Optimized processing method for compound combination used for modified asphalt

Abstract

The present invention discloses a compound combination optimization processing method for modified asphalt, which relates to the technical field of compound optimization. The method includes: determining an asphalt mixed sample and establishing a modified asphalt test model; obtaining a first modification test simulation result for a first composite modification characteristic set; obtaining a second modification test simulation result for a second composite modification characteristic set; introducing a third composite modification characteristic set to predict the modified performance evaluation result of a semi-open graded asphalt mixing process; adjusting the compound ratio in the compound combination processing process, and determining an optimized processing parameter set for processing control. The present invention solves the technical problem that in the processing process of modified asphalt in the prior art, there are unreasonable compound combinations and unreasonable processing parameters, which lead to low performance and quality of the modified asphalt, and achieves the technical effect of optimizing the processing process of modified asphalt and improving the performance and quality of asphalt.

Description

Technical Field

[0001] The invention relates to the technical field of compound optimization, and in particular to a compound combination optimization processing method for modified asphalt. Background Art

[0002] With the continuous development of the transportation industry, the requirements for the quality of road construction are increasing. As a high-performance road material, modified asphalt has been widely used in projects such as highways and airport runways. However, there are still some technical problems in the production and application of modified asphalt. Traditional modified asphalt processing methods often make it difficult to accurately control the combination and ratio of compounds, resulting in unstable performance of asphalt. In addition, the unreasonable selection of processing parameters will also affect the quality of modified asphalt, making it unable to fully exert its excellent performance. For example, in some cases, the performance indicators of modified asphalt such as density, strength, porosity, and water permeability are difficult to reach the ideal state, thus affecting the service life and safety of the road. At the same time, with the continuous improvement of road performance requirements, such as skid resistance and low noise, traditional modified asphalt processing technology has gradually become difficult to meet these new demands. Therefore, an innovative method is urgently needed to optimize the compound combination processing technology of modified asphalt to improve the performance and quality of asphalt and meet the requirements of modern road construction.

[0003] In the prior art, there are technical problems in the processing of modified asphalt, such as unreasonable compound combination and unreasonable processing parameters, which lead to poor performance and quality of the modified asphalt. Summary of the invention

[0004] The present application provides a compound combination optimization processing method for modified asphalt, which is used to solve the technical problems in the prior art that in the processing of modified asphalt, there are unreasonable compound combinations and unreasonable processing parameters, which lead to poor performance and quality of the modified asphalt.

[0005] In view of the above problems, the present application provides a compound combination optimization processing method for modified asphalt, the method comprising: determining M asphalt mixed samples, the M asphalt mixed samples comprising U dense-graded asphalt mixed samples and V open-graded asphalt mixed samples, and M=U+V; at the same time, in a compound combination processing technology composed of a melt mixing method, an emulsification method, and a reactive extrusion method, combining the M asphalt mixed samples, a modified asphalt test model is established; for a first composite modified characteristic set corresponding to the U dense-graded asphalt mixed samples, a modified characteristic analysis is performed in combination with the modified asphalt test model to obtain a first modified test simulation result, the first composite modified characteristic set comprising density and strength; for the V open-graded asphalt The second composite modified characteristic set corresponding to the green mixed sample is combined with the modified asphalt test model to perform modified characteristic analysis to obtain the second modified test simulation result, wherein the second composite modified characteristic set includes porosity and water permeability; the first modified test simulation result and the second modified test simulation result are compared, and the third composite modified characteristic set corresponding to the asphalt mastic gravel mixing process is introduced to evaluate the modified characteristics of the semi-open gradation asphalt mixing process, and predict the modified performance evaluation result of the semi-open gradation asphalt mixing process; based on the modified performance evaluation result, the compound ratio in the compound combination processing process is adjusted, and the process parameters are optimized according to the preset standards, and the optimized processing parameter set is determined for processing control.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] Determine M asphalt mixed samples; at the same time, in the compound combination processing technology composed of melt mixing method, emulsification method and reactive extrusion method, combine the M asphalt mixed samples to establish a modified asphalt test model; for the first composite modified characteristic set, perform modified characteristic analysis to obtain the first modified test simulation result; for the second composite modified characteristic set, perform modified characteristic analysis to obtain the second modified test simulation result; introduce the third composite modified characteristic set to evaluate the modified characteristics of the semi-open graded asphalt mixed processing technology, predict the modified performance evaluation result of the semi-open graded asphalt mixed processing technology, adjust the compound ratio in the compound combination processing technology, and optimize the process parameters according to the preset standards, and determine the optimized processing parameter set for processing control. The processing technology of the modified asphalt is optimized, and the performance and quality technical effect of the asphalt are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic diagram of a process for optimizing the compound combination processing method for modified asphalt provided in an embodiment of the present application;

[0010] Figure 2 A schematic diagram of a process for obtaining a first modification test simulation result in a compound combination optimization processing method for modified asphalt provided in an embodiment of the present application. DETAILED DESCRIPTION

[0011] The present application provides a compound combination optimization processing method for modified asphalt, which is used to solve the technical problems in the prior art that in the processing of modified asphalt, there are unreasonable compound combinations and unreasonable processing parameters, which lead to poor performance and quality of the modified asphalt.

[0012] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0013] Examples, such as Figure 1 As shown, the present application provides a compound combination optimization processing method for modified asphalt, the method comprising:

[0014] Step S100: Determine M asphalt mixture samples, wherein the M asphalt mixture samples include U dense-graded asphalt mixture samples and V open-graded asphalt mixture samples, and M=U+V.

[0015] Specifically, M asphalt mixture samples are determined, and these samples are divided into two categories, namely U dense-graded asphalt mixture samples and V open-graded asphalt mixture samples. It should be pointed out that there is a clear quantitative relationship between M and U and V, that is, M is equal to the sum of U and V. In order to accurately complete this task, the asphalt mixture samples need to be carefully screened and classified. First, a sufficient number of asphalt samples need to be collected and divided into two types, dense-graded and open-graded, according to their characteristics. In the classification process, it is necessary to ensure that each sample can be accurately classified into the corresponding category, and the specific number of U and V is counted. Finally, through simple mathematical calculations, we can determine the value of M, thereby ensuring the integrity and accuracy of the M asphalt mixture samples. This step provides an important basis for subsequent research and analysis, ensuring that different types of asphalt mixture samples can be targeted and studied.

[0016] Step S200: At the same time, in the compound combination processing technology composed of the melt mixing method, the emulsification method and the reactive extrusion method, the M asphalt mixed samples are combined to establish a modified asphalt test model.

[0017] Specifically, the focus is on the compound combination processing technology composed of melt mixing, emulsification, and reactive extrusion. Each of these processing technologies has unique characteristics and functions, and can effectively modify asphalt. First, the melt mixing method changes the properties of asphalt by melting asphalt and other compounds at high temperature and fully mixing them so that they interact with each other. The emulsification method is to mix asphalt with emulsifiers and water to form a stable emulsion, which can improve the adhesion and stability of asphalt. The reactive extrusion method promotes chemical reactions between asphalt and other compounds during the extrusion process, further improving the performance of asphalt. Next, M asphalt mixed samples are combined with these processing technologies. For each asphalt mixed sample, its composition, properties and characteristics are analyzed in detail to determine the most suitable processing technology combination. Then, a modified asphalt test model is established. Here, a neural network model is used. The relevant data of the asphalt mixed sample is used as input, including the composition of the sample, processing parameters, etc. The neural network model automatically learns the complex relationship between these input data and the asphalt modification performance. When establishing a neural network model, the structure of the model is first determined, including the number of layers and nodes of the input layer, hidden layer, and output layer. Then, a large amount of historical data is used to train the model. During the training process, the model will continuously adjust the weights and biases to minimize the error between the predicted value and the actual value. Through repeated training and optimization, the neural network model can gradually and accurately predict the modified performance of different asphalt mixed samples under specific processing technology. In this way, this model can be used to evaluate and optimize the compound combination processing technology to achieve the best modification effect. In short, by combining the compound combination processing technology and asphalt mixed samples to establish a neural network model, we can have a deeper understanding and optimization of the production process of modified asphalt and improve the performance and quality of asphalt.

[0018] Step S300: For the first composite modified characteristic set corresponding to the U dense-graded asphalt mixed samples, modifying characteristic analysis is performed in combination with the modified asphalt test model to obtain a first modified test simulation result, wherein the first composite modified characteristic set includes density and strength.

[0019] Specifically, an in-depth study will be conducted on U dense-graded asphalt mixed samples, which have corresponding first composite modified characteristic sets, including the critical density and strength characteristics. In order to fully understand the modified characteristics of these samples, they will be analyzed in combination with the modified asphalt test model established previously, which can simulate the modification process of asphalt under different conditions and provide accurate test data. In the specific operation, the relevant parameters of the dense-graded asphalt mixed samples are input into the modified asphalt test model, and the model will simulate and analyze the modified characteristics of the samples in terms of density and strength based on these parameters. Through a series of complex calculations and simulations, the model will output the first modified test simulation results, which will reflect the performance of the dense-graded asphalt mixed samples after modification, including the specific values ​​of density and strength and their changing trends. By obtaining the first modified test simulation results, we can have a deep understanding of the modified characteristics of the dense-graded asphalt mixed samples, providing an important basis for subsequent optimization and improvement.

[0020] Step S400: for the second composite modified characteristic set corresponding to the V open-graded asphalt mixed samples, modifying characteristic analysis is performed in combination with the modified asphalt test model to obtain a second modified test simulation result, wherein the second composite modified characteristic set includes porosity and water permeability.

[0021] Specifically, work will be carried out on V open-graded asphalt mixed samples, which have corresponding second composite modified characteristic sets, including two important characteristics: porosity and permeability. The modified asphalt test model established previously will be combined to analyze the modified characteristics of these samples. First, the relevant data of the open-graded asphalt mixed samples are input into the modified asphalt test model. These data include characteristic parameters such as sample composition, porosity and permeability. The modified asphalt test model will simulate and analyze based on the input data. Considering the unique properties of the open-graded asphalt mixed samples and the effects of porosity and permeability on the modified characteristics, we can obtain the second modified test simulation results through the calculation and analysis of the model. This simulation result will reflect the performance of the open-graded asphalt mixed samples after modification, especially the changes in porosity and permeability. For example, the model may predict how the porosity of the sample decreases and how the permeability decreases under specific modification conditions, thereby evaluating the modification effect. By analyzing the simulation results of the second modification test, we can gain an in-depth understanding of the modification characteristics of the open-graded asphalt mixed samples, providing an important reference basis for subsequent research and application, which will help optimize the modification process, improve the performance of asphalt, and meet different engineering needs.

[0022] Step S500: By comparing the first modification test simulation result and the second modification test simulation result, a third composite modification characteristic set corresponding to the mastic asphalt crushed stone mixing process is introduced to evaluate the modification characteristics of the semi-open gradation asphalt mixing process, and predict the modification performance evaluation result of the semi-open gradation asphalt mixing process.

[0023] Specifically, the neural network model is used to compare the first modification test simulation results and the second modification test simulation results, and combined with the third composite modification characteristic set corresponding to the asphalt mastic crushed stone mixing process, the modification characteristics of the semi-open gradation asphalt mixing process are evaluated and the modification performance evaluation results are predicted. First, the first modification test simulation results (density, strength and other characteristic data of dense gradation asphalt mixed samples) and the second modification test simulation results (void ratio, water permeability and other characteristic data of open gradation asphalt mixed samples) and the various characteristic data in the third composite modification characteristic set are sorted and preprocessed, including data normalization, removal of outliers and other operations to ensure the quality and validity of the data. Next, a neural network model multilayer perceptron (MLP) is constructed, and the input layer receives the data in the first modification test simulation results, the second modification test simulation results and the third composite modification characteristic set. Each input node corresponds to a characteristic variable, and the hidden layer processes the input data through nonlinear transformation, extracts features and gradually learns the complex relationships in the data, and the output layer generates the modification performance evaluation results of the semi-open gradation asphalt mixing process. When training the neural network model, a large number of existing data samples are used, and the input data and the corresponding known modified performance evaluation results are used as training sets. The weights and biases of the network are continuously adjusted through the back propagation algorithm to minimize the error between the predicted value and the actual value. The performance of the model can be measured using loss functions such as mean square error (MSE), and optimization algorithms such as stochastic gradient descent (SGD) are used to update the network parameters. After multiple iterations of training, when the performance of the model on the validation set reaches a satisfactory level, it is considered that the model has learned the rules in the data. At this time, the new first modification test simulation results, the second modification test simulation results, and the data in the third composite modification characteristic set can be input into the trained neural network model to obtain the predicted value of the modified performance evaluation results of the semi-open graded asphalt mixing process.

[0024] Step S600: Based on the modified performance evaluation result, the compound ratio in the compound combination processing technology is adjusted, and the process parameters are optimized according to the preset standards to determine the optimized processing parameter set for processing control.

[0025] Specifically, according to the evaluation results of the modified performance, the various indicators of asphalt performance reflected therein are carefully analyzed, including but not limited to strength, density, porosity, water permeability, etc., which are directly related to the performance of asphalt in practical applications. Next, the compound ratio in the compound combination processing technology will be adjusted. For example, if the evaluation results show that the strength of the asphalt is not ideal, the proportion of certain compounds that can enhance the strength will be increased, or the amount of compounds that have an adverse effect on the strength will be reduced. In the process of adjusting the ratio, various factors are considered comprehensively, such as the characteristics of different compounds, their interactions, and the degree of influence on the performance of asphalt. At the same time, the process parameters should be optimized in accordance with the preset standards. The preset standards are determined according to specific engineering requirements and industry specifications. Check the various parameters in the processing technology, such as temperature, pressure, time, etc., to see if they meet the preset standards. If it is found that some parameters need to be adjusted, they will be optimized to ensure that the processing technology can maximize the modified performance of asphalt. During the above adjustment and optimization process, we will continue to conduct experiments and analysis. By testing different ratios and parameter combinations, we will determine a set of optimized processing parameters. This set will contain the compound ratios and process parameters that are most suitable for the current asphalt mix sample and processing technology. Finally, we will use the determined set of optimized processing parameters for processing control, which means that in the actual production process, we will strictly follow these parameters to ensure that the modified asphalt produced has stable high performance. Through precise processing control, we can improve the quality and consistency of the product to meet the needs of different engineering applications.

[0026] In one possible implementation, Figure 2 As shown, step S300 also includes:

[0027] Step S310: determining first compound combination characteristic information associated with the U dense-graded asphalt mixed samples, wherein the first compound combination characteristic information includes classification identifiers of first material types corresponding to petroleum asphalt, coal tar, and fine aggregate.

[0028] Step S320: Based on the first material type, a first material basic indicator set associated with a classification identifier is added, where the first material basic indicator set includes density, viscosity, and softening point.

[0029] Step S330: Correlation mapping of the first material basic index set and the first compound combination characteristic information, simulating the mechanical properties of the U dense-graded asphalt mixed samples by finite element analysis, and adjusting the dense-graded asphalt modification parameters of the modified asphalt test model.

[0030] Specifically, the first compound combination characteristic information associated with U dense-graded asphalt mixed samples is determined. These dense-graded asphalt mixed samples are relatively complex in composition and contain a variety of different compounds. The classification identification of the first material type corresponding to petroleum asphalt, coal tar pitch and fine aggregate is clarified. As an important component, petroleum asphalt has specific physical and chemical properties. By determining its classification identification in the dense-graded asphalt mixed samples, we can better understand its role and contribution in the entire mixture. Similarly, coal tar pitch also has its unique characteristics. Determining its classification identification helps us analyze its impact on the performance of dense-graded asphalt. Fine aggregate plays a key filling and supporting role in dense-graded asphalt mixed samples. Clarifying the classification identification of fine aggregate can understand its particle size, shape and other characteristics, which will directly affect the density, strength and other important performance indicators of dense-graded asphalt. By carefully analyzing and determining the classification identification in these first compound combination characteristic information, the foundation is laid for the subsequent in-depth study and performance optimization of dense-graded asphalt mixed samples. This step not only helps to accurately describe the composition of dense-graded asphalt, but also provides a clear direction for further experiments and analysis.

[0031] Since the classification identification of the first material type corresponding to petroleum asphalt, coal asphalt and fine aggregate contained in the dense asphalt mixture sample has been clarified, it is now necessary to add the first material basic indicator set associated with its classification identification for these materials. This basic indicator set includes key indicators such as density, viscosity and softening point. Density reflects the compactness of the material and has an important impact on the overall quality and performance of the dense asphalt mixture sample. A higher density may mean that the material is more compact and can provide better strength and stability. Viscosity reflects the flow characteristics of the material. In the dense asphalt mixture sample, the appropriate viscosity can ensure that the material is easy to operate during the construction process and can maintain good adhesion after curing. Softening point is an important indicator for measuring the heat resistance of the material. For the dense asphalt mixture sample, a higher softening point means that it can still maintain good stability in a high temperature environment and is not prone to softening and deformation. By adding these basic indicators, the characteristics of different materials in the dense asphalt mixture sample can be more comprehensively understood, which not only helps to better understand the interaction between materials in subsequent analysis, but also provides specific direction and basis for optimizing the performance of dense asphalt. For example, if a material is found to have a low softening point, you can consider adjusting its mix ratio or looking for alternative materials to improve the heat resistance of dense-graded asphalt.

[0032] First, the first material basic index set is associated with the first compound combination characteristic information. This means that the basic indexes such as density, viscosity, and softening point of various materials in the dense asphalt mixed sample are matched with the combination characteristics of compounds such as petroleum asphalt, coal asphalt, and fine aggregate. Through this association mapping, we can have a deeper understanding of the relationship between different material properties and compound combinations, which provides an important basis for subsequent analysis and optimization. Next, we use finite element analysis to simulate the mechanical properties of U dense asphalt mixed samples. Finite element analysis is a powerful tool that can decompose complex structures or materials into small units and simulate their behavior under different load conditions through mathematical models. For dense asphalt mixed samples, finite element analysis is used to predict its mechanical properties such as deformation and stress distribution under stress. Through simulation, we can understand the performance of dense asphalt in actual use, such as durability and deformation resistance under traffic load. Based on the results of finite element analysis, the dense asphalt modification parameters of the modified asphalt test model can be adjusted, including material ratio, processing temperature, pressure, etc. By adjusting these parameters, the properties of dense-graded asphalt can be optimized to better meet the needs of actual applications. For example, if finite element analysis shows that dense-graded asphalt deforms more under a certain load condition, the material ratio or processing parameters can be adjusted to improve its strength and stiffness.

[0033] In a possible implementation, step S330 further includes:

[0034] Step S331: measuring the compressive strength of each of the U dense-graded asphalt mixture samples, and combining the density to obtain the elastic modulus under the filling index of the solid particles in the mixture with different filling indexes.

[0035] Step S332: At the same time, under different load conditions, the Poisson's ratio of different compressive strengths is analyzed, and then the elastic modulus under the filling index of solid particles in different mixtures and the Poisson's ratio of different compressive strengths are compared to initialize the configuration of the dense-graded asphalt modification parameters.

[0036] Specifically, the compressive strength of each of the U dense-graded asphalt mixture samples was measured. The compressive strength is an important indicator to measure the material's ability to resist compressive loads. For dense-graded asphalt mixture samples, its compressive strength is directly related to the stability and reliability when subjected to pressure in actual use. At the same time, the density is combined for analysis. The density reflects the compactness of the material and has an important influence on the performance of dense-graded asphalt mixture samples. By measuring the compressive strength and combining it with the density, the elastic modulus under the filling index of solid particles in different mixtures is obtained. The elastic modulus is the ratio of stress to strain of the material within the elastic deformation range. It reflects the stiffness and ability of the material to resist deformation. By determining the elastic modulus in different mixtures, the mechanical properties of dense-graded asphalt mixture samples under different compositions and conditions can be better understood.

[0037] At the same time, under different load conditions, the Poisson's ratio of different compressive strengths is analyzed. Poisson's ratio refers to the ratio of the transverse strain to the longitudinal strain of the material. It reflects the relationship between the transverse deformation and the longitudinal deformation of the material when it is subjected to force. By analyzing the Poisson's ratio under different compressive strengths, the deformation characteristics of the dense-graded asphalt mixed samples under different load conditions can be more comprehensively understood. After that, the elastic modulus of the solid particles in different mixtures under the filling index and the Poisson's ratio of different compressive strengths are compared to initialize the configuration of the dense-graded asphalt modification parameters. These parameters include the settings of the material ratio, processing technology, etc. By initializing the configuration according to the analysis results of the elastic modulus and Poisson's ratio, the dense-graded asphalt mixed samples can have better performance in subsequent processing and use. For example, if the analysis results show that the elastic modulus of a mixture is low, the material ratio or processing technology can be adjusted to increase its elastic modulus, thereby enhancing the stiffness and stability of the dense-graded asphalt mixed sample.

[0038] In a possible implementation, step S400 further includes:

[0039] Step S410: Determine the second compound combination characteristic information associated with the V open-graded asphalt mixed samples, where the second compound combination characteristic information includes classification identifiers of second material types corresponding to petroleum asphalt, coal asphalt, and coarse aggregate.

[0040] Step S420: Based on the second material type, a second material basic indicator set associated with the classification identifier is added.

[0041] Step S430: Correlation mapping of the second material basic index set and the second compound combination characteristic information, simulating the mechanical properties of the V open-graded asphalt mixed samples by finite element analysis, and adjusting the open-graded asphalt modification parameters of the modified asphalt test model.

[0042] Specifically, the aim is to determine the combined characteristic information of the second compound associated with V open-graded asphalt mixture samples, which are composed of multiple compounds, among which petroleum asphalt, coal asphalt and coarse aggregate play a key role. For petroleum asphalt, it has specific chemical composition and physical properties, and plays the role of a binder in the open-graded asphalt mixture sample. By determining its corresponding classification identifier, we can better understand the characteristics and contribution of petroleum asphalt in this specific mixture sample. Coal asphalt also has unique properties. Its presence in the open-graded asphalt mixture sample will affect the performance of the sample. Clarifying the classification identifier of coal asphalt helps to analyze its interaction with other components and its impact on the overall performance. Coarse aggregate occupies an important position in the open-graded asphalt mixture sample. Its size, shape and material will have a significant impact on the characteristics of the sample such as porosity and permeability. Determining the classification identifier of the second material type corresponding to the coarse aggregate can help accurately describe the characteristics of the coarse aggregate and provide a basis for subsequent analysis and performance evaluation.

[0043] Based on the determined second material type, add a set of second material basic indicators associated with the classification identifier. This set includes various characteristic indicators related to the open-graded asphalt mixture sample, such as the particle size distribution, strength, hardness, etc. of the material. These indicators are essential for describing the characteristics of different materials in the open-graded asphalt mixture sample. By adding these indicators, a more comprehensive understanding of the physical and chemical properties of the open-graded asphalt mixture sample can be achieved.

[0044] First, the second material basic index set and the second compound combination characteristic information are associated and mapped, which means that the basic indicators of petroleum asphalt, coal asphalt and coarse aggregate, such as needle penetration, carbon content, particle size distribution, etc., are associated with their corresponding material type classification identifiers. Through this association mapping, the relationship between material properties and material composition is established, so as to better understand the role of different materials in the open-graded asphalt mixed sample. Then, finite element analysis is used to simulate the mechanical properties of V open-graded asphalt mixed samples. Finite element analysis decomposes complex structures into small units and simulates their responses under different load conditions through mathematical models. For the open-graded asphalt mixed samples, consider simulating their stress distribution, deformation and failure mode under traffic loads, temperature changes, etc. Through finite element analysis, detailed information about the mechanical properties of the open-graded asphalt mixed samples, such as their strength, stiffness, toughness, etc., is obtained. Based on the results of finite element analysis, the open-graded asphalt modification parameters of the modified asphalt test model are adjusted. These parameters include material ratio, processing conditions, type and amount of additives, etc. By adjusting these parameters, the performance of the open-graded asphalt mixed samples is optimized to better meet the requirements of actual engineering applications. By correlating and mapping the basic material indicators and compound combination characteristics, finite element analysis was used to simulate the mechanical properties, and the modification parameters were adjusted, providing a scientific and effective method for optimizing the performance of open-graded asphalt mixture samples.

[0045] In a possible implementation, step S430 further includes:

[0046] Step S431: measuring the rheological properties of each of the V open-graded asphalt mixture samples, and obtaining the dynamic shear modulus and phase angle of the asphalt film distribution under different void structures in the mixture in combination with the void ratio.

[0047] Step S432: At the same time, under different temperature conditions, the freeze-thaw attenuation of different water permeability is analyzed. Then, the dynamic shear modulus and phase angle of the asphalt film distribution under the void structure in different mixtures, the freeze-thaw attenuation of different water permeability, and the configuration of the open-graded asphalt modification parameters are initialized.

[0048] Specifically, important analysis work was carried out on V open-graded asphalt mixture samples, and the rheological properties of each open-graded asphalt mixture sample were measured. Rheological properties reflect the deformation and flow characteristics of materials under stress. For asphalt mixture samples, this property is crucial because it is directly related to its performance in actual use. While measuring the rheological properties, the analysis was combined with the void ratio. The void ratio is a key characteristic of the open-graded asphalt mixture sample. It determines the content and distribution of air in the mixture. Different void ratios will affect the distribution of the asphalt film in the mixture. Through detailed measurement and analysis of each sample, the dynamic shear modulus and phase angle of the asphalt film distribution with different void structures in the mixture can be obtained. The dynamic shear modulus reflects the stiffness and ability to resist deformation of the material. In the open-graded asphalt mixture sample, the size of the dynamic shear modulus depends on factors such as the properties of the asphalt, the type of aggregate and the void structure. The phase angle represents the relationship between the viscous and elastic properties of the material. A higher phase angle usually means that the material has more viscous properties, while a lower phase angle means that the material is more elastic. Obtaining these parameters is crucial for a deep understanding of the performance of open-graded asphalt mixed samples. They can help evaluate the stability, durability, and deformation resistance of the mixture. At the same time, these parameters also provide an important basis for subsequent optimization and improvement. According to these parameters, the material ratio, processing technology and other factors are adjusted to improve the performance of open-graded asphalt mixed samples.

[0049] In a possible implementation, step S500 further includes:

[0050] Step S510: the third composite modified characteristic set corresponding to the asphalt mastic asphalt crushed stone mixing process includes powder-rubber ratio and mastic viscosity.

[0051] Step S520: Obtain target quality indicators, introduce a third composite modified characteristic set corresponding to the asphalt mastic crushed stone mixing process, and verify the modified characteristics of the semi-open graded asphalt mixing process against the target quality indicators, wherein the target quality indicators include an anti-slip index and a low noise index.

[0052] Specifically, it is clarified that the third composite modified characteristic set corresponding to the asphalt mastic crushed stone mixing process includes powder-rubber ratio and mastic viscosity. The powder-rubber ratio refers to the mass ratio of mineral powder to asphalt in the asphalt mixture, which has an important influence on the performance of the mixture. The appropriate powder-rubber ratio can improve the strength, stability and durability of the mixture. The mastic viscosity reflects the viscosity of the asphalt mastic, which affects the construction performance and road performance of the mixture. By determining these two characteristics, specific indicators can be provided for subsequent analysis.

[0053] Obtain target quality indicators, including anti-skid index and low noise index. Anti-skid index is crucial to road safety, reflecting the anti-skid ability of the road surface under wet or icy conditions. Low noise index takes into account the noise problem generated during road use, which is of great significance for improving the environmental quality around the road. After introducing the third composite modified characteristic set corresponding to the asphalt mastic crushed stone mixing process, the modified characteristics of the semi-open graded asphalt mixing process are verified against these target quality indicators, and the relationship between the powder-rubber ratio and mastic viscosity and the anti-skid index and low noise index is analyzed. For example, a higher powder-rubber ratio will improve the anti-skid performance of the road surface, but it will also affect the low noise index. Through this comparative verification, the performance of the semi-open graded asphalt mixing process in meeting the target quality indicators can be determined. If it is found that some characteristics do not match the target quality indicators, the processing parameters or material ratios are adjusted to optimize the performance of the semi-open graded asphalt so that it can better meet the requirements of anti-skid and low noise. By introducing a specific set of third composite modified properties and verifying them against target quality indicators, an important method and basis are provided for the optimization of semi-open-graded asphalt mixing processing technology.

[0054] In a possible implementation, step S520 further includes:

[0055] Step S521: If the modification characteristic verification is passed, then adding compound combination optimization processing permission to the modification performance evaluation result.

[0056] Step S522: If the modification characteristic verification fails, return to the modified asphalt test model and adjust the dense-graded asphalt modification parameters and / or the open-graded asphalt modification parameters again.

[0057] Specifically, first, for step S521, if the modified characteristics are verified, this means that the semi-open graded asphalt mixing process can meet the target quality indicators, including anti-skid indicators and low noise indicators, after introducing the third composite modified characteristics set corresponding to the asphalt mastic crushed stone mixing process. In this case, adding compound combination optimization processing permission to the modified performance evaluation results means that the current processing technology and material combination are recognized, and production can continue or be further optimized. After adding permission, the process can be used more safely for large-scale production, or fine-tuned on the existing basis to further improve performance.

[0058] However, if the modification characteristic verification fails, step S522 is entered. At this time, it is necessary to return to the modified asphalt test model and adjust the dense-graded asphalt modification parameters and / or the open-graded asphalt modification parameters again. This is because the failure of the verification indicates that the current parameter settings cannot enable the semi-open-graded asphalt mixing process to meet the expected performance requirements. By returning to the test model, the impact of different parameters on asphalt performance can be re-examined and analyzed. The parameters that need to be adjusted include but are not limited to the material ratio, processing temperature, pressure, etc. The adjustment of the dense-graded asphalt modification parameters and the open-graded asphalt modification parameters can be optimized for different types of asphalt mixing samples respectively. For example, if it is found that the performance of the dense-graded asphalt part is not up to standard, the parameters related to petroleum asphalt, coal asphalt, and fine aggregate can be adjusted; if there is a problem with the open-graded asphalt part, the parameters related to petroleum asphalt, coal asphalt, and coarse aggregate are adjusted. Through continuous adjustment and verification until the modification characteristic verification is passed, it is ensured that the semi-open-graded asphalt mixing process can produce products that meet quality requirements.

[0059] In a possible implementation, step S522 further includes:

[0060] Added dynamic adjustment formula for the upper limit of modification parameter adjustment. ,in, is the upper limit of adjustment of the ith modification parameter at time t, , is a constant related to the material properties corresponding to the dense-graded asphalt modification parameters and the open-graded asphalt modification parameters, is the basic value of the modified parameter of the i-th semi-open graded asphalt, is the current value of the modification parameter of the i-th semi-open-graded asphalt at time t.

[0061] Specifically, the formula represents the upper limit of adjustment of the i-th modification parameter at time t, and the determination of this upper limit is related to multiple factors. and They are constants closely related to the material properties corresponding to the dense-graded asphalt modification parameters and open-graded asphalt modification parameters. These constants reflect the degree of influence of the characteristics of different materials on the adjustment of modification parameters. Their values ​​will be determined based on the specific material properties and experimental data. It is the basic value of the modified parameter of the ith semi-open-graded asphalt. This basic value is a reference value initially set or determined based on past experience. is the current value of the modification parameter of the i-th semi-open graded asphalt at time t, which will change continuously as the adjustment process proceeds. Through this dynamic adjustment formula, when adjusting the modification parameters, the adjustment upper limit of each modification parameter can be accurately calculated based on the constants related to the material properties and the basic value and current value of the modification parameters. Such a design is of great significance. On the one hand, it can avoid the adverse effects caused by excessive adjustment during the adjustment process and ensure the stable performance and reliable quality of the modified asphalt. On the other hand, it can better adapt to the needs of different material properties and actual situations, because the formula takes into account the changes in material properties and the real-time status of the parameters, so that adjustments can be made more flexibly and accurately, improving the processing quality and performance of the modified asphalt, making it more in line with the requirements of practical applications.

[0062] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0063] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0064] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A method for optimizing the processing of a compound combination for modifying asphalt, characterized in that: The method comprises: Determine M asphalt mixed samples, wherein the M asphalt mixed samples include U dense-graded asphalt mixed samples and V open-graded asphalt mixed samples, and M=U+V; At the same time, in the compound combination processing technology composed of melt mixing method, emulsification method and reactive extrusion method, the M asphalt mixed samples are combined to establish a modified asphalt test model; For the first composite modified characteristic set corresponding to the U dense-graded asphalt mixed samples, modifying characteristic analysis is performed in combination with the modified asphalt test model to obtain a first modified test simulation result, wherein the first composite modified characteristic set includes density and strength; For the second composite modified characteristic set corresponding to the V open-graded asphalt mixed samples, performing modified characteristic analysis in combination with the modified asphalt test model to obtain a second modified test simulation result, wherein the second composite modified characteristic set includes porosity and water permeability; By comparing the first modification test simulation result and the second modification test simulation result, a third composite modification characteristic set corresponding to the mastic asphalt crushed stone mixing process is introduced to evaluate the modification characteristics of the semi-open gradation asphalt mixing process, and predict the modification performance evaluation result of the semi-open gradation asphalt mixing process; Based on the modified performance evaluation results, the compound ratio in the compound combination processing technology is adjusted, and the process parameters are optimized according to the preset standards to determine the optimized processing parameter set for processing control.

2. The compound combination optimization processing method for modified asphalt according to claim 1, characterized in that: For the first composite modified characteristic set corresponding to the U dense-graded asphalt mixed samples, the modified characteristic analysis is performed in combination with the modified asphalt test model to obtain a first modified test simulation result, the method comprising: Determine first compound combination characteristic information associated with the U dense-graded asphalt mixed samples, wherein the first compound combination characteristic information includes a classification identifier of a first material type corresponding to petroleum asphalt, coal asphalt, and fine aggregate; Based on the first material type, adding a first material basic indicator set associated with a classification identifier, wherein the first material basic indicator set includes density, viscosity, and softening point; The first material basic index set and the first compound combination characteristic information are associated and mapped, the mechanical properties of the U dense-graded asphalt mixed samples are simulated by finite element analysis, and the dense-graded asphalt modification parameters of the modified asphalt test model are adjusted.

3. The compound combination optimization processing method for modified asphalt according to claim 2, characterized in that: Finite element analysis is used to simulate the mechanical properties of the U dense-graded asphalt mixed samples, and the dense-graded asphalt modification parameters of the modified asphalt test model are adjusted. The method includes: The compressive strength of each dense-graded asphalt mixed sample in the U dense-graded asphalt mixed samples is measured, and the elastic modulus under the filling index of the solid particles in different mixtures is obtained in combination with the density; At the same time, under different load conditions, the Poisson's ratio of different compressive strengths is analyzed. Then, the elastic modulus under the filling index of solid particles in different mixtures and the Poisson's ratio of different compressive strengths are compared to initialize the configuration of the dense-graded asphalt modification parameters.

4. The compound combination optimization processing method for modified asphalt according to claim 2, characterized in that: For the second composite modified characteristic set corresponding to the V open-graded asphalt mixed samples, the modified characteristic analysis is performed in combination with the modified asphalt test model to obtain a second modified test simulation result, the method comprising: Determine second compound combination characteristic information associated with the V open-graded asphalt mixed samples, wherein the second compound combination characteristic information includes classification identifiers of second material types corresponding to petroleum asphalt, coal asphalt, and coarse aggregate; Based on the second material type, adding a second material basic indicator set associated with the classification identifier; The second material basic index set and the second compound combination characteristic information are associated and mapped, the mechanical properties of the V open-graded asphalt mixed samples are simulated by finite element analysis, and the open-graded asphalt modification parameters of the modified asphalt test model are adjusted.

5. The compound combination optimization processing method for modified asphalt according to claim 4, characterized in that: Finite element analysis is used to simulate the mechanical properties of the V open-graded asphalt mixed samples, and the open-graded asphalt modification parameters of the modified asphalt test model are adjusted. The method includes: Measuring the rheological properties of each of the V open-graded asphalt mixed samples, and obtaining the dynamic shear modulus and phase angle of the asphalt film distribution under the void structure in different mixtures in combination with the void ratio; At the same time, under different temperature conditions, the freeze-thaw attenuation of different moisture permeability is analyzed. After that, the dynamic shear modulus and phase angle of the asphalt film distribution under the void structure in different mixtures and the freeze-thaw attenuation of different moisture permeability are initialized to configure the open-graded asphalt modification parameters.

6. The compound combination optimization processing method for modified asphalt according to claim 5, characterized in that: Before predicting the modified performance evaluation result of the semi-open graded asphalt mixing process, the method further comprises: The third composite modified characteristic set corresponding to the asphalt mastic crushed stone mixing process includes powder-rubber ratio and mastic viscosity; The target quality index is obtained, and the third composite modified characteristic set corresponding to the mastic asphalt crushed stone mixing process is introduced. The modified characteristics of the semi-open graded asphalt mixing process are verified against the target quality index. The target quality index includes an anti-skid index and a low noise index.

7. The compound combination optimization processing method for modified asphalt according to claim 6, characterized in that: Verifying the modified characteristics of the semi-open graded asphalt mixing process according to the target quality index, the method comprises: If the modified characteristics are verified, then the compound combination optimization processing permission is added to the modified performance evaluation results; If the modification characteristic verification fails, the modified asphalt test model is returned to adjust the dense-graded asphalt modification parameters and / or the open-graded asphalt modification parameters again.

8. The compound combination optimization processing method for modified asphalt according to claim 7, characterized in that: Returning to the modified asphalt test model, adjusting the dense-graded asphalt modification parameters and / or the open-graded asphalt modification parameters again, the method further includes: Added dynamic adjustment formula for the upper limit of modification parameter adjustment. ,in, is the upper limit of adjustment of the ith modification parameter at time t, , is a constant related to the material properties corresponding to the dense-graded asphalt modification parameters and the open-graded asphalt modification parameters, is the basic value of the modified parameter of the i-th semi-open graded asphalt, is the current value of the modification parameter of the i-th semi-open-graded asphalt at time t.

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