Warm-mixing flame-retardant composite asphalt modifier as well as preparation and use methods thereof

Abstract

The invention relates to the technical field of asphalt modifiers, in particular to a warm-mixing flame-retardant composite asphalt modifier and a preparation and use method thereof, and the preparation method comprises the following steps: mixing a flame-retardant component and an interface modifier in a double-circulation airlift reactor, heating to 80-120 DEG C, and reacting for 1-3 hours; then adding a warm mixing component and an auxiliary agent, and stirring and compounding at 140-160 DEG C for 0.5-2 hours to obtain a mixture; and granulating the mixture through a water ring cutting granulator to obtain the warm-mixing flame-retardant composite asphalt modifier. Wherein the temperature of each section of the water ring cutting granulator is determined by raw material physical property parameters, equipment operation parameters, a quality target and environmental data; the temperature of each section of the granulator is dynamically regulated and controlled on the basis of raw material physical properties, equipment states, quality targets and environmental data, so that the modifier particles are uniform in shape and stable in performance, and the problems of caking, adhesion or invalidation of flame-retardant components and the like caused by improper temperature are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of asphalt modifiers, and in particular to a warm-mix flame-retardant composite asphalt modifier and a preparation and use method thereof. Background Art

[0002] In recent years, the road construction industry has put forward higher requirements on the performance and production process of asphalt modifiers. Against this background, warm mix and flame retardant technologies have developed rapidly. In the field of warm mix asphalt modifiers, they can effectively reduce energy consumption and harmful gas emissions by reducing the mixing and compaction temperature of asphalt mixtures; flame retardant asphalt modifiers improve the fire resistance of asphalt by adding compounds containing specific flame retardant elements, and are widely used in scenes with high fire protection requirements such as tunnels and bridges; in terms of granulation process, the automated temperature control system has improved the granulation quality to a certain extent.

[0003] Although the existing technology has made certain progress, it still has significant defects. On the one hand, the existing warm mix and flame retardant asphalt modifiers have a single function and cannot meet the dual needs of warm mix and flame retardancy at the same time, which limits its application in complex scenarios. On the other hand, the existing granulation temperature control system only adjusts the temperature according to preset parameters, and does not fully consider the impact of raw material properties and environmental changes on granulation quality, resulting in unstable product quality, which in turn affects the performance of asphalt mixture.

[0004] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides a warm-mix flame-retardant composite asphalt modifier and its preparation and use method, which dynamically controls the temperature of each section of the granulator based on the physical properties of the raw materials, equipment status, quality targets and environmental data to ensure that the modifier particles have uniform morphology and stable performance, and avoid problems such as agglomeration, adhesion or failure of flame retardant components due to improper temperature.

[0006] The first purpose of the present invention is to provide a method for preparing a warm-mix flame-retardant composite asphalt modifier, which dynamically controls the temperature of each section of the granulator based on the physical properties of the raw materials, equipment status, quality targets and environmental data to ensure that the modifier particles have uniform morphology and stable performance, and avoid problems such as agglomeration, adhesion or failure of the flame retardant component due to improper temperature.

[0007] The above technical objectives of the present invention are achieved through the following technical solutions:

[0008] A method for preparing a warm-mix flame-retardant composite asphalt modifier comprises:

[0009] Mix the flame retardant component and the interfacial modifier in a double loop airlift reactor, heat to 80-120°C, and react for 1-3 hours;

[0010] Then add the warm mix components and auxiliary agents, stir and compound at 140-160°C for 0.5-2 hours to obtain a mixture;

[0011] The mixture is granulated by a water ring cutting granulator to obtain a warm mix flame retardant composite asphalt modifier; wherein the temperature of each section of the water ring cutting granulator is determined by the physical properties of the raw materials, equipment operating parameters, quality targets and environmental data.

[0012] As a preferred embodiment of the present invention, the warm mix component is 30-70 parts, the flame retardant component is 10-40 parts, the interface modifier is 5-20 parts, and the auxiliary agent is 0.5-5 parts by weight.

[0013] As a preferred embodiment of the present invention, the warm mix components are cracking wax generated by catalytic cracking of waste polyolefins and at least one of a polyurethane prepolymer, a zwitterionic surfactant and an alkyl polyglycoside. The cracking temperature range is 200-400°C, and the carbon chain length of the cracking wax is C20-C50.

[0014] As a preferred embodiment of the present invention, the flame retardant component is at least one of a phosphorus-based flame retardant, a nitrogen-based flame retardant and an inorganic flame retardant.

[0015] As a preferred embodiment of the present invention, the interfacial modifier is a carbon nanotube-montmorillonite hybrid material or a thermoplastic elastomer, wherein the carbon nanotubes are in situ generated on the montmorillonite surface by thermal cracking of waste polyolefins, and the mass of the carbon nanotubes accounts for 5-15% of the total mass of the montmorillonite hybrid material.

[0016] As a preferred embodiment of the present invention, the auxiliary agent is at least one of a metallocene catalyst, a Ziegler-Natta catalyst and an antioxidant.

[0017] As a preferred embodiment of the present invention, the method for determining the temperature of each section of the water ring cutting granulator comprises:

[0018] Collect historical raw material physical properties, equipment operating parameters, quality targets and environmental data, annotate the corresponding historical granulation stage temperature and measured quality data, form a data set, and divide it into training set, validation set and test set;

[0019] Build deep learning models and set constraints;

[0020] Construct a multi-task loss function, which includes the error between the temperature prediction value and the actual value of each segment, the error between the quality prediction value and the actual value, and the penalty term for violating the constraint conditions;

[0021] Use the training set to train the model and minimize the loss function through the optimization algorithm;

[0022] Use the validation set to evaluate the performance of the model and adjust the model's hyperparameters based on the results of the validation set;

[0023] Use the test set to perform a final evaluation on the trained model and optimize the model based on the evaluation results;

[0024] Deploy the optimized model, receive raw material physical properties, equipment operating parameters, quality targets and environmental data in real time, and output the temperature setting values and quality prediction values for each section.

[0025] As a preferred solution of the present invention, the constraint conditions at least include the value range of each granulation temperature, equipment operating parameters and quality prediction values.

[0026] The second purpose of the present invention is to provide a warm-mix flame-retardant composite asphalt modifier prepared by the above method, which scientifically compounds the flame retardant and warm-mix components, can not only reduce the asphalt mixing temperature, but also enhance the flame retardant performance, and use the interface modifier to improve the compatibility of the components; and the water ring cutting granulator is based on multi-parameter intelligent temperature control technology, which can accurately control the temperature of each section to ensure that the modifier particles are uniform in morphology and stable in performance.

[0027] The third object of the present invention is to provide a method for using a warm-mix flame-retardant composite asphalt modifier, wherein the dosage of the warm-mix flame-retardant composite asphalt modifier is 2-5% of the asphalt mass.

[0028] Compared with the existing technology, the present invention has the following advantages: 1) The double-loop airlift reactor greatly improves the mass transfer efficiency, avoids the agglomeration of flame retardants, and creates good conditions for the uniform mixing of various components. At the same time, with the help of auxiliary agents, the various ingredients are promoted to merge with each other, forming a stable physical and chemical combination. The various raw material components work together, which not only broadens the construction temperature window and reduces mixing energy consumption, but also constructs a cross-scale flame retardant system, giving the asphalt good construction and workability and long-term service performance, and also solves many problems existing in traditional mechanical mixing;

[0029] 2) The present invention innovatively constructs a multi-dimensional parameter-driven intelligent temperature control mechanism, combining a deep learning model and a multi-task loss function to deeply couple raw material properties, equipment operation, quality targets, and environmental data. This mechanism breaks through the limitations of traditional temperature control modes, achieves adaptive adjustment of granulation temperature, significantly improves the consistency of modifier product quality and process applicability, effectively avoids a series of problems caused by improper temperature, and provides a precise and controllable technical guarantee for stable production;

[0030] 3) Warm mix, flame retardant, interface modifier and auxiliary agent are compounded in specific proportions, and the synergistic effect between the components is significant. The warm mix component reduces the asphalt construction viscosity, ensuring the workability and later strength of the mixture at low temperatures; the flame retardant component gives the asphalt good fire resistance through condensed phase barrier and gas phase dilution; the interface modifier builds a bridge between the various components and the asphalt, enhancing the compatibility of the system, and the auxiliary agent promotes the physical and chemical combination of the various components. The various components cooperate with each other to comprehensively optimize the performance of the asphalt, avoid the disadvantages of single component modification, achieve complementary advantages of the various components, significantly improve the overall quality of the asphalt, and meet the diverse engineering application needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic flow chart of a method for preparing a warm-mix flame-retardant composite asphalt modifier of the present invention. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0033] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0034] Secondly, the term "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0035] Example

[0036] Reference Figure 1 This embodiment provides a method for preparing a warm-mix flame-retardant composite asphalt modifier, comprising:

[0037] S1: Mix the flame retardant component and the interfacial modifier in a double loop airlift reactor, heat to 80-120°C, and react for 1-3 hours; put the flame retardant component and the interfacial modifier into the double loop airlift reactor, start the heating system of the reactor, monitor and adjust the temperature to 80-120°C in real time through a temperature sensor, and simultaneously introduce an inert gas to form a gas-liquid circulation so that the two components are fully in contact in the reactor. During the mixing process, the circulation speed is maintained by a stirring rate controller to ensure that the flame retardant component is evenly dispersed in the interfacial modifier. The reaction time is determined according to the dispersion of the components. The double loop airlift reactor uses gas lifting force to achieve the circulation flow of materials. Compared with the traditional stirred reactor, the mass transfer efficiency is improved by more than 30%, avoiding local agglomeration of the flame retardant component, and laying the foundation for uniform mixing for the subsequent compounding of the warm mix components.

[0038] S2 then adds the warm mix component and the auxiliary agent, and stirs and compounds at 140-160° C. for 0.5-2 hours to obtain a mixture; the warm mix component and the auxiliary agent are added to the double loop airlift reactor, the temperature is raised to 140-160° C. by the heating system, the mechanical stirring device is started, and the stirring rate is controlled at 150-250 rpm to fully blend the warm mix component with the previous reaction product. During this process, the auxiliary agent plays a dispersing and stabilizing role, promoting the formation of a stable physical and chemical bond between the components. The reaction time is adjusted according to the change in material viscosity, and finally a uniform semi-solid mixture is formed;

[0039] The S3 mixture is granulated in a water-ring-cutting granulator to obtain a warm-mix flame-retardant composite asphalt modifier. The temperature of each section of the water-ring-cutting granulator is determined by the physical properties of the raw materials, equipment operating parameters, quality targets, and environmental data.

[0040] The physical properties of raw materials include melting point, viscosity, thermal stability, moisture content, particle size distribution and the temperature entering the water ring cutting granulator. The above parameters reflect the physical state and flow characteristics of the raw materials at different temperatures and are the basis for determining the granulation temperature.

[0041] Equipment operating parameters include the screw speed, feed rate, cutter speed, die head aperture and cooling water pressure of the water ring pelletizer. The screw speed affects the shear heating of the material, the feed rate determines the heat load per unit time, the cutter speed and die head aperture jointly affect the temperature requirement during pellet forming, and the cooling water pressure is related to the temperature drop rate.

[0042] The quality targets include the particle size accuracy, surface finish, impact strength and melt index of the modifier of the present invention. Different quality indicators have different temperature sensitivities. For example, when high surface finish requirements are required, it is necessary to avoid material stringing caused by too low a temperature or particle adhesion caused by too high a temperature.

[0043] Environmental data includes ambient temperature, relative humidity, and atmospheric pressure. Ambient temperature affects the heat dissipation efficiency of the equipment (for example, in winter, the temperature of the heating section needs to be increased to compensate for heat dissipation losses). Humidity affects the hygroscopicity of the raw materials (adjuvants are prone to agglomeration under high humidity, so the temperature of the drying section needs to be increased). Air pressure affects the boiling point of water (in high-altitude areas, the temperature of the cooling section needs to be adjusted to avoid boiling).

[0044] The present invention deeply couples the temperature of each section of the water ring cutting granulator with the physical properties of raw materials, equipment operating parameters, quality targets and environmental data to form a multi-dimensional parameter-driven intelligent temperature control mechanism: the physical properties of the raw materials define the feasible temperature range to ensure component stability, the equipment parameters quantify the heat load to achieve dynamic temperature compensation, the quality targets are reversely deduced from the key temperature control nodes to ensure the quality of pellet molding, and the environmental data corrects external interference in real time to maintain process stability; this fusion mechanism breaks through the traditional extensive control mode of preset temperature, so that the granulation temperature can be adaptively adjusted according to the raw material characteristics, equipment status, quality requirements and environmental changes, fundamentally avoiding the problems of particle adhesion, uneven particle size, component failure and so on caused by improper temperature, significantly improving the consistency of modifier product quality and process applicability, and providing precise and controllable technical guarantee for the stable production of high-performance asphalt modifiers.

[0045] In some embodiments of the present invention, the warm mix component is 30-70 parts, the flame retardant component is 10-40 parts, the interface modifier is 5-20 parts, and the auxiliary agent is 0.5-5 parts by weight;

[0046] With the above-mentioned configuration, each component can achieve synergistic efficiency while exerting its own function, greatly improving the comprehensive performance of the modifier. 30-70 parts of warm mix components ensure that cracking wax and other ingredients reduce the construction viscosity of asphalt, widen the construction temperature window, and give the mixture good workability and later strength; 10-40 parts of flame retardant ensure the effective construction of the flame retardant system of condensed phase barrier and gas phase dilution, and give the material reliable fire resistance; 5-20 parts of interfacial modifier, with the help of carbon nanotube-montmorillonite hybrid materials or thermoplastic elastomers, enhance the compatibility of each component with asphalt, 0.5-5 parts of auxiliary agents, metallocene catalysts, etc. promote the physical and chemical reactions between the ingredients to ensure uniform dispersion. This ratio not only avoids performance imbalance due to too much or too little of a certain component, but also controls costs through reasonable dosage to achieve an optimal balance between performance and cost.

[0047] In some embodiments of the present invention, the warm mix component comprises pyrolysis wax generated by catalytic pyrolysis of waste polyolefins and at least one of a polyurethane prepolymer, a zwitterionic surfactant, and an alkyl polyglycoside. The pyrolysis temperature range is 200-400°C, and the carbon chain length of the pyrolysis wax is C20-C50. More specifically, the pyrolysis wax serves as the core viscosity-reducing component. Its 200-400°C pyrolysis process and C20-C50 carbon chain length enable the wax molecules to be semi-molten within the warm mix construction temperature range of 120-160°C. By mixing into the asphalt colloidal structure, the high-temperature viscosity is reduced, thereby reducing mechanical energy consumption during mixing. The long-chain structure forms a flexible bridge during the cooling process, maintaining the plasticity of the mixture and avoiding difficulties in aggregate adhesion at low temperatures.

[0048] When polyurethane prepolymer, zwitterionic surfactant, alkyl polyglycoside and cracking wax are compounded, the surfactant components (zwitterionic surfactant, alkyl polyglycoside) reduce the asphalt-aggregate interfacial tension, allowing the asphalt to spread quickly and wrap the aggregate at lower temperatures, reducing the problem of uneven dispersion caused by insufficient temperature. The polyurethane prepolymer forms hydrogen bonds or physical crosslinks with the polar groups in the asphalt, compensating for the bond strength that may be weakened due to the decrease in temperature during the warm mixing process, and preventing defects such as peeling and loosening of the mixture after molding.

[0049] The "physical viscosity reduction" of cracking wax and the "interface optimization" of surfactants jointly widen the construction temperature window (allowing the mixing temperature to be 10-20°C lower than that of traditional modified asphalt), while the "structural reinforcement" of polyurethane prepolymer avoids the degradation of road performance that may be caused by a single viscosity-reducing component, forming a chain effect of "reducing mixing energy consumption-ensuring construction uniformity-maintaining later strength". This combination not only utilizes the low-cost resource advantage of waste polyolefin cracking wax, but also makes up for the performance shortcomings of a single wax warm mix agent through functional additives, ensuring that the modified asphalt still has excellent construction and workability and long-term service performance under warm mix conditions while saving energy and protecting the environment.

[0050] In some embodiments of the present invention, the flame retardant component is at least one of a phosphorus-based flame retardant, a nitrogen-based flame retardant, and an inorganic flame retardant;

[0051] In the present invention, the flame retardant components (phosphorus-based, nitrogen-based, inorganic flame retardants) and the warm-mix components (pyrolysis wax, polyurethane prepolymer, surfactant, etc.) form a synergistic effect through multiple mechanisms: the surfactant in the warm-mix component enhances the dispersibility of the flame retardant in asphalt by virtue of its amphiphilic structure, avoids agglomeration and improves the flame retardant efficiency; the pyrolysis wax as a carbon source synergistically promotes the formation of the carbon layer with the phosphorus-based flame retardant, and the polyurethane prepolymer and the nitrogen-based flame retardant construct an elastic network to stabilize the gas-phase flame retardant gas, forming a "condensed phase barrier-gas phase dilution" cross-scale flame retardant system.

[0052] In some embodiments of the present invention, the interfacial modifier is a carbon nanotube-montmorillonite hybrid material or a thermoplastic elastomer, wherein the carbon nanotubes are in situ generated on the montmorillonite surface by thermal cracking of waste polyolefins, and the mass proportion of the carbon nanotubes is 5-15% of the total mass of the montmorillonite hybrid material; more specifically, montmorillonite (sodium-based, particle size ≤100nm) is dispersed in a cracking reaction system of waste polyolefins (such as waste polyethylene), and the cracking temperature is controlled to be within 200-400°C. During the catalytic cracking process of the waste polyolefin, the carbon atom clusters generated by the chain scission are deposited on the active sites on the montmorillonite surface, and carbon nanotubes are grown in situ. By adjusting the cracking time, the mass proportion of the carbon nanotubes is controlled to be within the range of 5-15%, forming a black and uniformly dispersed hybrid material;

[0053] The in-situ generated carbon nanotubes are tightly anchored on the surface of montmorillonite. Their high aspect ratio (1000-10000) and the lamellar structure of montmorillonite (thickness 1nm) form a "nanoscale reinforced network". In the double-loop reactor, the gas-liquid circulation effect allows the hybrid material to fully contact with the flame retardant. The surface defect sites of the carbon nanotubes adsorb the flame retardant molecules, and the montmorillonite layers fix the flame retardant through interlayer van der Waals forces, avoiding agglomeration caused by polarity differences in traditional mechanical mixing. At the same time, the lipophilic surface (carbon nanotubes) and hydrophilic edges (montmorillonite hydroxyls) of the hybrid material enable it to form an "amphiphilic interface" in asphalt, promoting the compatibility of warm-mix components (such as cracking wax) with the asphalt matrix.

[0054] In some embodiments of the present invention, the adjuvant is at least one of a metallocene catalyst, a Ziegler-Natta catalyst, and an antioxidant;

[0055] The auxiliary agent helps to promote the mutual integration of the components, so that the warm mix component, flame retardant component and interface modifier are better combined together, and the overall uniformity and stability of the modifier are improved.

[0056] In some embodiments of the present invention, the method for determining the temperature of each section of the water ring cutting granulator includes:

[0057] Collect historical raw material physical parameters, equipment operating parameters, quality targets and environmental data, annotate the corresponding historical granulation stage temperature and measured quality data to form a data set; more specifically, set up multiple sensors in the workshop to continuously collect historical raw material physical parameters, such as using a melting point meter to monitor the melting point of cracked wax and a rotational viscometer to measure the viscosity of the mixture; use the equipment's own sensors to collect equipment operating parameters, such as screw speed and feed rate; clarify quality targets, such as determining the particle size accuracy of pellets based on product standards; collect environmental data through temperature and humidity sensors and barometers; at the same time, record the corresponding historical granulation stage temperature and measured quality data obtained by quality testing equipment, such as pellet hardness and impact strength;

[0058] And divided into training set, validation set and test set; more specifically, the collected data is divided into training set, validation set and test set according to the ratio of 70%, 20% and 10%, and the data is normalized to ensure that the data is in a reasonable numerical range;

[0059] A deep learning model was constructed. More specifically, a long short-term memory (LSTM) model was built using the Python Keras framework. The model consists of one input layer that takes the processed multidimensional data as input; three hidden layers, each containing 64 LSTM units, to fully learn the time series characteristics of the data; and one fully connected layer as the output layer to output the temperature setpoints and quality predictions for each segment.

[0060] Set constraints and combine them with model training to guide the model to find the optimal solution while satisfying multiple constraints. The model output not only has theoretical value but also fits the actual production scenario.

[0061] Construct a multi-task loss function, which includes the error between the temperature prediction value and the actual value of each segment, the error between the quality prediction value and the actual value, and the penalty term for violating the constraint conditions;

[0062] More specifically, the multi-task loss function is:

[0063] L=αL t +βL q +γL c ;

[0064] Among them, L represents the total loss function value, L t It is the error function between the predicted value and the actual value of each temperature segment, which is used to measure the accuracy of temperature prediction. The calculation formula is:

[0065]

[0066] Where n is the number of samples, is the temperature prediction value of the i-th sample, is the actual temperature value of the i-th sample;

[0067] L q It is the error function between the quality prediction value and the actual value, which is used to evaluate the accuracy of quality prediction. The calculation formula is:

[0068]

[0069] Where m is the number of quality samples, is the quality prediction value of the jth sample, is the actual mass value of the jth sample;

[0070] Lc It is the penalty term for violating the constraint conditions, which is used to ensure that the model output meets the set constraint conditions. The constraint conditions are expressed as C k (k=1,2,…,p, p is the number of constraints), when a constraint C k When violated, L c Expressed as:

[0071]

[0072] Among them, λ k is the corresponding constraint C k The penalty coefficient, I(C k ) is the indicator function, when C k When violated, I(Ck) = 1, otherwise I(Ck) = 0;

[0073] α, β, and γ are weight coefficients used to balance the three losses. By adjusting their values, the importance of different components can be emphasized according to the needs of the specific problem. This multi-task loss function can comprehensively consider temperature prediction error, quality prediction error, and the satisfaction of constraints, allowing the model to optimize multiple objectives simultaneously during training, thereby improving the model's performance and generalization ability, and better adapting to the prediction requirements of the temperature and product quality of each section of the water ring cutting granulator in the preparation of warm-mix flame-retardant composite asphalt modifiers.

[0074] The model is trained using the training set, and the loss function is minimized through an optimization algorithm. More specifically, the model is trained using the training set and the Adaptive Moment Estimation (Adam) optimization algorithm is selected. The initial learning rate is set to 0.001. During training, the learning rate is decayed by 10% after every 50 training rounds by adjusting the learning rate scheduler until the loss function converges and stabilizes.

[0075] Use the validation set to evaluate the model's performance and adjust the model's hyperparameters based on the validation set's results. More specifically, hyperparameters include the number of hidden layer neurons, the number of training rounds, and the batch size.

[0076] Use the test set to perform a final evaluation on the trained model and optimize the model based on the evaluation results;

[0077] The optimized model is deployed to receive raw material physical properties, equipment operating parameters, quality targets and environmental data in real time, and output the temperature setting value and quality prediction value of each section. More specifically, the optimized model is exported as an H5 format file and integrated into the control system of the water ring cutting granulator. The control system collects raw material physical properties, equipment operating parameters, quality targets and environmental data in real time, and inputs the data into the model after standardization. The model quickly calculates and outputs the temperature setting value and quality prediction value of each section, thereby realizing precise control of the granulation process.

[0078] The above method realizes data-driven precise granulation temperature control by constructing an intelligent temperature control system: first, raw material properties, equipment operation, quality targets and environmental data are collected in real time through sensors to provide multi-dimensional input for model training; then an LSTM deep learning model is built, combined with a multi-task loss function, to simultaneously optimize the temperature prediction error, quality prediction accuracy and constraint satisfaction, so that the model can not only capture the time series characteristics of the data, but also balance the multiple restrictions in production; the introduction of constraints ensures the safe operation of the equipment and the compliance of product quality, avoiding the blindness and lag of traditional empirical control. The above method is deeply integrated with the preparation process, so that the temperature of each section of the water ring cutting granulator can be dynamically adjusted according to the characteristics of the raw materials, environmental changes and quality requirements, significantly improving the uniformity and stability of the modifier particles, and effectively solving the problems of particle adhesion and uneven particle size caused by improper temperature, providing an efficient, intelligent and reliable temperature control solution for industrial production, and ensuring the consistency of modifier performance and the controllability of the production process from the source.

[0079] In some embodiments of the present invention, the constraints include at least the value range of the granulation temperature in each stage, equipment operating parameters, and quality prediction values;

[0080] When the above constraints are combined with the multi-task loss function, a closed-loop control logic of "temperature-equipment-quality" is formed: temperature constraints ensure process feasibility, equipment constraints guarantee production reliability, and quality constraints lock in product goals. The three work together to force the model to simultaneously meet production safety, equipment life and quality standards when looking for the optimal solution, avoiding practical application conflicts caused by single indicator optimization in traditional methods. This multi-dimensional constraint mechanism not only improves the engineering practicality of the model output, but also transforms production experience into computable constraints, allowing data-driven intelligent control to be deeply integrated with actual production rules, realizing seamless connection between theoretical prediction and engineering practice, and ultimately significantly improving the stability of the granulation process and product quality consistency.

[0081] The method for using the above-mentioned warm mix flame retardant composite asphalt modifier of the present invention is that the dosage of the warm mix flame retardant composite asphalt modifier is 2-5% of the mass of asphalt; adding the warm mix flame retardant composite asphalt modifier at 2-5% of the mass of asphalt can effectively optimize the performance of asphalt while controlling costs. This dosage range allows the modifier to be fully dispersed in the asphalt, greatly improving the warm mix and flame retardant properties of the asphalt, reducing construction temperature, reducing energy consumption, and enhancing fire resistance; if the dosage is less than 2%, the modification effect is not significant; if it is higher than 5%, it not only causes material waste and increases costs, but may also affect the road performance of the asphalt due to system imbalance. The dosage of 2-5% can just balance the performance improvement and economic cost to achieve maximum benefit.

[0082] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for preparing a warm mix flame retardant composite asphalt modifier, characterized in that: include: Mix the flame retardant component and the interfacial modifier in a double loop airlift reactor, heat to 80-120°C, and react for 1-3 hours; Then add the warm mix components and auxiliary agents, stir and compound at 140-160°C for 0.5-2 hours to obtain a mixture; The mixture is granulated by a water ring cutting granulator to obtain the warm mix flame retardant composite asphalt modifier; wherein the temperature of each section of the water ring cutting granulator is determined by the physical properties of the raw materials, equipment operating parameters, quality targets and environmental data.

2. The method for preparing the warm mix flame retardant composite asphalt modifier according to claim 1, wherein: By weight, the warm mix component is 30-70 parts, the flame retardant component is 10-40 parts, the interface modifier is 5-20 parts, and the auxiliary agent is 0.5-5 parts.

3. The method for preparing the warm mix flame retardant composite asphalt modifier according to claim 2, wherein: The warm mix components are cracked wax generated by catalytic cracking of waste polyolefins and at least one of polyurethane prepolymer, zwitterionic surfactant and alkyl polyglycoside. The cracking temperature range is 200-400°C, and the carbon chain length of the cracked wax is C20-C50.

4. The method for preparing the warm mix flame retardant composite asphalt modifier according to claim 2, wherein: The flame retardant component is at least one of a phosphorus-based flame retardant, a nitrogen-based flame retardant and an inorganic flame retardant.

5. The method for preparing the warm mix flame retardant composite asphalt modifier according to claim 2, wherein: The interfacial modifier is a carbon nanotube-montmorillonite hybrid material or a thermoplastic elastomer, wherein the carbon nanotubes are in situ generated on the montmorillonite surface by thermal cracking of waste polyolefins, and the mass of the carbon nanotubes accounts for 5-15% of the total mass of the montmorillonite hybrid material.

6. The method for preparing the warm mix flame retardant composite asphalt modifier according to claim 2, wherein: The auxiliary agent is at least one of a metallocene catalyst, a Ziegler-Natta catalyst and an antioxidant.

7. The method for preparing the warm mix flame retardant composite asphalt modifier according to claim 1, wherein: The method for determining the temperature of each section of the water ring cutting granulator comprises: Collect historical raw material physical properties, equipment operating parameters, quality targets and environmental data, annotate the corresponding historical granulation stage temperature and measured quality data, form a data set, and divide it into training set, validation set and test set; Build deep learning models and set constraints; Construct a multi-task loss function, which includes the error between the temperature prediction value and the actual value of each segment, the error between the quality prediction value and the actual value, and the penalty term for violating the constraint conditions; Use the training set to train the model and minimize the loss function through the optimization algorithm; Use the validation set to evaluate the performance of the model and adjust the model's hyperparameters based on the results of the validation set; Use the test set to perform a final evaluation on the trained model and optimize the model based on the evaluation results; Deploy the optimized model, receive raw material physical properties, equipment operating parameters, quality targets and environmental data in real time, and output the temperature setting values and quality prediction values for each section.

8. The method for preparing the warm mix flame retardant composite asphalt modifier according to claim 7, wherein: The constraint conditions at least include the value range of each granulation temperature, equipment operating parameters and quality prediction values.

9. A warm mix flame retardant composite asphalt modifier prepared by the method for preparing a warm mix flame retardant composite asphalt modifier according to any one of claims 1 to 8.

10. The method for using the warm mix flame retardant composite asphalt modifier according to claim 9, wherein: The warm mix flame retardant composite asphalt modifier is added in an amount of 2-5% by mass of the asphalt.

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