Warm mix rubber asphalt compatibility evaluation method and device based on molecular simulation

Abstract

The invention provides a warm mixing rubber asphalt compatibility evaluation method and device based on molecular simulation, and relates to the technical field of data processing. The method comprises the following steps: performing dynamic simulation on a warm-mixed rubber asphalt analysis model to obtain performance parameters; the performance parameters at least comprise a plurality of sub-performance parameters, and the sub-performance parameters comprise a solubility parameter, binding energy and a glass transition temperature; determining a normalization matrix based on the performance parameters; calculating a first weight coefficient of the solubility parameter, a second weight coefficient of the binding energy and a third weight coefficient of the glass transition temperature by using the normalized matrix; and based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient, determining a compatibility evaluation result of the warm mixing rubber asphalt. According to the method, the compatibility mechanism of the warm-mixed rubber asphalt can be comprehensively revealed from the molecular scale, so that the compatibility evaluation result is prevented from being influenced by external environmental factors, and the accuracy of the compatibility evaluation result is improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of data processing technology. More specifically, the embodiments of the present invention relate to a method and device for evaluating the compatibility of warm-mix rubber asphalt based on molecular simulation. Background Art

[0002] With the rapid development of highway construction, asphalt, as the main pavement material, has a direct impact on the service life and driving safety of the road surface. Traditional asphalt is prone to road damage under extreme climatic conditions due to its low high temperature stability and poor low temperature crack resistance. To solve this problem, researchers have improved the performance of asphalt by adding rubber powder and hot mix agent to form hot mix rubber asphalt. The addition of rubber powder can not only enhance the flexibility and crack resistance of asphalt, but also effectively improve its performance under low temperature and thermal cycle conditions, with significant environmental and economic benefits. However, traditional hot mix rubber asphalt needs to be carried out at high temperature during the construction process, which not only consumes a lot of energy, but also produces harmful gases and pollutes the environment. In order to solve these problems, warm mix rubber asphalt technology came into being. As a new type of modified material, warm mix rubber asphalt has been widely used in road construction to improve the crack resistance, fatigue resistance and aging resistance of asphalt.

[0003] Since the compatibility of warm mix rubber asphalt obtained by using different warm mix agents is different, it is necessary to evaluate the compatibility of the produced warm mix rubber asphalt. The existing compatibility evaluation of warm mix rubber asphalt mainly relies on traditional test methods, such as physical property test and mechanical property test. These test methods have long experimental time, high cost, and the test conditions are difficult to fully control. It can be seen that the compatibility evaluation results are greatly affected by external environmental factors, resulting in low accuracy of the compatibility evaluation results. Summary of the invention

[0004] In this context, embodiments of the present invention are intended to provide a method and device for evaluating the compatibility of warm mix rubber asphalt based on molecular simulation.

[0005] In a first aspect of an embodiment of the present invention, a method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation is provided, comprising:

[0006] Constructing a warm mix rubber asphalt molecular model; wherein the warm mix rubber asphalt molecular model is constructed based on a rubber powder molecular model and a warm mix agent molecular model;

[0007] Performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain performance parameters of the warm mix rubber asphalt; wherein the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include solubility parameters, binding energy and glass transition temperature;

[0008] A normalization matrix is ​​determined based on the performance parameter; wherein the normalization matrix is ​​a 3×3 matrix; each row and each column of the normalization matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters;

[0009] Using the normalized matrix, a first weight coefficient of the solubility parameter, a second weight coefficient of the binding energy, and a third weight coefficient of the glass transition temperature are calculated;

[0010] Based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient, a compatibility evaluation result of the warm mix rubber asphalt is determined.

[0011] In one example of this implementation, constructing a warm mix rubber asphalt molecular model includes:

[0012] Constructing the initial warm mix rubber asphalt molecular model;

[0013] Obtaining the simulated density and radial distribution function of the initial warm mix rubber asphalt molecular model;

[0014] Using the simulated density and a predetermined standard density, a simulated error ratio is calculated;

[0015] determining a simulated peak value of the radial distribution function;

[0016] When the simulated error ratio is greater than the preset error ratio or the simulated peak value is less than the preset peak value, the following steps are repeatedly performed:

[0017] The initial warm mix rubber asphalt molecular model is adjusted to obtain an adjusted warm mix rubber asphalt molecular model; a simulated density and a radial distribution function of the adjusted warm mix rubber asphalt molecular model are obtained; a simulated error ratio is calculated using the simulated density and a predetermined standard density; and a simulated peak value of the radial distribution function is determined;

[0018] Until the simulation error ratio is less than or equal to the preset error ratio and the simulation peak value is greater than or equal to the preset peak value, the adjusted warm-mix rubber asphalt molecular model is determined as the final warm-mix rubber asphalt molecular model.

[0019] In one embodiment of this implementation, the dynamic simulation of the warm mix rubber asphalt analysis model is performed to obtain the performance parameters of the warm mix rubber asphalt, including:

[0020] Obtaining the intermolecular cohesive energy and molar volume of warm mix rubber asphalt from the warm mix rubber asphalt analysis model;

[0021] Using the intermolecular cohesive energy and the molar volume, the solubility parameter of the warm mix rubber asphalt is calculated;

[0022] Performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain the binding energy and glass transition temperature of the warm mix rubber asphalt;

[0023] The solubility parameter, the binding energy and the glass transition temperature are determined as the performance parameters of the warm mix rubber asphalt.

[0024] In one example of this implementation, the dynamic simulation of the warm mix rubber asphalt analysis model is performed to obtain the binding energy and glass transition temperature of the warm mix rubber asphalt, including:

[0025] Obtaining the combined total energy, rubber total energy, asphalt total energy and material density of the warm mix rubber asphalt from the warm mix rubber asphalt analysis model;

[0026] Using the total binding energy, the total rubber energy and the total asphalt energy, the binding energy of the warm mix rubber asphalt is calculated;

[0027] The glass transition temperature of the warm mix rubber asphalt is calculated using the material density.

[0028] In an example of this implementation manner, determining a normalization matrix based on the performance parameter includes:

[0029] Obtaining a preset judgment matrix matching the performance parameter; wherein the judgment matrix is ​​a 3×3 matrix; each row and each column of the judgment matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters;

[0030] Performing a conversion operation on each judgment element in the judgment matrix in turn until the last judgment element in the judgment matrix is ​​converted, thereby obtaining a normalized matrix; wherein the sum of all elements in each column of the normalized matrix is ​​1;

[0031] And, the conversion operation comprises the following steps:

[0032] Determine a target row and a target column where a target judgment element is located in the judgment matrix;

[0033] Calculating the sum of all judgment elements in the target column in the judgment matrix to obtain a target sum;

[0034] Calculate the ratio of the target judgment element to the target sum;

[0035] The ratio is determined as a normalized element located at the target row and the target column in the normalized matrix.

[0036] In one example of this implementation, the first weight coefficient of the solubility parameter, the second weight coefficient of the binding energy, and the third weight coefficient of the glass transition temperature are calculated using the normalized matrix, including:

[0037] Calculate the average value of all elements in each row of the normalized matrix;

[0038] Determine an average value of a current row in the normalized matrix corresponding to the solubility parameter as a first weight coefficient of the solubility parameter;

[0039] Determine an average value of a current row in the normalized matrix corresponding to the binding energy as a second weight coefficient of the binding energy;

[0040] The average value of the current row in the normalized matrix corresponding to the glass transition temperature is determined as a third weight coefficient of the glass transition temperature; wherein the sum of the first weight coefficient, the second weight coefficient and the third weight coefficient is 1.

[0041] In one example of this implementation, the compatibility evaluation result of the warm mix rubber asphalt is determined based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient, including:

[0042] Standardizing the solubility parameter, the binding energy, and the glass transition temperature to obtain a standardized solubility parameter, a standardized binding energy, and a standardized glass transition temperature;

[0043] Calculating the compatibility parameter of the warm mix rubber asphalt based on the standardized solubility parameter, the first weight coefficient, the standardized binding energy, the second weight coefficient, the standardized glass transition temperature and the third weight coefficient;

[0044] The compatibility grade corresponding to the compatibility parameter is determined as the compatibility evaluation result of the warm mix rubber asphalt.

[0045] In one example of this embodiment, the solubility parameter, the binding energy, and the glass transition temperature are standardized to obtain a standardized solubility parameter, a standardized binding energy, and a standardized glass transition temperature, including:

[0046] obtaining a predetermined minimum solubility parameter, a maximum solubility parameter, a minimum binding energy, a maximum binding energy, a minimum glass transition temperature, and a maximum glass transition temperature;

[0047] Using the solubility parameter, the minimum solubility parameter and the maximum solubility parameter, a standardized solubility parameter is calculated;

[0048] Using the binding energy, the minimum binding energy and the maximum binding energy, a normalized binding energy is calculated;

[0049] Using the glass transition temperature, the minimum glass transition temperature, and the maximum glass transition temperature, a normalized glass transition temperature is calculated.

[0050] In one example of this implementation, the calculation formula for the compatibility parameter of the warm mix rubber asphalt is:

[0051] S=W δ ·δ W +W G ·G w +W Tg ·Tg W

[0052] Wherein, S represents the compatibility parameter, W δ is the first weight coefficient, W G is the second weight coefficient, W Tg is the third weight coefficient, δ W is the standardized solubility parameter, G W is the normalized binding energy, Tg W is the normalized glass transition temperature.

[0053] In a second aspect of the present invention, a molecular simulation-based warm mix rubber asphalt compatibility evaluation device is provided, comprising:

[0054] A construction unit is used to construct a warm mix rubber asphalt molecular model; wherein the warm mix rubber asphalt molecular model is constructed based on a rubber powder molecular model and a warm mix agent molecular model;

[0055] A simulation unit, used for performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain performance parameters of the warm mix rubber asphalt; wherein the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include solubility parameters, binding energy and glass transition temperature;

[0056] A first determining unit is configured to determine a normalized matrix based on the performance parameter; wherein the normalized matrix is ​​a 3×3 matrix; each row and each column of the normalized matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters;

[0057] a calculation unit, configured to calculate a first weight coefficient of the solubility parameter, a second weight coefficient of the binding energy, and a third weight coefficient of the glass transition temperature using the normalized matrix;

[0058] The second determination unit is used to determine the compatibility evaluation result of the warm mix rubber asphalt based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient.

[0059] In a third aspect of an embodiment of the present invention, a computing device is provided, comprising: at least one processor, a memory, and an input-output unit; wherein the memory is used to store a computer program, and the processor is used to call the computer program stored in the memory to execute any one of the methods described in the first aspect.

[0060] In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, which includes instructions, and when the instructions are executed on a computer, the computer executes the method described in any one of the first aspects.

[0061] In a fifth aspect of the embodiments of the present invention, a computer program product is provided, comprising a computer program, which implements any one of the methods in the first aspect when executed by a processor.

[0062] According to the molecular simulation-based compatibility evaluation method and device for warm mix rubber asphalt of the embodiment of the present invention, a structurally stable and energy-minimum warm mix rubber asphalt molecular model for molecular dynamics simulation calculation can be constructed, and then the solubility parameter, binding energy, glass transition temperature and other performance parameters of the warm mix rubber asphalt can be simulated and calculated. The obtained performance parameters can be used to evaluate the compatibility between each warm mix agent-rubber-asphalt molecules in the warm mix rubber asphalt; and based on the above three parameters, the influence ratio of the three parameters on the compatibility evaluation of warm mix rubber asphalt is determined; thereby, a weighted characterization method for evaluating warm mix rubber asphalt is established, which is suitable for evaluating the compatibility between each warm mix agent-rubber-asphalt molecules in the warm mix rubber asphalt, and comprehensively reveals the compatibility mechanism of warm mix rubber asphalt from the molecular scale, so that the compatibility evaluation results are not affected by external environmental factors, thereby improving the accuracy of the compatibility evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, in which:

[0064] Figure 1 A schematic flow chart of a method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation provided by one embodiment of the present invention;

[0065] Figure 2 A schematic diagram of a rubber powder molecular model provided by one embodiment of the present invention;

[0066] Figure 3 Schematic diagram of two molecular models of warm mix agents provided in one embodiment of the present invention;

[0067] Figure 4 A schematic diagram of a molecular model of SDYK warm mix rubber asphalt provided in one embodiment of the present invention;

[0068] Figure 5 A schematic diagram of an EM type warm mix rubber asphalt molecular model provided by one embodiment of the present invention;

[0069] Figure 6 A schematic diagram of simulating the intramolecular energy stabilization of warm mix rubber asphalt provided by one embodiment of the present invention;

[0070] Figure 7 A schematic diagram of density variation of SDYK type warm mix rubber asphalt and EM type warm mix rubber asphalt provided in one embodiment of the present invention;

[0071] Figure 8 A schematic diagram of verifying the radial distribution function of warm mix rubber asphalt provided by an embodiment of the present invention;

[0072] Fig. 9 A schematic diagram of the difference in solubility between SDYK type warm mix rubber asphalt and EM type warm mix rubber asphalt provided in one embodiment of the present invention;

[0073] Fig.10 A schematic diagram of the relationship between the binding energy and temperature of common rubber asphalt, SDYK type warm mix rubber asphalt and EM type warm mix rubber asphalt provided in one embodiment of the present invention;

[0074] Fig.11 A schematic diagram of the relationship between the specific volume and temperature of common rubber asphalt and EM type warm mix rubber asphalt provided in one embodiment of the present invention;

[0075] Fig.12 A schematic diagram of the relationship between the specific volume and temperature of common rubber asphalt and SDYK type warm mix rubber asphalt provided in one embodiment of the present invention;

[0076] Fig.13 A schematic structural diagram of a warm mix rubber asphalt compatibility evaluation device based on molecular simulation provided by one embodiment of the present invention;

[0077] Fig.14 A schematic diagram of the structure of a medium according to an embodiment of the present invention is schematically shown;

[0078] Fig.15 A schematic diagram of the structure of a computing device according to an embodiment of the present invention is schematically shown.

[0079] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0080] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0081] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0082] According to an embodiment of the present invention, a method and device for evaluating the compatibility of warm mix rubber asphalt based on molecular simulation are proposed.

[0083] It should be noted that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction and does not have any limiting meaning.

[0084] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0085] Exemplary Methods

[0086] Reference below Figure 1 , Figure 1 This is a flow chart of a method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation provided by an embodiment of the present invention. It should be noted that the embodiments of the present invention can be applied to any applicable scenario.

[0087] Figure 1 The process of the warm mix rubber asphalt compatibility evaluation method based on molecular simulation provided by one embodiment of the present invention includes:

[0088] Step S101, constructing a warm mix rubber asphalt molecular model.

[0089] In an embodiment of the present invention, the warm-mix rubber asphalt molecular model is constructed based on a rubber powder molecular model and a warm-mix agent molecular model. The warm-mix rubber asphalt molecular model, the rubber powder molecular model and the warm-mix agent molecular model can be constructed based on actual materials. The warm-mix rubber asphalt molecular model can be constructed based on Panjin 90# base asphalt and adding 20% ​​of its mass fraction of rubber powder and warm-mix agent. The rubber powder is natural rubber and styrene-butadiene rubber in a ratio of 3:7, and 1% of the mass fraction of the viscosity-reducing warm-mix agent EM is added thereto to prepare EM type warm-mix rubber asphalt, or 0.6% of the mass fraction of the surfactant warm-mix agent SDYK is added to prepare SDYK type warm-mix rubber asphalt. The chemical composition of EM viscosity-reducing warm mix agent is mainly a mixture of saturated hydrocarbons, specifically long-chain aliphatic hydrocarbons. This warm mix agent is usually a solid white powdery substance, which achieves the warm mix effect by reducing the viscosity of asphalt; the molecular structure of SDYK surfactant-type warm mix agent consists of two parts, one is a hydrophilic head, which usually contains polar functional groups, and the other is a hydrophobic tail, which is usually composed of long-chain alkyl or aromatic compounds.

[0090] In the embodiment of the present invention, the rubber powder molecular model can be constructed based on waste tires, and the rubber components of the waste tire rubber powder are mainly styrene-butadiene rubber and natural rubber, with a mass ratio of 3:7. Natural rubber is a homopolymer composed of natural rubber repeating units, and styrene-butadiene rubber is a random copolymer produced by low-temperature emulsion polymerization of butadiene and styrene, wherein butadiene includes trans-1-4 butadiene, cis-1-4 butadiene and 1,2 butadiene.

[0091] For example, through the three major index experiments, the 25℃ penetration (0.1mm), softening point (℃) and 5℃ elongation (cm) of EM type warm mix rubber asphalt and SDYK type warm mix rubber asphalt were measured; the density and solubility parameters of EM type warm mix rubber asphalt and SDYK type warm mix rubber asphalt were measured. All test results are shown in Table 1.

[0092] Table 1 Basic test indicators

[0093]

[0094] In the embodiment of the present invention, a rubber powder molecular model can be constructed according to the data in Table 1, and a viscosity-reducing warm mix agent EM warm mix agent molecular model and a surface-active warm mix agent SDYK warm mix agent molecular model can be constructed according to the different chemical compositions of the warm mix agent.

[0095] Please also read Figure 2The rubber powder molecular model can be constructed in the following way: styrene butadiene rubber is polymerized into a styrene butadiene rubber single chain according to a preset ratio, 15 natural rubber repeating units are polymerized into a natural rubber single chain, the structure and energy of the styrene butadiene rubber single chain and the natural rubber single chain are firstly optimized respectively, and then the rubber powder molecular group model is constructed according to the ratio of styrene butadiene rubber single chain to natural rubber single chain of 3:7.

[0096] Please also read Figure 3 , Figure 3 A schematic diagram of a warm-mix agent molecular model of a viscosity-reducing warm-mix agent EM and a molecular model of a surfactant-type warm-mix agent SDYK provided in one embodiment of the present invention; wherein the EM warm-mix agent molecule is an aliphatic hydrocarbon, and the EM representative molecular model is constructed based on the FTIR and AFM test data of the research group; the SDYK warm-mix agent molecule adopts a long-chain aliphatic imidazoline, and the SDYK warm-mix agent molecular model is constructed based on the representative molecule of the surfactant-type warm-mix agent.

[0097] Please also read Figure 4 and Figure 5 , the construction method of the SDYK type warm mix rubber asphalt molecular model and the EM type warm mix rubber asphalt molecular model can be: based on the gel chromatography (GPC) test, the contents of the four components of the 90# matrix asphalt are determined and simulated, and the final contents of the four components are shown in Table 2;

[0098] Table 2 Content of four components

[0099]

[0100] According to the proportion of the experimental design, the rubber powder content is 20% of the mass of the base asphalt, the viscosity-reducing warm mix agent EM content is 1%, and the surfactant warm mix agent SDYK content is 0.6%. These molecular information are placed in a 3D periodic cubic box with an initial density of 1.0 g / cm3, assembled according to the proportion of each molecule, and the construction tool provided by the software is used to manually adjust the distance and angle between molecules to ensure that the geometric structure of the model meets the actual physical conditions. The addition quantities are shown in Table 3, and the SDYK type warm mix rubber asphalt molecular model and the EM type warm mix rubber asphalt molecular model are obtained.

[0101] Table 3 Addition quantity of various molecules

[0102]

[0103] As an optional implementation, the method of constructing the warm mix rubber asphalt molecular model in step S101 may include:

[0104] Constructing the initial warm mix rubber asphalt molecular model;

[0105] Obtaining the simulated density and radial distribution function of the initial warm mix rubber asphalt molecular model;

[0106] Using the simulated density and a predetermined standard density, a simulated error ratio is calculated;

[0107] determining a simulated peak value of the radial distribution function;

[0108] When the simulated error ratio is greater than the preset error ratio or the simulated peak value is less than the preset peak value, the following steps are repeatedly performed:

[0109] The initial warm mix rubber asphalt molecular model is adjusted to obtain an adjusted warm mix rubber asphalt molecular model; a simulated density and a radial distribution function of the adjusted warm mix rubber asphalt molecular model are obtained; a simulated error ratio is calculated using the simulated density and a predetermined standard density; and a simulated peak value of the radial distribution function is determined;

[0110] Until the simulation error ratio is less than or equal to the preset error ratio and the simulation peak value is greater than or equal to the preset peak value, the adjusted warm-mix rubber asphalt molecular model is determined as the final warm-mix rubber asphalt molecular model.

[0111] Among them, by implementing this implementation method, by continuously iteratively adjusting the initial model and evaluating the accuracy of the model based on the error ratio between the simulated density and the standard density and the simulated peak value of the radial distribution function, it can be ensured that the final warm mix rubber asphalt molecular model not only meets the expected density standard, but also has reasonable distribution characteristics in the molecular structure. This method effectively improves the construction accuracy of the molecular model and provides a more reliable model basis for subsequent material performance analysis and application research.

[0112] In the embodiment of the present invention, the accuracy of the constructed initial warm mix rubber asphalt molecular model can be verified to make the warm mix rubber asphalt molecular model closer to the actual warm mix rubber asphalt. The accuracy verification is performed by calculating the energy, density and molecular order (i.e. radial distribution function g(r)) of the warm mix rubber asphalt molecular model. The energy of the simulated warm mix rubber asphalt molecule is stable; the error between the simulated density requirement and the actual measured density shall not be greater than 5% (equivalent to a preset error ratio of 5%, i.e. the simulated error ratio cannot be greater than 5%); the simulated molecular order is obtained through the output image, showing short-range order and long-range disorder, which is reasonable.

[0113] For example, the energy, density and molecular order of two initial warm-mix rubber asphalt molecular models were calculated under the condition of room temperature 298K and standard atmospheric pressure to simulate the energy stability of warm-mix rubber asphalt molecules. Figure 6 shown.

[0114] The simulated density is calculated for the initial warm mix rubber asphalt molecular model, and the preset error ratio with the actual measured density is required to be no greater than 5% to meet the requirements. The simulated density changes as follows Figure 7 As shown, the preset error ratio between the predetermined standard density meets the requirement.

[0115] The radial distribution function g(r) represents the probability of other particles appearing at a distance r around a particle. The calculation formula is as follows:

[0116]

[0117] Where: ρ is the simulation density of the model; N is the number of particles in the model; r is the distance from the center of mass of a given molecule.

[0118] By calculating the radial distribution function of warm mix rubber asphalt, the aggregation of warm mix agent-rubber agent-asphalt can be obtained. The larger the simulated peak value of the radial distribution function (reaching the preset peak value), the better the compatibility between the two. The radial distribution function inside the asphalt component can also be used to understand the effect of the addition of warm mix agent on the internal structure of asphalt. The molecular order is obtained through the output image, which shows short-range order and long-range disorder, which is reasonable, such as Figure 8 , and the simulation results are also verified to be reasonable.

[0119] Step S102, performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain performance parameters of the warm mix rubber asphalt.

[0120] In an embodiment of the present invention, the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include solubility parameter, binding energy and glass transition temperature; in addition, the performance parameters may also include test results of mechanical indicators (bulk modulus, shear modulus and elastic modulus, etc.), which can evaluate the mechanical properties of warm-mix rubber asphalt.

[0121] As an optional implementation, step S102 performs dynamic simulation on the warm mix rubber asphalt analysis model to obtain the performance parameters of the warm mix rubber asphalt, which may include:

[0122] Obtaining the intermolecular cohesive energy and molar volume of warm mix rubber asphalt from the warm mix rubber asphalt analysis model;

[0123] Using the intermolecular cohesive energy and the molar volume, the solubility parameter of the warm mix rubber asphalt is calculated;

[0124] Performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain the binding energy and glass transition temperature of the warm mix rubber asphalt;

[0125] The solubility parameter, the binding energy and the glass transition temperature are determined as the performance parameters of the warm mix rubber asphalt.

[0126] Among them, this implementation method extracts key molecular characteristics, such as intermolecular cohesive energy and molar volume, from the warm mix rubber asphalt analysis model, and then calculates the solubility parameters. This step provides an important basis for understanding the dissolution behavior of the material in the solvent. At the same time, the binding energy and glass transition temperature are directly obtained through kinetic simulation. These parameters are crucial for evaluating the mechanical properties and thermal stability of the material. The solubility parameters, binding energy and glass transition temperature are used as the performance parameters of warm mix rubber asphalt. It not only improves the accuracy and comprehensiveness of the evaluation, but also provides a scientific basis for the design, optimization and application of materials, which is helpful to promote the technological progress and application expansion of warm mix rubber asphalt in related fields.

[0127] In the embodiment of the present invention, the solubility parameter is used to reflect the interaction between polymers. The solubility parameter is the square root of the cohesive energy density, and its calculation formula is:

[0128]

[0129] Where δ is the solubility parameter, unit is (J / cm 3 ) 1 / 2 ; E coh is the intermolecular cohesive energy; V is the molar volume, in cm 3 .

[0130] The difference in solubility parameters quoted in this step (such as Fig. 9 The compatibility between different substances can be reflected by the solubility parameter difference. The smaller the difference in solubility parameters, the better the compatibility. Conversely, the compatibility is poor.

[0131] Optionally, the method of performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain the binding energy and glass transition temperature of the warm mix rubber asphalt may include:

[0132] Obtaining the combined total energy, rubber total energy, asphalt total energy and material density of the warm mix rubber asphalt from the warm mix rubber asphalt analysis model;

[0133] Using the total binding energy, the total rubber energy and the total asphalt energy, the binding energy of the warm mix rubber asphalt is calculated;

[0134] The glass transition temperature of the warm mix rubber asphalt is calculated using the material density.

[0135] Among them, the implementation of this embodiment avoids the errors and time-consuming processes that may be introduced in traditional experimental methods by directly obtaining key energy parameters (such as total binding energy, total rubber energy, total asphalt energy) and material density from the warm mix rubber asphalt analysis model. The binding energy calculated using these parameters can accurately reflect the interaction strength between the rubber and asphalt components in the warm mix rubber asphalt, which is crucial for understanding the mechanical properties and durability of the material. At the same time, the glass transition temperature calculated by the material density provides an important basis for evaluating the thermal stability and operating temperature range of the material. This method not only improves the calculation efficiency and accuracy, but also promotes the in-depth development of scientific research on warm mix rubber asphalt materials, and provides strong technical support for the design, optimization and application of materials.

[0136] In the embodiment of the present invention, the binding energy E binding The calculation formula is:

[0137] E binding =(E ab -E a -E b )

[0138] Where: E ab is the total binding energy of the blend molecular system when it is stable; E a is the total energy of the rubber when it reaches stability; E b It is the total energy of asphalt when it reaches stability.

[0139] A positive binding energy value indicates mutual repulsion between the two substances, and a negative binding energy value indicates mutual attraction between the two substances. The larger the absolute value of the binding energy, the better the compatibility between asphalt and other substances.

[0140] For example, using molecular dynamics simulation, the total energy of rubber asphalt, EM type warm mix rubber asphalt and SDYK type warm mix rubber asphalt molecular systems were calculated at temperatures of 325K, 375K, 425K, 475K, 525K, and 575K, as shown in Table 4.

[0141] Table 4 Total energy of each molecular system at different temperatures

[0142]

[0143] The binding energy of each asphalt molecular system is obtained by calculation, such as Fig.10. The results show that the total energy of each asphalt molecular system increases with increasing temperature, and the binding energy changes with the change of temperature. At a temperature of 475K, the absolute value of the binding energy is the largest; the absolute values ​​of the binding energy of warm-mix rubber asphalt are from high to low: SDYK type warm-mix rubber asphalt, EM type warm-mix rubber asphalt, and rubber asphalt, indicating that the addition of warm-mix agent improves the compatibility of rubber asphalt, among which SDYK has a better improvement effect. From the results of molecular dynamics simulation, it can be seen that the addition of warm-mix agent EM and SDYK increases the absolute value of the binding energy of rubber asphalt and improves the compatibility between rubber and asphalt. Compared with EM, the absolute value of the binding energy of rubber asphalt is larger after SDYK is added, which indicates that the interaction force between molecules in the system is stronger and the molecules are not easily separated or destroyed, so the system exhibits good compatibility or mutual solubility.

[0144] In the embodiment of the present invention, asphalt, as a viscoelastic material, is relatively sensitive to temperature changes. As the temperature changes from low to high, it will present three mechanical states, namely, glass state, highly elastic state and viscous flow state.

[0145] In the glassy state, the material has a relatively high modulus, deforms very little under external force, is highly brittle, and has a transition temperature called the glass transition temperature Tg.

[0146] By calculating the model at different temperatures, the relationship curves of the volume ratio and temperature of rubber powder modified asphalt and warm mix rubber powder modified asphalt were simulated (such as Fig.11 and Fig.12 The specific volume calculation formula (as shown below) is used to calculate the glass transition temperature Tg.

[0147]

[0148] Where: V b is the specific volume, ρ is the material density, the unit is g / cm 3 .

[0149] For example, by performing molecular dynamics simulation on each asphalt molecular model, the volume-temperature relationship curve of rubber asphalt and warm mix rubber asphalt was obtained, and the glass transition temperature Tg was calculated by the linear fitting equation Tg=a+b*x (a is the intercept of the data fitting, b is the slope of the data fitting), and the correlation coefficient R2 was obtained to be above 0.98.

[0150] The results show that the addition of warm mix agent will change the glass transition temperature of rubber modified asphalt. SDYK warm mix agent reduces the glass transition temperature of rubber asphalt, while EM warm mix agent increases the glass transition temperature of rubber asphalt.

[0151] The addition of warm mix agent changes the glass transition temperature of warm mix rubber asphalt and improves the compatibility between rubber and asphalt. It is inferred that the change in glass transition temperature is attributed to the change in compatibility between various molecules in the warm mix rubber asphalt system. Compared with warm mix agent EM, warm mix agent SDYK-rubber-asphalt has better interaction, better compatibility between component molecules, and lower glass transition point temperature.

[0152] Step S103: determining a normalization matrix based on the performance parameters.

[0153] In an embodiment of the present invention, the normalized matrix is ​​a 3×3 matrix; each row and each column of the normalized matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters.

[0154] As an optional implementation, the method of determining the normalization matrix based on the performance parameter in step S103 may specifically be:

[0155] Obtaining a preset judgment matrix matching the performance parameter; wherein the judgment matrix is ​​a 3×3 matrix; each row and each column of the judgment matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters;

[0156] Performing a conversion operation on each judgment element in the judgment matrix in turn until the last judgment element in the judgment matrix is ​​converted, thereby obtaining a normalized matrix; wherein the sum of all elements in each column of the normalized matrix is ​​1;

[0157] And, the conversion operation comprises the following steps:

[0158] Determine a target row and a target column where a target judgment element is located in the judgment matrix;

[0159] Calculating the sum of all judgment elements in the target column in the judgment matrix to obtain a target sum;

[0160] Calculate the ratio of the target judgment element to the target sum;

[0161] The ratio is determined as a normalized element located at the target row and the target column in the normalized matrix.

[0162] Among them, the implementation of this implementation method ensures that each sub-performance parameter has a unique and clear corresponding position in the matrix by pre-setting a 3×3 judgment matrix that accurately matches the performance parameters, laying a solid foundation for the subsequent naturalization processing. Secondly, by performing conversion operations on each judgment element in the judgment matrix one by one until all are completed, this process is not only meticulous, but also ensures the comprehensiveness and accuracy of the naturalization processing. More importantly, the conversion operation determines the normalized elements at the corresponding positions in the normalization matrix by calculating the ratio of the target judgment element to the target sum. This method ensures that the sum of each column element of the normalization matrix is ​​1, that is, column normalization is achieved, making the comparison and weight distribution between different sub-performance parameters more scientific and reasonable. In general, this implementation method not only improves the efficiency and accuracy of the naturalization processing, but also provides more reliable and effective data support for subsequent performance evaluation or comprehensive scoring.

[0163] In the embodiment of the present invention, a hypothesis may be proposed first to construct a judgment matrix matching the performance parameters:

[0164] The solubility parameter (δ) is more important for the binding energy (G), but the difference is not significant;

[0165] The binding energy (G) and glass transition temperature (Tg) have a comparable influence on the target;

[0166] The solubility parameter (δ) has a greater influence on the glass transition temperature (Tg) than the binding energy (G).

[0167] The judgment matrix constructed in this way is shown in Table 5.

[0168] Note: Solubility parameter is considered to be twice as important to binding energy;

[0169] The binding energy has an equal influence on the glass transition temperature, so the value is assigned to 1;

[0170] The solubility parameter is considered to be more important than the glass transition temperature and is assigned a value of 3.

[0171] Table 5 Weight coefficient judgment matrix

[0172] Solubility parameter (δ) Binding energy (G) Glass transition temperature (Tg) Solubility parameter (δ) 1 2 3 Binding energy (G) 1 / 2 1 1 Glass transition temperature (Tg) 1 / 3 1 1

[0173] In the embodiment of the present invention, the normalization matrix is ​​shown in Table 6:

[0174] Table 6 Normalization matrix

[0175]

[0176] For example, in the judgment matrix, the target judgment element with target behavior 1 and target column 1 is 1, and the target sum of all judgment elements in column 1 of the judgment matrix is The ratio of the target judgment element to the target sum is calculated as 0.545 is determined as the normalized element located at target row 1 and target column 1 in the normalized matrix.

[0177] Step S104, using the normalized matrix to calculate the first weight coefficient of the solubility parameter, the second weight coefficient of the binding energy, and the third weight coefficient of the glass transition temperature

[0178] As an optional implementation manner, the method of using the normalized matrix to calculate the first weight coefficient of the solubility parameter, the second weight coefficient of the binding energy, and the third weight coefficient of the glass transition temperature in step S104 may include:

[0179] Calculate the average value of all elements in each row of the normalized matrix;

[0180] Determine an average value of a current row in the normalized matrix corresponding to the solubility parameter as a first weight coefficient of the solubility parameter;

[0181] Determine an average value of a current row in the normalized matrix corresponding to the binding energy as a second weight coefficient of the binding energy;

[0182] The average value of the current row in the normalized matrix corresponding to the glass transition temperature is determined as a third weight coefficient of the glass transition temperature; wherein the sum of the first weight coefficient, the second weight coefficient and the third weight coefficient is 1.

[0183] Wherein, this implementation method is implemented, and the weight coefficients of different properties are determined respectively by directly calculating the average value of each corresponding row in the normalization matrix, which not only simplifies the calculation process, improves the calculation efficiency, but also ensures that the determination of the weight coefficient has objectivity and accuracy. Since the weight coefficient is directly calculated based on the data of the normalization matrix, it can better reflect the importance of each property in the overall assessment, and avoids the subjectivity and uncertainty of artificial assignment. In addition, the method ensures that the sum of the first weight coefficient, the second weight coefficient and the third weight coefficient is 1, meets the basic requirements of the weight coefficient, and provides a reliable basis for subsequent comprehensive evaluation.

[0184] In the embodiment of the present invention, the average value of each row of the normalized matrix is ​​calculated to obtain the weight coefficient:

[0185] The first weight coefficient W of the solubility parameter (δ) δ Can be: W δ=(0.545+0.5+0.6) / 3=0.548;

[0186] The second weight coefficient W of binding energy (G) G Can be: W G =(0.273+0.25+0.2) / 3=0.241;

[0187] The third weight coefficient W of glass transition temperature (Tg) Tg Can be: W Tg =(0.182+0.25+0.2) / 3=0.211. And, W δ +W G +W Tg =1.

[0188] Step S105, determining a compatibility evaluation result of the warm mix rubber asphalt based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient.

[0189] In the embodiments of the present invention, the solubility parameter measures the ability of different substances to dissolve or be compatible with each other. Smaller solubility differences generally mean better compatibility. If the difference in solubility parameters is small, the compatibility of rubber and asphalt when mixed will be better. Binding energy reflects the strength of interaction between materials. Higher binding energy generally means stronger mutual attraction, which also helps to improve compatibility. The glass transition temperature Tg is the temperature at which a material transitions from brittle (glassy state) to elastic (rubbery state). For the compatibility of warm mix rubber asphalt, closer Tg values ​​generally indicate better compatibility.

[0190] As an optional implementation manner, in step S105, based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient, determining the compatibility evaluation result of the warm mix rubber asphalt may include:

[0191] Standardizing the solubility parameter, the binding energy, and the glass transition temperature to obtain a standardized solubility parameter, a standardized binding energy, and a standardized glass transition temperature;

[0192] Calculating the compatibility parameter of the warm mix rubber asphalt based on the standardized solubility parameter, the first weight coefficient, the standardized binding energy, the second weight coefficient, the standardized glass transition temperature and the third weight coefficient;

[0193] The compatibility grade corresponding to the compatibility parameter is determined as the compatibility evaluation result of the warm mix rubber asphalt.

[0194] Among them, by implementing this implementation method, the solubility parameters, binding energy and glass transition temperature are standardized, which eliminates the influence of the dimensions and value ranges between different parameters, so that they can be compared and weighted on the same scale. The compatibility parameters calculated based on the standardized parameters and the corresponding weight coefficients can comprehensively and objectively reflect the compatibility status between the rubber and asphalt components in warm mix rubber asphalt. Corresponding the compatibility parameters to the compatibility grades not only makes the evaluation results more intuitive and easy to understand, but also provides clear guidance for the design, optimization and application of materials. This method not only improves the accuracy and reliability of compatibility evaluation, but also provides strong technical support for the research and development and application of warm mix rubber asphalt materials.

[0195] Optionally, the solubility parameter, the binding energy and the glass transition temperature are standardized to obtain the standardized solubility parameter, the standardized binding energy and the standardized glass transition temperature, which may include:

[0196] obtaining a predetermined minimum solubility parameter, a maximum solubility parameter, a minimum binding energy, a maximum binding energy, a minimum glass transition temperature, and a maximum glass transition temperature;

[0197] Using the solubility parameter, the minimum solubility parameter and the maximum solubility parameter, a standardized solubility parameter is calculated;

[0198] Using the binding energy, the minimum binding energy and the maximum binding energy, a normalized binding energy is calculated;

[0199] Using the glass transition temperature, the minimum glass transition temperature, and the maximum glass transition temperature, a normalized glass transition temperature is calculated.

[0200] Among them, by implementing this implementation method, the objectivity and accuracy of the standardization process can be ensured by obtaining predetermined minimum and maximum values ​​as references. The standardized solubility parameters, standardized binding energy, and standardized glass transition temperature obtained by calculating the original performance parameters using these reference values ​​not only eliminate the dimensional differences, but also make it possible to compare the performance of warm-mix rubber asphalt materials from different batches or sources. This method not only improves the comparability and interpretability of performance parameters, but also provides a more reliable and scientific basis for subsequent material performance evaluation, quality control, and optimization, which helps to promote in-depth research and development in the field of warm-mix rubber asphalt materials.

[0201] In the embodiment of the present invention, the solubility parameter, the binding energy and the glass transition temperature may be standardized in the following manner:

[0202] The standardized formula for solubility parameters can be:

[0203] Where: s is the solubility parameter of warm mix rubber asphalt simulation calculation; δ min and δ max is the minimum and maximum value of the solubility parameters measured in multiple simulations;

[0204] Where: s is the solubility parameter of warm mix rubber asphalt simulation calculation; δ min and δ max are the minimum solubility parameter and the maximum solubility parameter measured by multiple simulations;

[0205] The normalized formula for binding energy can be:

[0206]

[0207] Where: G s is the binding energy calculated by simulation of warm mix rubber asphalt; G min and G max are the minimum binding energy and maximum binding energy measured from multiple simulations;

[0208] The standardized formula for the glass transition temperature can be:

[0209]

[0210] Where: Tg x is the glass transition temperature of warm mix rubber asphalt simulation calculation; Tg min and Tg max are the minimum glass transition temperature and the maximum glass transition temperature measured by multiple simulations.

[0211] In the embodiment of the present invention, based on the standardized solubility parameter, the first weight coefficient, the standardized binding energy, the second weight coefficient, the standardized glass transition temperature and the third weight coefficient, the calculation formula for the compatibility parameter S of the warm mix rubber asphalt can be:

[0212] S=W ′ ·δ W +W G ·G W +W Tg ·Tg W

[0213] Solubility parameter δ: A lower solubility parameter difference indicates better compatibility between asphalt and rubber, so δ W The closer it is to 1, the better the compatibility.

[0214] Binding energy G: Higher binding energy usually means stronger physical adsorption or adhesion, thus improving compatibility, G W The larger the value, the better the compatibility.

[0215] Glass transition temperature Tg: When the Tg values ​​are close, it means that asphalt and rubber have similar physical properties at similar temperatures, thereby improving compatibility. W The larger the value, the better the compatibility.

[0216] The larger the final compatibility parameter S is, the better the compatibility of the warm mix rubber asphalt is. Specifically, the value ranges corresponding to different compatibility levels can be divided according to the compatibility parameter.

[0217] The present invention can protect the performance evaluation results from the influence of external environmental factors, thereby improving the accuracy of the performance evaluation results. In addition, the present invention can also improve the construction accuracy of the warm-mix rubber asphalt molecular model. In addition, the present invention can also accurately calculate the solubility parameter based on the intermolecular cohesive energy and molar volume. In addition, the present invention can also improve the calculation efficiency and accuracy of the binding energy and the glass transition temperature. In addition, the present invention can also ensure the objectivity and accuracy of the weight distribution. In addition, the present invention can also improve the efficiency of converting the judgment matrix into the normalization matrix. In addition, the present invention can also improve the accuracy and reliability of the compatibility evaluation. In addition, the present invention can also improve the comparability and interpretability of performance parameters.

[0218] Exemplary Devices

[0219] After introducing the method of the exemplary embodiment of the present invention, next, refer to Fig.13 A warm mix rubber asphalt compatibility evaluation device based on molecular simulation according to an exemplary embodiment of the present invention is described, and the device comprises:

[0220] A construction unit 1301 is used to construct a warm mix rubber asphalt molecular model; wherein the warm mix rubber asphalt molecular model is constructed based on a rubber powder molecular model and a warm mix agent molecular model;

[0221] The simulation unit 1302 is used to perform dynamic simulation on the warm mix rubber asphalt analysis model to obtain performance parameters of the warm mix rubber asphalt; wherein the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include solubility parameters, binding energy and glass transition temperature;

[0222] A first determining unit 1303 is configured to determine a normalized matrix based on the performance parameter; wherein the normalized matrix is ​​a 3×3 matrix; each row and each column of the normalized matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters;

[0223] A calculation unit 1304 is used to calculate the first weight coefficient of the solubility parameter, the second weight coefficient of the binding energy, and the third weight coefficient of the glass transition temperature using the normalized matrix;

[0224] The second determining unit 1305 is used to determine the compatibility evaluation result of the warm mix rubber asphalt based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient.

[0225] The present invention can protect the performance evaluation results from being affected by external environmental factors, thereby improving the accuracy of the performance evaluation results.

[0226] Exemplary Media

[0227] After introducing the method and apparatus of the exemplary embodiment of the present invention, next, reference is made to Fig.14 For a description of a computer-readable storage medium according to an exemplary embodiment of the present invention, please refer to Fig.14 , the computer-readable storage medium shown is a CD 140, on which a computer program (i.e., a program product) is stored. When the computer program is executed by the processor, each step described in the above method implementation is implemented, for example, constructing a warm-mix rubber asphalt molecular model; wherein the warm-mix rubber asphalt molecular model is constructed based on a rubber powder molecular model and a warm-mix agent molecular model; performing a dynamic simulation on the warm-mix rubber asphalt analysis model to obtain performance parameters of the warm-mix rubber asphalt; wherein the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include a solubility parameter, a binding energy, and a glass transition temperature; determining a normalization matrix based on the performance parameters; wherein the The normalized matrix is ​​a 3×3 matrix; each row and each column of the normalized matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters; the first weight coefficient of the solubility parameter, the second weight coefficient of the binding energy, and the third weight coefficient of the glass transition temperature are calculated using the normalized matrix; based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient, the compatibility evaluation result of the warm mix rubber asphalt is determined; the specific implementation method of each step will not be repeated here.

[0228] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0229] Exemplary Computing Devices

[0230] After introducing the method, apparatus and medium of the exemplary embodiments of the present invention, next, reference is made to Fig.15 A computing device for evaluating the performance of warm mix rubber asphalt according to an exemplary embodiment of the present invention.

[0231] Fig.15 A block diagram of an exemplary computing device 150 suitable for implementing embodiments of the present invention is shown, and the computing device 150 may be a computer system or a server. Fig.15 The computing device 150 shown is merely an example and should not bring any limitation to the functionality and scope of use of embodiments of the present invention.

[0232] like Fig.15 As shown, the components of computing device 150 may include, but are not limited to: one or more processors or processing units 1501, system memory 1502, and a bus 1503 connecting different system components (including system memory 1502 and processing unit 1501).

[0233] Computing device 150 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computing device 150, including volatile and nonvolatile media, removable and non-removable media.

[0234] System memory 1502 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 15021 and / or cache memory 15022. Computing device 150 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, ROM 15023 may be used to read and write non-removable, non-volatile magnetic media ( Fig.15 is not shown in the Fig.15As shown in FIG. 1 , a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 1503 via one or more data medium interfaces. System memory 1502 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of various embodiments of the present invention.

[0235] A program / utility 15025 having a set (at least one) of program modules 15024 may be stored, for example, in system memory 1502, and such program modules 15024 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 15024 generally perform the functions and / or methods of the embodiments described herein.

[0236] The computing device 150 may also communicate with one or more external devices 1504 (e.g., a keyboard, a pointing device, a display, etc.). Such communication may be performed via an input / output (I / O) interface 1505. In addition, the computing device 150 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 1506. Fig.15 As shown, the network adapter 1506 communicates with other modules (such as the processing unit 1501, etc.) of the computing device 150 via the bus 1503. It should be understood that although Fig.15 Not shown, other hardware and / or software modules may be used in conjunction with computing device 150 .

[0237] The processing unit 1501 executes various functional applications and data processing by running the program stored in the system memory 1502, for example, constructing a molecular model of warm-mix rubber asphalt; wherein the molecular model of warm-mix rubber asphalt is constructed based on a molecular model of rubber powder and a molecular model of a warm-mix agent; performing a dynamic simulation on the warm-mix rubber asphalt analysis model to obtain performance parameters of warm-mix rubber asphalt; wherein the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include a solubility parameter, a binding energy, and a glass transition temperature; determining a normalization matrix based on the performance parameters; wherein the normalization matrix is ​​a 3×3 matrix; each row and each column of the normalization matrix corresponds to a sub-performance parameter in the performance parameter, and the sub-performance parameters corresponding to any two rows are different, and the sub-performance parameters corresponding to any two columns are different; using the normalization matrix to calculate a first weight coefficient of the solubility parameter, a second weight coefficient of the binding energy, and a third weight coefficient of the glass transition temperature; based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature, and the third weight coefficient, determining the compatibility evaluation result of the warm-mix rubber asphalt. The specific implementation of each step will not be repeated here. It should be noted that although several units / modules or sub-units / sub-modules of the warm mix rubber asphalt compatibility evaluation device based on molecular simulation are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be concretized in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided to be concretized by multiple units / modules.

[0238] In the description of the present invention, it should be noted that the terms “first”, “second” and “third” are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0239] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0240] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0241] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0242] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0243] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0244] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

[0245] In addition, although the operations of the method of the present invention are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0246] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

Claims

1. A method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation, characterized in that: include: Constructing a warm mix rubber asphalt molecular model; wherein the warm mix rubber asphalt molecular model is constructed based on a rubber powder molecular model and a warm mix agent molecular model; Performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain performance parameters of the warm mix rubber asphalt; wherein the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include solubility parameters, binding energy and glass transition temperature; A normalization matrix is ​​determined based on the performance parameter; wherein the normalization matrix is ​​a 3×3 matrix; each row and each column of the normalization matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters; Using the normalized matrix, a first weight coefficient of the solubility parameter, a second weight coefficient of the binding energy, and a third weight coefficient of the glass transition temperature are calculated; Based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient, a compatibility evaluation result of the warm mix rubber asphalt is determined.

2. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 1, characterized in that: The method of constructing a warm mix rubber asphalt molecular model comprises: Constructing the initial warm mix rubber asphalt molecular model; Obtaining the simulated density and radial distribution function of the initial warm mix rubber asphalt molecular model; Using the simulated density and a predetermined standard density, a simulated error ratio is calculated; determining a simulated peak value of the radial distribution function; When the simulated error ratio is greater than the preset error ratio or the simulated peak value is less than the preset peak value, the following steps are repeatedly performed: The initial warm mix rubber asphalt molecular model is adjusted to obtain an adjusted warm mix rubber asphalt molecular model; a simulated density and a radial distribution function of the adjusted warm mix rubber asphalt molecular model are obtained; a simulated error ratio is calculated using the simulated density and a predetermined standard density; and a simulated peak value of the radial distribution function is determined; Until the simulation error ratio is less than or equal to the preset error ratio and the simulation peak value is greater than or equal to the preset peak value, the adjusted warm-mix rubber asphalt molecular model is determined as the final warm-mix rubber asphalt molecular model.

3. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 1, characterized in that: The dynamic simulation of the warm mix rubber asphalt analysis model is performed to obtain the performance parameters of the warm mix rubber asphalt, including: Obtaining the intermolecular cohesive energy and molar volume of warm mix rubber asphalt from the warm mix rubber asphalt analysis model; Using the intermolecular cohesive energy and the molar volume, the solubility parameter of the warm mix rubber asphalt is calculated; Performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain the binding energy and glass transition temperature of the warm mix rubber asphalt; The solubility parameter, the binding energy and the glass transition temperature are determined as the performance parameters of the warm mix rubber asphalt.

4. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 3, characterized in that: The method of performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain the binding energy and glass transition temperature of the warm mix rubber asphalt includes: Obtaining the combined total energy, rubber total energy, asphalt total energy and material density of the warm mix rubber asphalt from the warm mix rubber asphalt analysis model; Using the total binding energy, the total rubber energy and the total asphalt energy, the binding energy of the warm mix rubber asphalt is calculated; The glass transition temperature of the warm mix rubber asphalt is calculated using the material density.

5. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 1, characterized in that: The determining of a normalization matrix based on the performance parameter comprises: Obtaining a preset judgment matrix matching the performance parameter; wherein the judgment matrix is ​​a 3×3 matrix; each row and each column of the judgment matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters; Performing a conversion operation on each judgment element in the judgment matrix in turn until the last judgment element in the judgment matrix is ​​converted, thereby obtaining a normalized matrix; wherein the sum of all elements in each column of the normalized matrix is ​​1; And, the conversion operation comprises the following steps: Determine a target row and a target column where a target judgment element is located in the judgment matrix; Calculating the sum of all judgment elements in the target column in the judgment matrix to obtain a target sum; Calculate the ratio of the target judgment element to the target sum; The ratio is determined as a normalized element located at the target row and the target column in the normalized matrix.

6. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 5, characterized in that: The method of using the normalized matrix to calculate the first weight coefficient of the solubility parameter, the second weight coefficient of the binding energy, and the third weight coefficient of the glass transition temperature includes: Calculate the average value of all elements in each row of the normalized matrix; Determine an average value of a current row in the normalized matrix corresponding to the solubility parameter as a first weight coefficient of the solubility parameter; Determine an average value of a current row in the normalized matrix corresponding to the binding energy as a second weight coefficient of the binding energy; The average value of the current row in the normalized matrix corresponding to the glass transition temperature is determined as a third weight coefficient of the glass transition temperature; wherein the sum of the first weight coefficient, the second weight coefficient and the third weight coefficient is 1.

7. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 1, characterized in that: The method of determining the compatibility evaluation result of the warm mix rubber asphalt based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient includes: Standardizing the solubility parameter, the binding energy, and the glass transition temperature to obtain a standardized solubility parameter, a standardized binding energy, and a standardized glass transition temperature; Calculating the compatibility parameter of the warm mix rubber asphalt based on the standardized solubility parameter, the first weight coefficient, the standardized binding energy, the second weight coefficient, the standardized glass transition temperature and the third weight coefficient; The compatibility grade corresponding to the compatibility parameter is determined as the compatibility evaluation result of the warm mix rubber asphalt.

8. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 7, characterized in that: The step of standardizing the solubility parameter, the binding energy, and the glass transition temperature to obtain a standardized solubility parameter, a standardized binding energy, and a standardized glass transition temperature comprises: obtaining a predetermined minimum solubility parameter, a maximum solubility parameter, a minimum binding energy, a maximum binding energy, a minimum glass transition temperature, and a maximum glass transition temperature; Using the solubility parameter, the minimum solubility parameter and the maximum solubility parameter, a standardized solubility parameter is calculated; Using the binding energy, the minimum binding energy and the maximum binding energy, a normalized binding energy is calculated; Using the glass transition temperature, the minimum glass transition temperature, and the maximum glass transition temperature, a normalized glass transition temperature is calculated.

9. The method for evaluating compatibility of warm mix rubber asphalt based on molecular simulation according to claim 7, characterized in that: The calculation formula of the compatibility parameter of the warm mix rubber asphalt is: S=W δ δ W +W G ·G W +W Tg ·Tg W Wherein, S represents the compatibility parameter, W δ is the first weight coefficient, W g is the second weight coefficient, W Tg is the third weight coefficient, δ W is the standardized solubility parameter, G W is the normalized binding energy, Tg W is the normalized glass transition temperature.

10. A warm mix rubber asphalt compatibility evaluation device based on molecular simulation, characterized in that: include: A construction unit is used to construct a warm mix rubber asphalt molecular model; wherein the warm mix rubber asphalt molecular model is constructed based on a rubber powder molecular model and a warm mix agent molecular model; A simulation unit, used for performing dynamic simulation on the warm mix rubber asphalt analysis model to obtain performance parameters of the warm mix rubber asphalt; wherein the performance parameters include at least a plurality of sub-performance parameters, and the sub-performance parameters include solubility parameters, binding energy and glass transition temperature; A first determining unit is configured to determine a normalized matrix based on the performance parameter; wherein the normalized matrix is ​​a 3×3 matrix; each row and each column of the normalized matrix corresponds to a sub-performance parameter in the performance parameter, and any two rows correspond to different sub-performance parameters, and any two columns correspond to different sub-performance parameters; a calculation unit, configured to calculate a first weight coefficient of the solubility parameter, a second weight coefficient of the binding energy, and a third weight coefficient of the glass transition temperature using the normalized matrix; The second determination unit is used to determine the compatibility evaluation result of the warm mix rubber asphalt based on the solubility parameter, the first weight coefficient, the binding energy, the second weight coefficient, the glass transition temperature and the third weight coefficient.

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