according to claim 1, characterized in that: After the specimens were prepared, they were wrapped with plastic film to prevent moisture loss during the test and placed at room temperature for 24 hours.

3. The method for constructing a stress-strain response prediction model for soil-soil mixture considering tunnel waste residue content according to claim 1, characterized in that: Before step S1, the tunnel waste generated on site is screened, and particles with a size of less than 0.075 mm are classified as a fine-grained group, and particles with a size greater than 60 mm and greater than 0.075 mm are classified as a coarse-grained group. Basic physical experiments are then performed to confirm the types of fine and coarse components, thereby obtaining a prediction model suitable for this type of mixed tunnel waste.

4. A method for predicting the stress-strain response of a slag-soil mixture considering the content of tunnel waste residue, characterized in that: A model constructed using the method according to any one of claims 1 to 3.

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