Method and system for predicting shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture

Abstract

The invention provides a method and a system for predicting a shear strength parameter value of a calcium alginate microcapsule drainage asphalt mixture, and relates to the technical field of asphalt mixers.The prediction method comprises the following steps: S1, obtaining a to-be-predicted calcium alginate microcapsule drainage asphalt mixture, and determining the shear strength parameter value of the to-be-predicted calcium alginate microcapsule drainage asphalt mixture; the calcium alginate microcapsule drainage asphalt mixture comprises aggregate, asphalt mortar and calcium alginate microcapsules, wherein the asphalt mortar comprises asphalt mortar and mineral powder; s2, testing the asphalt mortar at a preset temperature to obtain a complex modulus of the asphalt mortar; testing the asphalt mortar at a preset temperature to obtain the surface energy of the asphalt mortar; testing the skeleton formed by the aggregate to obtain an internal friction angle of the skeleton of the aggregate; and S3, inputting the complex modulus, the surface energy and the internal friction angle of the aggregate skeleton obtained in the step S2 into a pre-constructed parameter value prediction model to obtain a shear strength parameter value of the calcium alginate microcapsule drainage asphalt mixture.

Description

Technical Field

[0001] The present invention relates to the technical field of asphalt mixtures, and in particular to a method and system for predicting shear strength parameter values ​​of calcium alginate microcapsule drainage asphalt mixtures. Background Art

[0002] Drained asphalt pavement is a very common pavement form, and rutting damage is one of the main modes of pavement damage. The rutting resistance of pavement materials is closely related to the parameter value of their shear strength. Cohesion and friction angle are common parameter values ​​used to characterize the shear strength of materials, which can be used for theoretical analysis and finite element simulation analysis to predict the rutting development law or rutting depth of roads.

[0003] Based on the above background, this research group provides a method and system for predicting the shear strength parameter values ​​of drained asphalt mixtures, which can quickly predict the shear strength parameter values. It is disclosed in a patent application number of 202310196931.2 and the patent name is "A method and system for predicting the shear strength parameter values ​​of drained asphalt mixtures".

[0004] However, the inventors realized that by incorporating microcapsules, especially calcium alginate microcapsules, into asphalt mixtures as a new type of pavement material, the self-healing ability of the mixture can be improved by incorporating microcapsules containing self-healing agents, thereby extending the service life of the pavement and reducing maintenance costs.

[0005] However, similar to the technical problems disclosed in the prior patents, the determination of the shear strength parameters of existing asphalt mixtures often requires a large number of mechanical property experiments. When considering the shear strength at different temperatures or different microcapsule dosages, a large number of experiments are required. On the one hand, this is not conducive to our rapid determination of the shear strength of calcium alginate microcapsule asphalt mixtures. On the other hand, the test results of macroscopic mechanical properties cannot quickly guide us to optimize the material ratio. Summary of the invention

[0006] In view of the above problems, the present invention proposes a prediction method for the shear strength parameters of microcapsule asphalt mixture, covering the influence of factors such as temperature and microcapsule dosage. This method can achieve rapid prediction of the shear strength parameters of microcapsule asphalt mixture by targeting the mechanical parameters of the asphalt mixture at the microscopic level, such as the complex modulus of asphalt mortar and the shear strength of the particle skeleton.

[0007] The present invention provides a method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture, comprising the following steps:

[0008] S1. Obtaining a calcium alginate microcapsule drainage asphalt mixture to be predicted, wherein the calcium alginate microcapsule drainage asphalt mixture comprises aggregate, asphalt mortar and calcium alginate microcapsules, wherein the asphalt mortar comprises asphalt mortar and mineral powder;

[0009] S2. At a preset temperature, the asphalt mortar is tested to obtain the complex modulus of the asphalt mortar; at a preset temperature, the asphalt mortar is tested to obtain the surface energy of the asphalt mortar; the skeleton composed of aggregates is tested to obtain the internal friction angle of the aggregate skeleton;

[0010] S3. Input the complex modulus, the surface energy and the internal friction angle of the aggregate skeleton obtained in step S2 into a pre-constructed parameter value prediction model to obtain the shear strength parameter value of the calcium alginate microcapsule drainage asphalt mixture.

[0011] In some embodiments, in step S2, a triaxial compression test is performed on the skeleton composed of the aggregate to measure the internal friction angle of the aggregate skeleton.

[0012] In some embodiments, in step S2, a rheological test is performed on the asphalt mortar to obtain the complex modulus of the asphalt mortar.

[0013] In some embodiments, in step S2, a static contact angle test is performed on the asphalt mortar to obtain the surface energy of the asphalt mortar.

[0014] In some embodiments, the S3 comprises:

[0015] S31, inputting the internal friction angle of the aggregate skeleton and the complex modulus into the parameter value prediction model, and the parameter value prediction model uses a pre-configured first prediction formula to process the internal friction angle of the aggregate skeleton and the complex modulus to obtain the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature;

[0016] S32. The complex modulus, the surface energy and the predicted internal friction angle of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature are input into the parameter value prediction model. The parameter value prediction model calls a pre-configured second prediction model to process the complex modulus, the surface energy and the predicted internal friction angle of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature to obtain the cohesion of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature.

[0017] In some embodiments, the first prediction formula is as follows:

[0018]

[0019] Among them, φ EPAM，Tis the predicted internal friction angle of calcium alginate microcapsule drainage asphalt mixture at temperature T;

[0020] φ sk is the internal friction angle of the aggregate skeleton;

[0021] F is the first preset constant;

[0022] P is the volume proportion of calcium alginate microcapsules in aggregate + calcium alginate microcapsules;

[0023] G T * is the complex modulus of asphalt mortar;

[0024] K is a second preset constant.

[0025] In some embodiments, the second prediction formula is as follows:

[0026] C EPAM，T =(N·S 2 +M·S)·P·tanφ EPAM，T

[0027] Among them, c EPAM,T is the cohesion of calcium alginate microcapsule drainage asphalt mixture at temperature T;

[0028]

[0029] W C，T is the cohesive work of asphalt mortar, which is twice the surface energy;

[0030] N is a third preset constant;

[0031] M is a fourth preset constant;

[0032] P is the volume proportion of calcium alginate microcapsules in aggregate + calcium alginate microcapsules;

[0033] G T * is the complex modulus of asphalt mortar;

[0034] φ EPAM，T is the predicted internal friction angle of calcium alginate microcapsule drainage asphalt mixture at temperature T.

[0035] The second object of the present invention is to provide a shear strength parameter value prediction system for calcium alginate microcapsule drainage asphalt mixture, which is applied to the shear strength parameter value prediction method, comprising:

[0036] A first data acquisition module, used for acquiring an external input of an internal friction angle of the aggregate skeleton obtained by testing the skeleton composed of the aggregate at room temperature;

[0037] A second data acquisition module, used to obtain the complex modulus and surface energy corresponding to the asphalt mortar obtained by testing the asphalt mortar at a preset temperature through external input;

[0038] A parameter value prediction module is respectively connected to the first data acquisition module and the second data acquisition module, and is used to input the complex modulus, the surface energy and the internal friction angle of the aggregate skeleton into a pre-constructed parameter value prediction model to obtain the shear strength parameter value corresponding to the calcium alginate microcapsule drainage asphalt mixture.

[0039] In some embodiments, the parameter value prediction module includes:

[0040] a first prediction unit, for inputting the internal friction angle of the aggregate skeleton and the complex modulus into the parameter value prediction model, and causing the parameter value prediction model to call a pre-configured first prediction formula to process the internal friction angle of the aggregate skeleton and the complex modulus to obtain a predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature;

[0041] A second prediction unit is connected to the first prediction unit, and is used to input the complex modulus, the surface energy and the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature into the parameter value prediction model, and the parameter value prediction model calls a pre-configured second prediction model to process the complex modulus, the surface energy and the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature to obtain the shear strength parameter value corresponding to the calcium alginate microcapsule drainage asphalt mixture. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Grading diagram of basalt aggregate used for verification test;

[0043] Figure 2 This is a physical picture of the calcium alginate microcapsules used in the present invention;

[0044] Figure 3 This is a comparison diagram of the internal friction angle obtained by actual test of the present invention and the internal friction angle predicted by the formula;

[0045] Figure 4 This is a comparison chart of the cohesion value actually tested in the experiment of the present invention and the cohesion value predicted by the formula. DETAILED DESCRIPTION

[0046] First, those skilled in the art should understand that these implementations are only used to explain the technical principles of the embodiments of the present application, and are not intended to limit the protection scope of the embodiments of the present application. Those skilled in the art can make adjustments to them as needed to adapt to specific application scenarios.

[0047] In a preferred embodiment of the present invention, a method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture is provided, comprising the following steps:

[0048] S1. Obtaining a calcium alginate microcapsule drainage asphalt mixture to be predicted, wherein the calcium alginate microcapsule drainage asphalt mixture comprises aggregate, asphalt mortar and calcium alginate microcapsules, wherein the asphalt mortar comprises asphalt mortar and mineral powder;

[0049] S2. At a preset temperature, the asphalt mortar is tested to obtain the complex modulus of the asphalt mortar; at a preset temperature, the asphalt mortar is tested to obtain the surface energy of the asphalt mortar; the skeleton composed of aggregates is tested to obtain the internal friction angle of the aggregate skeleton;

[0050] S3. Input the complex modulus, the surface energy and the internal friction angle of the aggregate skeleton obtained in step S2 into a pre-constructed parameter value prediction model to obtain the shear strength parameter value of the calcium alginate microcapsule drainage asphalt mixture.

[0051] Specifically, in this embodiment, considering that the calcium alginate microcapsule drainage asphalt mixture is a multiphase body, it can be regarded as composed of asphalt mortar, aggregate and calcium alginate microcapsules at the microscopic level. Compared with the drainage asphalt mixture, the asphalt mortar is easier to prepare, and its shear strength parameter values ​​at different temperatures can also be quickly determined. The basalt aggregate itself is not affected by temperature, and its shear strength parameter value is easier to obtain than the drainage asphalt mixture. Therefore, separating the drainage asphalt mixture into asphalt mortar and aggregate for separate testing can speed up the prediction of the shear strength parameter value. Combined with known parameters such as the added volume proportion of calcium alginate microcapsules, the shear strength parameter value can be quickly predicted.

[0052] More specifically, in other embodiments, the aggregate may be made of raw materials such as basalt aggregate.

[0053] More specifically, in other embodiments, the mineral powder may be made of raw materials such as limestone mineral powder or slag mineral powder.

[0054] At the same time, as described in the aforementioned patent, the shear strength of drainage asphalt is related to the mechanical properties of its meso-components. Compared with the macroscopic experiments conducted on drainage asphalt, the determination of the mechanical properties of its meso-components has the advantages of simple sample preparation and convenient experimental operation. Therefore, it is of key significance to predict the macroscopic shear strength of drainage asphalt based on the mechanical properties of its meso-components.

[0055] In some embodiments, in step S2, a triaxial compression test is performed on the skeleton composed of the aggregate to measure the internal friction angle of the aggregate skeleton.

[0056] Since the triaxial compression test is an existing technology, it can be carried out with reference to BS EN 13286-7-2004 and will not be described in detail here.

[0057] In some embodiments, in step S2, a rheological test is performed on the asphalt mortar to obtain the complex modulus of the asphalt mortar.

[0058] Since the rheological test is an existing technology, it can be performed with reference to AASHTO T315 and will not be described in detail here.

[0059] In some embodiments, in step S2, a static contact angle test is performed on the asphalt mortar to obtain the surface energy of the asphalt mortar.

[0060] Since the contact angle test is an existing technology, it can be performed by reference and will not be described in detail here.

[0061] In some embodiments, the S3 comprises:

[0062] S31, inputting the internal friction angle of the aggregate skeleton and the complex modulus into the parameter value prediction model, and the parameter value prediction model uses a pre-configured first prediction formula to process the internal friction angle of the aggregate skeleton and the complex modulus to obtain the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature;

[0063] S32. The complex modulus, the surface energy and the predicted internal friction angle of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature are input into the parameter value prediction model. The parameter value prediction model calls a pre-configured second prediction model to process the complex modulus, the surface energy and the predicted internal friction angle of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature to obtain the cohesion of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature.

[0064] In some embodiments, the first prediction formula is as follows:

[0065]

[0066] Among them, φEPAM，T is the predicted internal friction angle of calcium alginate microcapsule drainage asphalt mixture at temperature T; φ sk is the internal friction angle of the aggregate skeleton; F is the first preset constant, which can be 0.09; P is the volume ratio of calcium alginate microcapsules in aggregate + calcium alginate microcapsules; G T * is the complex modulus of asphalt mortar; K is the second preset constant, which can be -0.1.

[0067] In some embodiments, the second prediction formula is as follows:

[0068] C EPAM，T =(N·S 2 +M·S)·P·tanφ EPAM，T

[0069] Among them, c EPAM,T is the cohesion of calcium alginate microcapsule drainage asphalt mixture at temperature T;

[0070]

[0071] W C，T is the cohesion work of asphalt mortar, which is twice the surface energy; N is the third preset constant, which can be -0.0145; M is the fourth preset constant, which can be 4.3223; P is the volume proportion of calcium alginate microcapsules in aggregate + calcium alginate microcapsules; G T * is the complex modulus of asphalt mortar; φ EPAM，T is the predicted internal friction angle of calcium alginate microcapsule drainage asphalt mixture at temperature T.

[0072] The specific embodiment of the present invention also provides a shear strength parameter value prediction system for calcium alginate microcapsule drainage asphalt mixture, which is applied to the shear strength parameter value prediction method, including:

[0073] A first data acquisition module, used for acquiring an external input of an internal friction angle of the aggregate skeleton obtained by testing the skeleton composed of the aggregate at room temperature;

[0074] A second data acquisition module, used to obtain the complex modulus and surface energy corresponding to the asphalt mortar obtained by testing the asphalt mortar at a preset temperature through external input;

[0075] A parameter value prediction module is respectively connected to the first data acquisition module and the second data acquisition module, and is used to input the complex modulus, the surface energy and the internal friction angle of the aggregate skeleton into a pre-constructed parameter value prediction model to obtain the shear strength parameter value corresponding to the calcium alginate microcapsule drainage asphalt mixture.

[0076] In some embodiments, the parameter value prediction module includes:

[0077] a first prediction unit, for inputting the internal friction angle of the aggregate skeleton and the complex modulus into the parameter value prediction model, and causing the parameter value prediction model to call a pre-configured first prediction formula to process the internal friction angle of the aggregate skeleton and the complex modulus to obtain a predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature;

[0078] A second prediction unit is connected to the first prediction unit, and is used to input the complex modulus, the surface energy and the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature into the parameter value prediction model, and the parameter value prediction model calls a pre-configured second prediction model to process the complex modulus, the surface energy and the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature to obtain the shear strength parameter value corresponding to the calcium alginate microcapsule drainage asphalt mixture.

[0079] The prediction formula of this application is verified below in conjunction with specific embodiments:

[0080] In a specific embodiment of the present invention, the calcium alginate microcapsule drainage asphalt mixture used is prepared by mixing basalt aggregate, calcium alginate microcapsules (particle size 2.5-3.5 mm), asphalt mortar with a needle penetration of 70, and limestone ore powder.

[0081] Among them, the grading of basalt aggregate is as follows: Figure 1 As shown. When calcium alginate microcapsules are added, calcium alginate microcapsules will partially replace the 2.36-3.55mm basalt aggregate in the skeleton, and the replacement ratio is 0%, 10%, 30% and 50% by volume ratio. The optimal oil-stone ratio (i.e. the mass ratio of asphalt mortar to granular aggregate) is 4%. The amount of limestone powder is 3.5% of the asphalt mortar content. The experimental temperatures are 30℃, 40℃, 50℃, 60℃, and 70℃ respectively. The triaxial macro test results and the test results of the micro-level material properties are shown in Table 1. Figure 3 This is a comparison diagram of the internal friction angle obtained by actual test of the present invention and the internal friction angle predicted by the formula; Figure 4 The figure is a comparison chart of the cohesion value obtained by the actual test of the present invention and the cohesion value predicted by the formula. From the test results, it can be seen that the prediction method adopted by the present invention has a high matching degree with the measurement value actually measured in the laboratory, and R2 is above 0.95.

[0082] Table 1: Triaxial macroscopic test results and microscopic material properties test results

[0083]

[0084] It can be seen from the above results that the prediction method disclosed in the present invention can determine the shear strength parameters of microcapsule asphalt mixture without conducting complex macroscopic tests, but predicts the macroscopic shear strength parameters based on the easier to measure microscopic performance of asphalt mixture. These macroscopic shear strength parameters can be used for subsequent road finite element calculations or theoretical calculations to provide a reference for the anti-rutting design of road structures. At the same time, the method proposed in the present invention is based on the microscopic characteristics of microcapsule asphalt mixture, which helps to reveal the formation mechanism of the shear strength of microcapsule asphalt mixture, provide theoretical support for the optimization of its shear strength, and help optimize the mix design of microcapsule asphalt mixture.

[0085] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture, characterized in that: The following steps are involved: S1. Obtaining a calcium alginate microcapsule drainage asphalt mixture to be predicted, wherein the calcium alginate microcapsule drainage asphalt mixture comprises aggregate, asphalt mortar and calcium alginate microcapsules, wherein the asphalt mortar comprises asphalt mortar and mineral powder; S2. Testing the asphalt mortar at a preset temperature to obtain the complex modulus of the asphalt mortar; At a preset temperature, the asphalt mortar is tested to obtain the surface energy of the asphalt mortar; the skeleton composed of aggregates is tested to obtain the internal friction angle of the aggregate skeleton; S3. Input the complex modulus, the surface energy and the internal friction angle of the aggregate skeleton obtained in step S2 into a pre-constructed parameter value prediction model to obtain the shear strength parameter value of the calcium alginate microcapsule drainage asphalt mixture.

2. The method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture according to claim 1, characterized in that: In the step S2, a triaxial compression test is performed on the skeleton formed by the aggregate to measure the internal friction angle of the aggregate skeleton.

3. The method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture according to claim 1, characterized in that: In the step S2, a rheological test is performed on the asphalt mortar to obtain the complex modulus of the asphalt mortar.

4. The method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture according to claim 1, characterized in that: In the step S2, a static contact angle test is performed on the asphalt mortar to obtain the surface energy of the asphalt mortar.

5. The method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture according to claim 1, characterized in that: The S3 includes: S31, inputting the internal friction angle of the aggregate skeleton and the complex modulus into the parameter value prediction model, and the parameter value prediction model uses a pre-configured first prediction formula to process the internal friction angle of the aggregate skeleton and the complex modulus to obtain the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature; S32. The complex modulus, the surface energy and the predicted internal friction angle of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature are input into the parameter value prediction model. The parameter value prediction model calls a pre-configured second prediction model to process the complex modulus, the surface energy and the predicted internal friction angle of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature to obtain the cohesion of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature.

6. The method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture according to claim 5, characterized in that: The first prediction formula is as follows: Among them, φ EPAM,T is the predicted internal friction angle of calcium alginate microcapsule drainage asphalt mixture at temperature T; φ sk is the internal friction angle of the aggregate skeleton; F is the first preset constant; P is the volume proportion of calcium alginate microcapsules in aggregate + calcium alginate microcapsules; G is the complex modulus of asphalt mortar; K is a second preset constant.

7. The method for predicting the shear strength parameter value of calcium alginate microcapsule drainage asphalt mixture according to claim 5, characterized in that: The second prediction formula is as follows: c EPAM,T =(N·S 2 +M·S)·P·tanφ EPAM,T Among them, c EPAM，T is the cohesion of calcium alginate microcapsule drainage asphalt mixture at temperature T; W C，T is the cohesive work of asphalt mortar, which is twice the surface energy; N is a third preset constant; M is a fourth preset constant; P is the volume proportion of calcium alginate microcapsules in aggregate + calcium alginate microcapsules; is the complex modulus of asphalt mortar; φ EPAM , T is the predicted internal friction angle of calcium alginate microcapsule drainage asphalt mixture at temperature T.

8. A shear strength parameter value prediction system for calcium alginate microcapsule drainage asphalt mixture, characterized in that: The method for predicting a shear strength parameter value as claimed in any one of claims 1 to 7 comprises: A first data acquisition module, used for acquiring an external input of an internal friction angle of the aggregate skeleton obtained by testing the skeleton composed of the aggregate at room temperature; A second data acquisition module, used to obtain the complex modulus and surface energy corresponding to the asphalt mortar obtained by testing the asphalt mortar at a preset temperature through external input; A parameter value prediction module is respectively connected to the first data acquisition module and the second data acquisition module, and is used to input the complex modulus, the surface energy and the internal friction angle of the aggregate skeleton into a pre-constructed parameter value prediction model to obtain the shear strength parameter value corresponding to the calcium alginate microcapsule drainage asphalt mixture.

9. The shear strength parameter value prediction system according to claim 8, characterized in that: The parameter value prediction module comprises: a first prediction unit, for inputting the internal friction angle of the aggregate skeleton and the complex modulus into the parameter value prediction model, and causing the parameter value prediction model to call a pre-configured first prediction formula to process the internal friction angle of the aggregate skeleton and the complex modulus to obtain a predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature; A second prediction unit is connected to the first prediction unit, and is used to input the complex modulus, the surface energy and the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature into the parameter value prediction model, and the parameter value prediction model calls a pre-configured second prediction model to process the complex modulus, the surface energy and the predicted internal friction angle value of the calcium alginate microcapsule drainage asphalt mixture at the preset temperature to obtain the shear strength parameter value corresponding to the calcium alginate microcapsule drainage asphalt mixture.

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