A devolatilization extrusion granulation method for metallocene solution process polyolefin elastomers

Abstract

The application discloses a devolatilization extrusion granulation method for a metallocene solution method polyolefin elastomer, and relates to the technical field of polymer material production and post-processing equipment, and comprises the following steps: sending the polyolefin elastomer solution into a double-screw extruder to perform preliminary concentration to obtain material; when the material enters a first-stage medium-pressure flash devolatilization zone, the process parameters are adjusted by using a material characteristic-process parameter correlation model to obtain concentrated material; the solvent content at the outlet of the zone is predicted by using a coupling prediction model, and the process parameters of the next zone are pre-corrected by feedforward; the same process is used in a second-stage high-shear surface renewal devolatilization zone, and the concentrated material is obtained through devolatilization; the melt after devolatilization is obtained in a third-stage high-vacuum-air stripping collaborative final devolatilization zone; after homogenization and pressure increase, the melt is granulated through an underwater cutting die to obtain granular products. The application aims to solve the defects of incomplete devolatilization, material degradation, high energy consumption and unstable operation, and realizes intelligent control of the whole process.

Description

Technical Field

[0001] This invention relates to the field of polymer material production and post-processing equipment technology, and in particular to a devolatilization extrusion granulation method for metallocene solution-processed polyolefin elastomers. Background Technology

[0002] Polyolefin elastomers (POE / POP / EPDM) are high-end polyolefin materials produced by solution polymerization of ethylene and α-olefins (such as 1-octene) under the action of metallocene catalysts. Due to their excellent flexibility, transparency, aging resistance, and good processing flowability, they are widely used in the automotive, packaging, wire and cable, and polymer modification industries. In the solution polymerization process, the polymer is dissolved in an inert alkane solvent (such as hexane or cyclohexane) at a high concentration (typically containing 30%-50% solids). Therefore, most of the solvent must be removed before granulation to obtain a pure POE / POP / EPDM product.

[0003] Traditional POE / POP / EPDM devolatilization processes often employ an "upstream flash tank + downstream single-screw devolatilization extruder" or a "multi-stage series devolatilization reactor" approach. These technical routes have significant drawbacks: long process flow, complex equipment, and high energy consumption; the material remains at high temperatures for extended periods, which can easily lead to chain breakage or cross-linking of POE / POP / EPDM molecular chains due to thermal oxidation or localized overheating, affecting the product's molecular weight distribution and mechanical properties; for high-viscosity POE / POP / EPDM melts, traditional equipment has low mass transfer efficiency, making it difficult to stably reduce solvent residues to below 1000 ppm, while high-end applications often require residues below 200 ppm to meet stringent standards for odor, volatile matter, and long-term aging performance.

[0004] Twin-screw extruders have become a potential choice for integrated devolatilization and granulation due to their excellent mixing, conveying, and surface renewal capabilities. However, applying general twin-screw devolatilization technology directly to POE / POP / EPDM faces unique challenges: 1. Material characteristics challenge: POE / POP / EPDM melts have extremely high viscosity and significant viscoelasticity. During the devolatilization process, they easily encapsulate solvent molecules and generate a strong "pole climbing" effect, resulting in unstable conveying, uneven filling, and material leakage from the vent.

[0005] 2. Heat-sensitive challenge: POE / POP / EPDM is sensitive to thermal history. Excessive temperature or prolonged heating time can lead to irreversible degradation, requiring the devolatilization process to be completed at the lowest possible temperature and the shortest possible effective residence time.

[0006] 3. Deep devolatilization challenge: Achieving deep devolatilization at the ppm level requires extremely high mass transfer driving force (high vacuum) and a very large phase interface (melt surface renewal), which places extremely high demands on the design of the equipment's vacuum system, sealing, and the screw's pressure build-up and surface renewal capabilities.

[0007] Sichuan Zhongwang Group has accumulated a wealth of experience in related technical practices, but how to systematically integrate and synergistically optimize flash evaporation, high-shear renewal, ultimate vacuum and gas stripping technologies, and achieve precise intelligent control of the entire process to stably, efficiently and flexibly produce high-quality POE / POP / EPDM, remains a technical problem that needs to be solved. Summary of the Invention

[0008] This invention provides a method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers, comprising: The polyolefin elastomer solution is fed into a twin-screw extruder via a forced feeding device for preheating and initial concentration to obtain the material, and the status data is collected in real time by process instruments. When the material enters the first-stage medium-pressure flash devolatilization zone, the process parameters of this zone are adjusted based on the current state data using the material characteristics-process parameter correlation model to obtain concentrated material. When the concentrated material is in the first-stage medium-pressure flash devolatilization zone, the solvent content at the outlet of the zone is predicted by a coupled prediction model based on the current process parameters and state data, and the process parameters of the second-stage high-shear surface update devolatilization zone are pre-corrected by feedforward. When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the process parameters of this zone are adjusted based on the current state data using the material property-process parameter correlation model to obtain the reconcentrated material, and the process parameters of the next zone are pre-corrected using the coupled prediction model. When the reconcentrated material enters the three-stage high vacuum-gas stripping synergistic final devolatilization zone, the process parameters of this zone are adjusted according to the current state data through the material characteristics-process parameter correlation model. The optimal process parameters of this zone are solved using a multi-objective optimization algorithm and the process is driven to obtain the devolatilized melt. The devolatilized melt is homogenized and pressurized, and then granulated through an underwater pelletizing die to obtain granular products.

[0009] The aforementioned method for devolatilization and extrusion granulation of metallocene solution-processed polyolefin elastomers involves adjusting the process parameters of a primary medium-pressure flash devolatilization zone based on current state data using a material characteristic-process parameter correlation model to obtain concentrated material, including: Construct a material property-process parameter correlation model and pre-install it in the intelligent control system; The material enters the first-stage medium-pressure flash devolatilization zone. Using the material characteristics-process parameter correlation model, the process parameters in this zone are dynamically adjusted based on real-time status data to complete the first-stage devolatilization and obtain concentrated material.

[0010] The aforementioned method for devolatilization and extrusion granulation of metallocene solution-processed polyolefin elastomers includes the following steps: When the concentrated material is in the primary medium-pressure flash devolatilization zone, the solvent content at the outlet of this zone is predicted using a coupled prediction model based on current process parameters and state data. Furthermore, the process parameters of the secondary high-shear surface-updated devolatilization zone are pre-corrected using a feedforward method. A coupled prediction model based on virtual material tracking and residence time pattern matching is constructed and pre-installed in the intelligent control system; When the concentrated material triggers the preset conditions in the primary medium-pressure flash devolatilization zone, the coupled prediction model is used to predict the solvent content at the outlet of the current devolatilization zone, and the process parameters of the secondary high-shear surface updated devolatilization zone are pre-corrected by feedforward.

[0011] The aforementioned method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers comprises constructing a coupled prediction model based on virtual material tracking and residence time profile matching, and pre-installing this model in an intelligent control system, including: For specific screw configurations in each devolatilization zone of a twin-screw extruder, an offline library of residence time maps for each zone is generated. A virtual material particle tracking engine is constructed to calculate the differences in residence time and state evolution of materials in each level of devolatilization zone; The feedforward correction decision module assesses the risk level based on the virtual tracking prediction results and generates a feedforward correction strategy for process parameters.

[0012] The aforementioned method for devolatilization and extrusion granulation of metallocene solution-processed polyolefin elastomers includes the following steps: When the concentrated material triggers preset conditions in the primary medium-pressure flash devolatilization zone, a coupled prediction model is used to predict the solvent content at the outlet of the current devolatilization zone, and feedforward pre-correction is performed on the process parameters of the secondary high-shear surface updated devolatilization zone. When the concentrated material triggers preset conditions in the primary medium-pressure flash devolatilization zone, the intelligent control system acquires the current state data and the initial process parameter settings of the secondary high-shear surface to update the devolatilization zone, thus obtaining the baseline operating conditions.

[0013] Using the baseline operating conditions as input, the virtual material particle tracking engine is used to deduce the state evolution trajectory of the material from its current position to the outlet of the first-stage medium-pressure flash devolatilization zone, and output the predicted solvent content at the outlet of the first-stage medium-pressure flash devolatilization zone.

[0014] The feedforward correction decision module performs a risk assessment on the outlet prediction results of the first-stage medium-pressure flash devolatilization zone and generates a feedforward correction instruction for updating the process parameters of the second-stage high-shear surface devolatilization zone.

[0015] The aforementioned method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers involves adjusting the process parameters of a secondary high-shear surface renewing devolatilization zone based on current state data using a material property-process parameter correlation model to obtain a re-concentrated material. Furthermore, a coupled prediction model is used to pre-correct the process parameters for the next zone, including: When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the intelligent control system dynamically adjusts the process parameters in this zone using the material characteristics-process parameter correlation model to obtain the reconcentrated material. When the material triggers preset conditions in the secondary high-shear surface renew devolatilization zone, the intelligent control system uses a coupled prediction model to pre-correct the process parameters of the tertiary high-vacuum-air stripping synergistic final devolatilization zone.

[0016] The aforementioned method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers involves an intelligent control system dynamically adjusting process parameters in a secondary high-shear surface renewal devolatilization zone when the concentrated material enters the zone, using a material property-process parameter correlation model to obtain a reconcentrated material. This includes: Obtain the structural configuration of the updated devolatilization zone on the secondary high-shear surface and set the initial process parameters for this zone; After the concentrated material enters, the intelligent control system collects status data in real time and calls the material characteristic-process parameter correlation model for closed-loop adjustment. The material is renewed and volatilized through a high-shear surface, further reducing the solvent content and yielding a reconcentrated material.

[0017] The aforementioned method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers involves the following steps: When the reconcentrated material enters the three-stage high-vacuum-air-stripping synergistic final devolatilization zone, the process parameters of this zone are adjusted based on current state data using a material characteristic-process parameter correlation model. A multi-objective optimization algorithm is then used to solve for the optimal process parameters of this zone and drive the execution, resulting in a devolatilized melt, comprising: When the reconcentrated material enters the three-stage high vacuum-air stripping synergistic final devolatilization zone, the intelligent control system calls the material characteristic-process parameter correlation model to perform basic closed-loop adjustment.

[0018] The intelligent control system invokes a multi-objective collaborative real-time optimization algorithm to solve for the optimal setpoints of temperature, absolute pressure, and gas stripping medium injection flow rate in the region, based on the basic adjustments provided by the correlation model.

[0019] The beneficial effects achieved by this invention are as follows: The three-stage synergistic process of "medium-pressure flash evaporation + high-shear renewal + extreme vacuum air extraction" is highly targeted and can efficiently remove solvents from 70% to below 200ppm, while maintaining stable operation and high product consistency.

[0020] The stepped, precise temperature control and short-process design greatly reduce the thermal and mechanical shear history of POE / POP / EPDM materials, effectively inhibiting degradation and gel formation, and maintaining the original molecular structure and high performance of POE / POP / EPDM.

[0021] The first-stage medium-pressure flash evaporation fully utilizes the latent heat of solvent vaporization, and the heat of solvent vapor condensation can be recovered; the integrated equipment shortens the process, reduces equipment investment and floor space, and the overall energy consumption is reduced by about 20%-30% compared with the traditional process.

[0022] The closed-loop control system based on online detection and intelligent models enables the production process to adapt to the switching between different grades of POE / POP / EPDM (such as different comonomer contents and different molecular weights), realizing the flexibility and intelligence of high-end manufacturing. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0024] Figure 1 This is a flowchart of a devolatilization extrusion granulation method for metallocene solution-based polyolefin elastomers provided in Embodiment 1 of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Example 1 like Figure 1 As shown, Embodiment 1 of this application provides a method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers, comprising: S1: The polyolefin elastomer solution is fed into a twin-screw extruder through a forced feeding device for preheating and initial concentration to obtain the material, and the status data is collected in real time by process instruments; Specifically, the intelligent control system pre-stores a database of polyolefin elastomer material properties containing different comonomer contents (10%~40%) and different molecular weights (melt index 0.5~50g / 10min), and stores the optimal initial process parameter set for the corresponding grades. After the target product grade is input, the system automatically calls up the matching initial parameters, including forced feed flow rate, preheating zone temperature, and initial screw speed of the main unit, and sends them to each actuator.

[0027] The polyolefin elastomer solution, with solvents such as hexane and cyclohexane, having a solvent mass fraction of 50%~70% and a solid content of 30%~50%, is pressurized in a buffer tank and then quantitatively fed into the forced feeding and preheating zone of the twin-screw extruder by a metering forced feeding device.

[0028] The solvent for the polyolefin elastomer solution is an inert alkane such as hexane or cyclohexane, with a solvent mass fraction of 50% to 70% and a solid content of 30% to 50%; for example, a polyolefin elastomer solution with an octene content of 20% and a solution solid content of 35% (solvent is hexane).

[0029] The forced feeding device includes a metering pump and a twin-screw toothed forced feeding element; wherein the metering accuracy of the metering pump is ≤±0.5%, and the twin-screw toothed forced feeding element adopts a large diameter and deep screw groove design to effectively overcome the "climbing rod" effect of high viscoelastic solution and ensure that the material enters the main cylinder at full flow rate without pulsation.

[0030] The length of the forced feeding and preheating zone along the material conveying direction is 6D (D is the screw diameter). The cylinder adopts a segmented heat transfer oil circulation heating and cooling design, with at least 3 independent temperature control sections set along the axial direction, and the temperature control accuracy is ±1℃.

[0031] The intelligent control system stabilizes the temperature of each section of the preheating zone at 90~120℃ (e.g., 105℃) based on the initial parameters, and maintains the operating pressure at 0.101~0.12MPa absolute pressure (slight positive pressure).

[0032] The material is conveyed forward by the twin-screw toothed forced feeding element, while simultaneously undergoing sufficient heat exchange with the cylinder wall to achieve uniform heating. Under these temperature and pressure conditions, the solvent in the material begins to slowly evaporate without violent boiling, forming a gas-liquid two-phase mixture, thus completing the initial concentration.

[0033] Among them, the micro-positive pressure operation prevents air from entering the cylinder and causing material oxidation and degradation, while avoiding solvent vapor overflow from the feed inlet, which would cause material loss and environmental pollution.

[0034] Process instruments are deployed at key locations in the forced feeding and preheating zone, each stage of devolatilization zone, and the homogenization and granulation section to collect real-time data on core status parameters such as temperature, pressure, feed flow rate, screw speed, melt viscosity, and residual solvent concentration. All collected data is preprocessed by the intelligent control system, including filtering, outlier removal, and time synchronization, to obtain status data.

[0035] S2: When the material enters the first-stage medium-pressure flash devolatilization zone, the process parameters of this zone are adjusted based on the current state data using the material characteristics-process parameter correlation model to obtain concentrated material. The material property-process parameter correlation model is composed of an online mass transfer coefficient inversion module, a state migration path prediction module, and a multi-source constraint fusion decision module coupled in sequence. Its core is to automatically call the corresponding apparent solvent removal rate equation and ideal migration path according to the devolatilization zone where the material is located (first-stage medium-pressure flash devolatilization zone, second-stage high-shear surface renewal devolatilization zone, or third-stage high-vacuum-gas stripping synergistic final devolatilization zone), so as to realize the dynamic optimal adjustment of process parameters in each devolatilization zone.

[0036] The process involves the following sub-steps when the material enters the primary medium-pressure flash devolatilization zone: Based on the current state data, the process parameters of this zone are adjusted using a material characteristic-process parameter correlation model to obtain concentrated material. S21: Construct a material property-process parameter correlation model and pre-install it in the intelligent control system; Specifically, the material property-process parameter correlation model is composed of an online mass transfer coefficient inversion module, a state migration path prediction module, and a multi-source constraint fusion decision module coupled in sequence. When the model is applied to a specific devolatilization zone, the system automatically calls the corresponding apparent solvent removal rate equation and ideal migration path for that zone.

[0037] Specifically, the online mass transfer coefficient inversion module is based on the mass transfer mechanism of the devolatilization zone where the material is located. It calls the corresponding apparent solvent removal rate equation according to the region. The specific calculation formula is as follows: in, This represents the instantaneous rate of change of solvent concentration within the current control period (i.e., the apparent removal rate). The instantaneous solvent mass fraction of the material; The apparent rate constant of the first-stage medium-pressure flash volatilization zone is determined by fitting offline experimental data and corrected in real time during online inversion. For the temperature of the solvent in this region The saturated vapor pressure below; This is the actual absolute pressure in the area; The reference pressure (such as standard atmospheric pressure) is used for dimensionless calculation. The pressure driving force index is determined by fitting offline experimental data. The apparent rate constant of the devolatilization zone for the secondary high-shear surface is updated by fitting offline experimental data and corrected in real time during online inversion; This represents the actual temperature in the area. For reference temperature; This represents the screw shear rate in that region. For reference shear rate; This is the actual absolute pressure of the area. Standard atmospheric pressure; These are the effect exponents for temperature, shear rate, and vacuum degree, respectively, determined by fitting offline experimental data. The apparent rate constant of the final devolatilization zone in the three-stage high vacuum-gas stripping synergistic process was determined by fitting offline experimental data and corrected in real time during online inversion. This refers to the actual temperature in the area; This is the actual absolute pressure in the area; Inject flow rate of the air-lifting medium. For reference gas lift flow rate; These are the effect indices for temperature and vacuum, respectively; The air-lift enhancement factor was determined by fitting offline experimental data.

[0038] The solvent removal rate equation fully describes the change law of solvent concentration in the material within the control cycle; it can quickly deduce the current value of the apparent rate constant in each control cycle, thereby characterizing the real mass transfer capacity of the region under the current operating conditions in real time.

[0039] Within each control cycle, the online mass transfer coefficient inversion module acquires the inlet solvent content, outlet solvent content, and current process parameters of the devolatilization zone where the material is located. Using the inlet solvent content as the initial condition, it substitutes it into the apparent solvent removal rate equation for the corresponding zone to calculate the predicted outlet solvent content. The gradient descent method is used to correct the apparent rate constant in the corresponding equation until the deviation between the predicted and measured values ​​converges to a preset threshold. The corrected apparent rate constant is then smoothly updated using an exponentially weighted moving average method, serving as a representation of the material's true mass transfer capacity in that zone under the current operating conditions.

[0040] The state migration path prediction module constructs a two-dimensional state space for each level of devolatilization zone based on solvent content and material viscosity, and obtains the ideal migration path for each zone through offline experimental fitting: the ideal flash evaporation path for the first-level medium-pressure flash devolatilization zone, the ideal surface renewal path for the second-level high-shear surface renewal devolatilization zone, and the ideal air stripping enhancement path for the third-level high-vacuum-air stripping synergistic final devolatilization zone.

[0041] Within each control cycle, the corresponding ideal path is invoked according to the area where the material is located. The currently measured or inferred solvent content and viscosity value are mapped to the state space. The deviation vector between the actual state point and the corresponding point of the ideal path is calculated and decomposed into the progress deviation along the tangent direction of the path and the quality deviation along the normal direction of the path.

[0042] If the schedule deviation is dominant, the dominant controllable variable in this area should be adjusted first (absolute pressure in the first-stage medium-pressure flash devolatilization zone, absolute pressure or shear rate in the second-stage high-shear surface renewal devolatilization zone, and absolute pressure or gas stripping flow rate in the third-stage high-vacuum-gas stripping synergistic final devolatilization zone) to adjust the devolatilization rate. If quality deviations are dominant, temperature should be adjusted first to correct melt viscosity and ensure that the material always migrates along the optimal path.

[0043] The multi-source constraint fusion decision module integrates mass transfer capacity constraints and process safety constraints to solve for the optimal process parameter adjustment. This module transforms the current region's mass transfer capacity parameter output by the online mass transfer coefficient inversion module into the upper limit of the adjustment range of the controllable variable in that region, and transforms the deviation vector output by the state transition path prediction module into the gradient direction of the objective function. A single-step optimization problem is constructed: with the objective of minimizing the distance between the actual state point and the ideal path, and with mass transfer capacity constraints, temperature safety constraints, absolute pressure safety constraints, and viscosity transport safety constraints as boundaries, the optimal adjustment increment is solved using the Lagrange multiplier method within milliseconds. When the mass transfer capacity parameter abruptly exceeds three standard deviations of the historical mean, the model automatically switches to a conservative adjustment mode and triggers an early warning.

[0044] S22: The material enters the first-stage medium-pressure flash devolatilization zone. Using the material characteristics-process parameter correlation model, the process parameters of this zone are dynamically adjusted according to real-time status data to complete the first-stage devolatilization and obtain concentrated material.

[0045] Specifically, the first-stage medium-pressure flash devolatilization zone has an axial length of 10D (D is the screw diameter). The screw adopts a full-conveying element configuration with large lead and large free volume. The cylinder is heated by circulating heat transfer oil with a temperature control accuracy of ±1℃. The exhaust port is connected to a liquid ring vacuum system and a solvent vapor condensation and recovery device.

[0046] The intelligent control system retrieves initial process parameters based on the target product brand and sets initial values. These process parameters include controllable parameters such as temperature and pressure.

[0047] After the material enters the zone, the status data collected by the process instruments deployed in the zone according to the control cycle is input into the material characteristic-process parameter correlation model. The material characteristic-process parameter correlation model sequentially performs online mass transfer coefficient inversion, state transition path prediction, and multi-source constraint fusion decision-making, and outputs the optimal adjustment process parameters for temperature and absolute pressure, which are then sent to the actuators after safety limiting.

[0048] Under a sudden pressure drop, the material undergoes controlled flash evaporation, with a large amount of solvent vaporizing and being removed by the vacuum system. The evaporated solvent vapor is condensed to recover latent heat for preheating the feed. After this step, the solids content of the material is stably increased from 30%~50% to 60%~80%, with no material leakage from the vent or material entrainment, resulting in concentrated material. The concentrated material is continuously driven by the screw into the secondary high-shear surface renewal devolatilization zone, and its status data is synchronously transmitted to the downstream control module.

[0049] S3: When the concentrated material is in the first-stage medium-pressure flash devolatilization zone, the solvent content at the outlet of the zone is predicted by a coupled prediction model based on the current process parameters and state data, and the process parameters of the second-stage high-shear surface update devolatilization zone are pre-corrected by feedforward. During the operation of the concentrated material in the primary medium-pressure flash devolatilization zone, the intelligent control system calls the coupled prediction model to deduce the state evolution trajectory of the material from its current position to the outlet of the primary medium-pressure flash devolatilization zone based on the real-time collected current state data, predicts the solvent content distribution at the outlet, and performs feedforward pre-correction of its process parameters before the material actually enters the secondary high-shear surface renewal devolatilization zone to ensure that the zone is in optimal operating condition when the material enters the secondary high-shear surface renewal devolatilization zone.

[0050] Specifically, when the concentrated material is in the primary medium-pressure flash devolatilization zone, the solvent content at the outlet of this zone is predicted using a coupled prediction model based on the current process parameters and state data. Furthermore, the process parameters of the secondary high-shear surface updated devolatilization zone are pre-corrected using a feedforward method, including the following sub-steps: S31: Construct a coupled prediction model based on virtual material tracking and residence time map matching, and pre-install this model in the intelligent control system; The process of constructing a coupled prediction model based on virtual material tracking and residence time pattern matching, and pre-installing this model in the intelligent control system, includes the following sub-steps: S311: For specific screw configurations in each stage of the devolatilization zone of a twin-screw extruder, generate an offline library of residence time maps for each zone. In the offline phase, for the large-lead conveying element configuration of the first-stage medium-pressure flash devolatilization zone, the combination configuration of the kneading block and reverse thread element of the second-stage high-shear surface renewal devolatilization zone, and the shallow screw groove pressure building element configuration of the third-stage high-vacuum-airlift synergistic final devolatilization zone, computational fluid dynamics simulation software was used to simulate the residence time distribution curves of inert tracer particles from the inlet to the outlet of each zone under different screw speed and feed flow rate combinations.

[0051] Each screw speed-feed flow rate combination corresponds to a unique residence time distribution curve. After statistical fitting, all curves are parametrically compressed using gamma distribution or log-normal distribution function. Each curve retains only the distribution type identifier and two characteristic parameters.

[0052] The compressed graph library is stored in the read-only memory of the intelligent control system in the form of a two-dimensional index table of screw speed and feed flow rate, allowing for rapid retrieval during the online phase. Simultaneously, a series retrieval rule for graphs at each level of the devolatilization zone is established, specifying how to adjust the equivalent flow parameters at the inlet of the next zone based on the material filling status at the outlet of the previous zone, ensuring consistent matching of graphs across zones during continuous simulation.

[0053] S312: Construct a virtual material particle tracking engine to calculate the differences in residence time and state evolution of materials in each level of devolatilization zone; Specifically, the virtual material particle tracking engine can perform state extrapolation for any target devolatilization zone. When it is necessary to predict the solvent content of the material from the current location to the outlet of a certain devolatilization zone, a set of virtual material particles (e.g., 100-300 particles) is generated in memory. Each particle is assigned an estimated solvent content and an initial temperature value at the current moment. If the current location is the inlet of the zone, the initial value is taken from the upstream measured data; if the current location is within the zone, the current estimated value is derived by back-calculating the inlet measured data, the running time, and the zone's partitioned mass transfer attenuation rules. The partitioned mass transfer attenuation rules refer to a complete extrapolation logic system pre-constructed for different mass transfer mechanisms at each level of the devolatilization zone, including mass transfer attenuation equations and their parameter calling relationships.

[0054] Next, based on the current main screw speed and feed flow rate, a matching residence time distribution curve is retrieved from the residence time spectrum library of the target devouring zone. The Monte Carlo sampling method is used to independently assign a remaining residence time value from the current position to the outlet of the zone to each virtual particle, so that the statistical distribution of this set of residence times is consistent with the distribution of the corresponding remaining residence time in the spectrum curve.

[0055] Each virtual particle independently deduces the decay process of its solvent content based on its allocated remaining residence time under the partitioned mass transfer decay rule.

[0056] Specifically, for each virtual particle's residence time in each devolatilization zone, its solvent content is estimated to decrease according to the mass transfer decay equation. The intelligent control system calculates the change in particle solvent content within each estimated time step using the following formula: Among them, for each virtual particle, the residence time in the first-level medium-pressure flash evaporation and devolvation zone; For the first The solvent content of a virtual particle at the current moment; The mass transfer correction coefficient for the first-stage medium-pressure flash devolatilization zone is determined by fitting offline experimental data. Temperature of solvent in the first-stage medium-pressure flash devolatilization zone The saturated vapor pressure is obtained from the pre-stored solvent saturated vapor pressure temperature characteristic curve; This is the actual absolute pressure of the first-level medium-pressure flash devolatilization zone; To achieve the absolute pressure in the first-stage medium-pressure flash devolatilization zone The equilibrium concentration of the solvent in the melt under the given conditions is obtained from a pre-stored table of equilibrium concentrations and absolute pressures. The simulation time step is automatically set by the system based on the control cycle.

[0057] For each virtual particle, during the residence time of the updated devolatilization zone on the secondary high-shear surface; The mass transfer correction coefficient for the devolatilization zone of the secondary high-shear surface was updated and determined by fitting offline experimental data. The solvent diffusion coefficient in the melt is given by the value of the second-order high-shear surface renewal devolatilization zone temperature. and real-time melt viscosity The function is retrieved from the pre-stored diffusion coefficient temperature viscosity correlation table; The surface renewal frequency is the screw shear rate in the secondary high-shear surface renewal devouring zone. The function is retrieved from the pre-stored surface update frequency-shear rate correlation curve; To update the absolute pressure of the devolatilization zone on a secondary high-shear surface The equilibrium concentration of the solvent in the melt under the given conditions is obtained from a pre-stored table of equilibrium concentrations and absolute pressures. The time step is used for simulation.

[0058] For each virtual particle, during its residence time in the three-stage high vacuum-gas stripping synergistic final devolatilization zone; For the first The solvent content of a virtual particle at the current moment; The vacuum suction mass transfer coefficient is determined by fitting offline experimental data. The solvent at the temperature of the final devolatilization zone in the three-stage high vacuum-stripping synergistic process. The saturated vapor pressure is obtained from the pre-stored solvent saturated vapor pressure temperature characteristic curve; The actual absolute pressure of the three-stage high vacuum-gas stripping synergistic final devolatilization zone; The mass transfer coefficient for gas stripping enhancement was determined by fitting offline experimental data. Inject flow rate for the air-lifting medium; The effective melt volume of the three-stage high vacuum-gas stripping synergistic final devolatilization zone is estimated from the screw free volume and filling degree of this zone. To achieve absolute pressure in the final devolatilization zone of the three-stage high vacuum-gas-lift synergistic process The equilibrium concentration of the solvent in the melt under certain conditions; The time step is used for simulation.

[0059] The coefficients and functional relationships in the above mechanism equations were all determined in advance through laboratory and pilot-scale devices, and were fixed in the process database of the intelligent control system in the form of data tables or functions for online use by the virtual material particle tracking engine.

[0060] The simulation calculations for each particle are independent, and the state simulation of all particles is completed within milliseconds using multi-core parallel processing capabilities. After the simulation is completed, the solvent content distribution of the particle swarm at the outlet of the target devolatilization zone is statistically analyzed, and the mean, standard deviation, and 95th percentile are output as prediction results. The 95th percentile prediction value is used to characterize the upper limit of the possible residual concentration under the most unfavorable residence time combination, providing a robust risk assessment basis for feedforward correction decisions.

[0061] S313: The feedforward correction decision module assesses the risk level based on the virtual tracking prediction results and generates a feedforward correction strategy for process parameters. Next, a feedforward correction decision module is constructed. This module receives the prediction results output by the virtual material particle tracking engine and executes a three-level risk assessment and decision-making process.

[0062] First, the 95th percentile residual value in the prediction results is compared with the target control range of the target devolatilization zone: if the predicted quantile value is lower than the target upper limit, the zone is determined to be in a low-risk state; if it is between 1.0 and 1.2 times the target upper limit, it is determined to be in a medium-risk state; if it exceeds 1.2 times, it is determined to be in a high-risk state.

[0063] Secondly, the direction and magnitude of correction are determined based on the risk level and the dominant controllable variables of the area to be corrected. For example, when the area to be corrected is a secondary high-shear surface renewal devolatilization zone and is classified as medium risk, the temperature parameter with a smooth response and high control accuracy is preferentially selected as the correction variable. Secondly, adjusting the screw speed to enhance the surface renewal frequency is considered. The correction magnitude of each parameter is proportional to the risk level and is limited by the feasible range of process parameters and safety constraints in that area.

[0064] Finally, based on the actual axial position of the material in the screw and the screw speed, the lead time required for the correction action to take effect is calculated, and the timing of the correction command is automatically scheduled to ensure that the correction action is precisely aligned with the time when the target material batch enters the area to be corrected.

[0065] Simultaneously, a coordination priority is set between feedforward correction and real-time feedback adjustment from the material characteristic-process parameter correlation model. Specifically, before material enters a certain zone, feedforward correction has priority and can pre-adjust the parameter settings for that zone; once the material actually enters the zone, the material characteristic-process parameter correlation model takes over and fine-tunes the parameters; the feedforward correction amount is retained as a baseline offset for feedback adjustment rather than overwritten, avoiding conflicts between the two types of control commands.

[0066] S32: When the concentrated material triggers the preset conditions in the first-stage medium-pressure flash devolatilization zone, the coupled prediction model is used to predict the solvent content at the outlet of the current devolatilization zone, and the process parameters of the second-stage high-shear surface updated devolatilization zone are pre-corrected by feedforward.

[0067] Specifically, when the concentrated material reaches the preset trigger condition in the primary medium-pressure flash devolatilization zone, the solvent content at the outlet of the primary medium-pressure flash devolatilization zone is predicted using a coupled prediction model, and the process parameters of the secondary high-shear surface update devolatilization zone are pre-corrected by feedforward, including the following sub-steps: S321: When the concentrated material triggers the preset conditions in the first-stage medium-pressure flash devolatilization zone, the intelligent control system obtains the current state data and the initial process parameter settings of the second-stage high-shear surface to update the devolatilization zone, and obtains the baseline operating conditions. During the operation of the concentrated material in the primary medium-pressure flash devolatilization zone, the intelligent control system initiates the predictive process according to preset trigger conditions. The trigger conditions can be set as follows: the cumulative residence time of the material in the primary medium-pressure flash devolatilization zone reaches a preset proportion (e.g., 60% to 80% of the average residence time in this zone), or the axial position of the material in the screw reaches a preset distance from the outlet of the primary medium-pressure flash devolatilization zone (e.g., 2 to 3 times the screw diameter).

[0068] When the triggering conditions are met, the system automatically acquires the current status data, including the cumulative running time from the inlet of the first-level medium-pressure flash devolatilization zone to the present, the actual temperature and absolute pressure values ​​of each section, and the real-time melt viscosity fed back by the online viscometer.

[0069] Based on the current status data and the mass transfer attenuation rules of the first-stage medium-pressure flash devolatilization zone, the estimated solvent content of the material is calculated by reverse deduction.

[0070] Simultaneously, the current process parameter settings for the secondary high-shear surface renewal devolatilization zone are read, including the temperature setting and absolute pressure setting of the secondary high-shear surface renewal devolatilization zone. This data constitutes the baseline operating condition for the coupled prediction and is fully fed into the virtual material particle tracking engine.

[0071] S322: Using the baseline operating conditions as input, the virtual material particle tracking engine is used to deduce the state evolution trajectory of the material from its current position to the outlet of the first-stage medium-pressure flash devolatilization zone, and output the predicted solvent content at the outlet of the first-stage medium-pressure flash devolatilization zone. The intelligent control system invokes the virtual material particle tracking engine to initialize a set of virtual material particles, setting the current estimated solvent content obtained from S321 and the current actual temperature of the primary medium-pressure flash devolatilization zone as the initial values ​​for each particle. Subsequently, based on the current screw speed and feed flow rate, the system retrieves the corresponding residence time distribution curve from the residence time spectrum library of the primary medium-pressure flash devolatilization zone, and uses Monte Carlo sampling to randomly assign each particle the remaining residence time value from its current position to the outlet of the primary medium-pressure flash devolatilization zone.

[0072] According to the flash mass transfer attenuation rule of the first-stage medium-pressure flash devaporization zone, each particle reads the current temperature setpoint and absolute pressure setpoint of the first-stage medium-pressure flash devaporization zone within each simulation time step, substitutes them into the mass transfer attenuation equation to calculate the attenuation of the solvent content of the particle, and accumulates them until the end of the remaining residence time allocated to the particle, to obtain the set of predicted solvent content values ​​of each particle at the outlet of the first-stage medium-pressure flash devaporization zone.

[0073] After the simulation is completed, the solvent content values ​​of all particles at the outlet of the first-stage medium-pressure flash evaporation and devolvation zone are statistically analyzed, and the results are output to the feedforward correction decision module.

[0074] S323: Through the feedforward correction decision module, a risk assessment is performed on the prediction results of the outlet of the first-stage medium-pressure flash devolatilization zone, and a feedforward correction instruction is generated to update the process parameters of the second-stage high-shear surface devolatilization zone.

[0075] The prediction results output by the virtual tracking engine are fed into the feedforward correction decision module. The predicted solvent content at the outlet of the primary medium-pressure flash devolatilization zone is evaluated to see if it exceeds a preset threshold. If it does, it indicates that the initial solvent content of the concentrated material entering the secondary high-shear surface renewal devolatilization zone will be too high, requiring feedforward correction of the process parameters in the secondary high-shear surface renewal devolatilization zone to enhance devolatilization capacity.

[0076] For cases requiring correction, the correction variable is selected according to preset rules: priority is given to moderately increasing the temperature setpoint of the secondary high-shear surface renewal devolatilization zone within the preset safety range; if the temperature has reached the upper limit, the absolute pressure setpoint is further reduced. The correction magnitude is jointly determined by the prediction deviation value and the mass transfer capacity constraint of the secondary high-shear surface renewal devolatilization zone.

[0077] After the correction instruction is generated, the time offset that the correction instruction for updating the secondary high-shear surface devolatilization zone needs to be issued in advance is calculated based on the current axial position of the material in the primary medium-pressure flash devolatilization zone and the screw speed. The correction instruction with timestamp is then submitted to the decision-making layer scheduling queue.

[0078] At the trigger moment of the command scheduling, the feedforward correction command is converted into a specific control signal and sent to the temperature controller and vacuum regulating valve of the secondary high-shear surface update devolatilization zone. After receiving the command, each actuator immediately performs parameter adjustment and sends an execution confirmation signal back to the system after the adjustment stabilizes.

[0079] The system records a complete event log for this feedforward correction. When the target material batch actually passes through the secondary high-shear surface and updates the devolatilization zone outlet, the near-infrared spectrometer at the corresponding location collects the actual outlet solvent content data, compares the actual value with the historical predicted value, and calculates the cumulative statistics of the prediction error.

[0080] If the prediction error of multiple consecutive batches exceeds the preset allowable range, the online fine-tuning program of the residence time spectrum library of the first-level medium-pressure flash devolatilization zone is automatically triggered. The model is calibrated by correcting the spectrum feature parameters, so that the prediction accuracy of the model continues to improve as the production process progresses, realizing the online self-evolution of the model.

[0081] S4: When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the process parameters of this zone are adjusted according to the current state data using the material property-process parameter correlation model to obtain the reconcentrated material, and the process parameters of the next zone are pre-corrected using the coupled prediction model. Throughout the process of the concentrated material entering the secondary high-shear surface renewal devolatilization zone, the intelligent control system dynamically adjusts the temperature and absolute pressure of the zone using a material characteristic-process parameter correlation model. This allows the material to further remove solvent under the action of high-shear surface renewal, resulting in a re-concentrated material. Simultaneously, when the material reaches the preset trigger condition within the zone, the coupled prediction model is invoked to predict the outlet solvent content when it leaves the secondary high-shear surface renewal devolatilization zone. Based on this prediction, the process parameters of the tertiary high-vacuum-gas stripping synergistic final devolatilization zone are pre-corrected to ensure that the zone is in optimal operating condition when the material enters it.

[0082] When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the process parameters in this zone are adjusted based on the current state data using a material property-process parameter correlation model to obtain the reconcentrated material. The process parameters for the next zone are then pre-corrected using a coupled prediction model, including the following sub-steps: S41: When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the intelligent control system dynamically adjusts the process parameters of the zone using the material characteristics-process parameter correlation model to obtain the reconcentrated material. When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the intelligent control system dynamically adjusts the process parameters in this zone using a material characteristic-process parameter correlation model to obtain a reconcentrated material, including the following sub-steps: S411: Obtain the structural configuration of the secondary high-shear surface update devolatilization zone and set the initial process parameters for this zone; The secondary high-shear surface renewal devolatilization zone is located immediately after the primary medium-pressure flash devolatilization zone, with a length of approximately 12D (D being the screw diameter) along the screw axial direction. The screw configuration in this zone employs a combination design of multiple sets of large-angle interlocking kneading blocks and reverse-threaded elements, forming at least three high-shear surface renewal combination sections along the screw axial direction. The cylinder utilizes a high-precision electric heating and water cooling combined temperature control method, with multiple independent temperature control sections set along the axial direction. An exhaust port is located at the top and connected to the secondary vacuum system via a pipeline.

[0083] Before the concentrated material enters, the intelligent control system retrieves the initial process parameter set based on the target product grade, including the initial temperature setpoint, the initial absolute pressure setpoint, and the initial screw speed setpoint, and sends them to the actuator. If a feedforward correction command for this area has been generated, the correction amount is added to the initial setpoint as a baseline offset.

[0084] S412: After the concentrated material enters, the intelligent control system collects status data in real time and calls the material characteristic-process parameter correlation model for closed-loop adjustment. After the concentrated material enters, the intelligent control system collects status data in real time and calls the material characteristic-process parameter correlation model for closed-loop adjustment. The model automatically identifies the current area as a secondary high-shear surface renewal devolatilization zone, calls the corresponding surface renewal apparent solvent removal rate equation and ideal surface renewal path, outputs the optimal adjustment values ​​for temperature and absolute pressure in this zone, and sends them to the actuator for execution.

[0085] S413: The material is renewed and devolatilized through a high-shear surface, further reducing the solvent content and obtaining a reconcentrated material.

[0086] Under the forced mechanical action of the kneading block and the reverse threaded element, the concentrated material is repeatedly stretched, folded, and turned over, exposing the internal solvent molecules to the surface before being extracted under a medium vacuum environment. The solvent content decreases from the inlet range to the preset target range, the melt viscosity increases, and a reconcentrated material is obtained.

[0087] As the material exits the secondary high-shear surface and renews the devolatilization zone, the residual solvent concentration and melt viscosity are collected by an outlet near-infrared spectrometer and an online viscometer. This data, along with the inlet status, residence time, and process parameter curves, are recorded for subsequent control and online model calibration.

[0088] S42: When the material triggers the preset conditions in the secondary high-shear surface renewal devolatilization zone, the intelligent control system uses a coupled prediction model to pre-correct the process parameters of the tertiary high-vacuum-air stripping synergistic final devolatilization zone.

[0089] When the cumulative residence time of the concentrated material in the secondary high-shear surface renewal devolatilization zone reaches a preset proportion of the average residence time in that zone, or when the axial position approaches the preset distance from the outlet, the current status data is automatically acquired, including the cumulative running time from the inlet of that zone to the present, the actual temperature and absolute pressure values ​​of each section, and the real-time melt viscosity fed back by the online viscometer.

[0090] Based on the current status data and the surface renewal mass transfer attenuation rules of this zone, the estimated current solvent content of the material is deduced. Simultaneously, the initial process parameter settings of the three-stage high-vacuum-gas stripping synergistic final devolatilization zone are read to form the prediction baseline condition.

[0091] Starting from the current state, the virtual material particle tracking engine is used to deduce the state evolution trajectory of the material in the remaining section of the secondary high-shear surface updated devolatilization zone, and output the predicted solvent content at the outlet of the secondary high-shear surface updated devolatilization zone.

[0092] The predicted solvent content at the outlet of the secondary high-shear surface renewal devolatilization zone is compared with the target residual value: if it is lower than the target upper limit, the current parameters are maintained; if it exceeds the limit, the temperature, absolute pressure, and stripping medium injection rate are adjusted sequentially in order of increasing energy consumption. The correction magnitude is proportional to the prediction deviation and the mass transfer capacity constraint of the zone. The system calculates the advance issuance time of the command based on the current position of the material in the secondary high-shear surface renewal devolatilization zone and the screw speed to ensure that the parameters are adjusted in place when the material enters the tertiary high-vacuum-stripping synergistic final devolatilization zone.

[0093] At the trigger moment, a control signal is sent to the temperature controller, ultimate vacuum regulating valve, and stripping injection pump of the three-stage high vacuum-stripping synergistic final devolatilization zone. A correction event log is recorded. When material passes through the outlet of the three-stage high vacuum-stripping synergistic final devolatilization zone, the measured residual value using a near-infrared spectrometer is compared with the predicted value to calculate the error. If the error exceeds the limit for consecutive batches, online fine-tuning of the residence time spectral library in the three-stage high vacuum-stripping synergistic final devolatilization zone is triggered, enabling model self-evolution.

[0094] S5: When the reconcentrated material enters the three-stage high vacuum-gas stripping synergistic final devolatilization zone, the process parameters of this zone are adjusted according to the current state data through the material characteristics-process parameter correlation model, and the optimal process parameters of this zone are solved using a multi-objective optimization algorithm and driven to execute, so as to obtain the devolatilized melt.

[0095] The process involves the following sub-steps: When the reconcentrated material enters the three-stage high-vacuum-air stripping synergistic final devolatilization zone, the process parameters in this zone are adjusted based on the current state data using a material characteristic-process parameter correlation model. A multi-objective optimization algorithm is then used to solve for the optimal process parameters in this zone and drive the execution, resulting in the devolatilized melt. S51: When the reconcentrated material enters the three-stage high vacuum-air stripping synergistic final devolatilization zone, the intelligent control system calls the material characteristic-process parameter correlation model to perform basic closed-loop adjustment.

[0096] The three-stage high vacuum-lift synergistic final devolatilization zone is arranged immediately after the two-stage high-shear surface renewal devolatilization zone, and the screw adopts a shallow-groove pressure-building element configuration. The cylinder uses a combination of high-precision electric heating and water cooling for temperature control, and the exhaust port is connected to an ultimate vacuum system consisting of a Roots pump and a steam jet pump, and integrates a temperature-controlled lift-up medium injection unit.

[0097] After the concentrated material enters the zone, the intelligent control system collects real-time status data according to the control cycle, including the actual temperature value, the actual absolute pressure value, the melt viscosity and the residual solvent concentration data of each section.

[0098] Next, the material properties-process parameters association model is invoked to automatically identify the current region as the three-level high vacuum-stripping synergistic final devolatilization zone. The corresponding stripping-enhanced apparent solvent removal rate equation and ideal stripping enhancement path are invoked, and the online mass transfer coefficient inversion, state migration path prediction and multi-source constraint fusion decision are executed in sequence. The basic adjustment of temperature and absolute pressure in this region is output as the benchmark for closed-loop regulation.

[0099] S52: The intelligent control system calls a multi-objective collaborative real-time optimization algorithm to solve for the optimal setpoints of temperature, absolute pressure and gas stripping medium injection flow rate in the region, based on the basic adjustment provided by the correlation model.

[0100] The decision variables are the temperature, absolute pressure, and stripping medium injection flow rate in the three-stage high-vacuum-stripping synergistic final devolatilization zone. The optimization objectives are the deviation between the outlet solvent residue and the target value (devolatilization effect), the material's cumulative thermal history, and the combined energy consumption of the vacuum pump unit and stripping steam. These three objectives are conflicting: improving the devolatilization effect increases thermal history and energy consumption, while reducing energy consumption may lead to excessive residue. The feasible range of process parameters and the melt delivery viscosity limit are used as constraints.

[0101] Next, a particle population of a preset size is initialized, with each particle corresponding to a set of candidate solutions for decision variables. During the iteration process, the particles are substituted into the apparent solvent removal rate equation to calculate the values ​​of three objective functions. Non-dominated solutions are selected based on Pareto dominance and stored in an external archive. When the archive is full, a crowding distance pruning strategy is used to maintain a uniform distribution of solutions. The particles update their speed and position based on their individual historical best and the global best selected from the archive. After iterating to the termination condition, the Pareto optimal solution set is output.

[0102] Subsequently, a decision matrix containing the Pareto solution and three objectives is constructed. After normalization to eliminate dimensional differences, the objective weights are adaptively adjusted according to the current solvent residue deviation: when the residue deviation is >50ppm, the devolatilization effect is given priority (full devolatilization mode); when the deviation is 20~50ppm, the weights of the three objectives are balanced (balance mode); when the deviation is <20ppm, the thermal history is given priority (quality priority mode).

[0103] The weight switching employs a smooth transition mechanism to avoid process parameter oscillations. The weighted distance between each candidate solution and the positive and negative ideal solutions is calculated, and the solution with the highest relative proximity is selected as the optimal process parameter for the current control cycle.

[0104] The selected optimal temperature, absolute pressure, and stripping medium injection flow rate are converted into control signals and sent to the corresponding actuators. Under the synergistic effect of ultimate vacuum and the stripping medium, residual solvent on the surface and inside the material is efficiently extracted. The microbubbles formed by the stripping medium provide additional phase interfaces and carrying effects for the deep solvent. After this step, the residual solvent in the material is reduced from 1%~3% to below 200ppm, resulting in a pure devolatilization melt.

[0105] S6: The devolatilized melt is homogenized and pressurized, and then granulated through an underwater pelletizing die to obtain granular products.

[0106] Corresponding to the above embodiments, the present invention provides a computer storage medium, including: at least one memory and at least one processor; The memory is used to store one or more program instructions; A processor for running one or more program instructions to execute a devolatilization extrusion granulation method for metallocene solution-processed polyolefin elastomers.

[0107] Corresponding to the above embodiments, this embodiment of the invention provides a computer-readable storage medium containing one or more program instructions, which are executed by a processor to provide a devolatilization extrusion granulation method for metallocene solution-based polyolefin elastomers.

[0108] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions that, when executed on a computer, cause the computer to perform the above-described devolatilization extrusion granulation method for metallocene solution-processed polyolefin elastomers.

[0109] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0110] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0111] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0112] Among them, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0113] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).

[0114] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0115] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using a combination of hardware and software. When applied as software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0116] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers, characterized in that, include: The polyolefin elastomer solution is fed into a twin-screw extruder via a forced feeding device for preheating and initial concentration to obtain the material, and the status data is collected in real time by process instruments. When the material enters the first-stage medium-pressure flash devolatilization zone, the process parameters of this zone are adjusted based on the current state data using the material characteristics-process parameter correlation model to obtain concentrated material. When the concentrated material is in the first-stage medium-pressure flash devolatilization zone, the solvent content at the outlet of the zone is predicted by a coupled prediction model based on the current process parameters and state data, and the process parameters of the second-stage high-shear surface update devolatilization zone are pre-corrected by feedforward. When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the process parameters of this zone are adjusted based on the current state data using the material property-process parameter correlation model to obtain the reconcentrated material, and the process parameters of the next zone are pre-corrected using the coupled prediction model. When the reconcentrated material enters the three-stage high vacuum-gas stripping synergistic final devolatilization zone, the process parameters of this zone are adjusted according to the current state data through the material characteristics-process parameter correlation model. The optimal process parameters of this zone are solved using a multi-objective optimization algorithm and the process is driven to obtain the devolatilized melt. The devolatilized melt is homogenized and pressurized, and then granulated through an underwater pelletizing die to obtain granular products; The material characteristic-process parameter correlation model is composed of a mass transfer coefficient online inversion module, a state transition path prediction module, and a multi-source constraint fusion decision module coupled sequentially. The mass transfer coefficient online inversion module obtains the inlet solvent content, outlet solvent content, and current process parameters of the devolatilization zone where the material is located. It uses the inlet solvent content as the initial condition and substitutes it into the apparent solvent removal rate equation of the corresponding region to calculate the predicted value of the outlet solvent content. The state transition path prediction module constructs a two-dimensional state space for each devolatilization zone based on the solvent content and material viscosity, and obtains the ideal migration path for each zone through offline experiments. The multi-source constraint fusion decision module is used to integrate mass transfer capacity constraints and process safety constraints to solve for the optimal process parameter adjustment amount. The online mass transfer coefficient inversion module is based on the mass transfer mechanism of the devolatilization zone where the material is located. It calls the corresponding apparent solvent removal rate equation according to the region. The specific calculation formula is as follows: in, This is the instantaneous rate of change of solvent concentration within the current control period, i.e., the apparent removal rate. The instantaneous solvent mass fraction of the material; The apparent rate constant of the first-stage medium-pressure flash volatilization zone; For the temperature of the solvent in this region The saturated vapor pressure below; This is the actual absolute pressure in the area; Used as a reference pressure for dimensionless transformation; The pressure driving force index; To update the apparent rate constant of the devolatilization zone on the secondary high-shear surface; This represents the actual temperature in the area. For reference temperature; This represents the screw shear rate in that region. Reference shear rate; This is the actual absolute pressure of the area. Standard atmospheric pressure; These are the effect indices for temperature, shear rate, and vacuum degree, respectively. The apparent rate constant of the final devolatilization zone in the three-stage high vacuum-gas stripping synergistic process; This refers to the actual temperature in the area. This is the actual absolute pressure in the area; Inject flow rate of the air-lifting medium. For reference gas lift flow rate; These are the effect indices for temperature and vacuum, respectively; It is an air-lifting enhancement factor; The construction of the coupled prediction model includes: generating an offline residence time map library for each zone of the twin-screw extruder based on the screw configuration of each zone; constructing a virtual material particle tracking engine to calculate the residence time differences and state evolution process of materials in each zone; and using a feedforward correction decision module to assess the risk level based on the virtual tracking prediction results and generate a feedforward correction strategy for process parameters.

2. The method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers according to claim 1, characterized in that, When the material enters the primary medium-pressure flash devolatilization zone, the process parameters of this zone are adjusted based on the current state data using a material characteristic-process parameter correlation model to obtain concentrated material, including: Construct a material property-process parameter correlation model and pre-install it in the intelligent control system; The material enters the first-stage medium-pressure flash devolatilization zone. Using the material characteristics-process parameter correlation model, the process parameters in this zone are dynamically adjusted based on real-time status data to complete the first-stage devolatilization and obtain concentrated material.

3. The method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers according to claim 1, characterized in that, When the concentrated material is in the primary medium-pressure flash devolatilization zone, the solvent content at the outlet of this zone is predicted using a coupled prediction model based on the current process parameters and state data. Furthermore, feedforward pre-correction is performed on the process parameters of the secondary high-shear surface update devolatilization zone, including: A coupled prediction model based on virtual material tracking and residence time pattern matching is constructed and pre-installed in the intelligent control system; When the concentrated material triggers the preset conditions in the primary medium-pressure flash devolatilization zone, the coupled prediction model is used to predict the solvent content at the outlet of the current devolatilization zone, and the process parameters of the secondary high-shear surface updated devolatilization zone are pre-corrected by feedforward.

4. The method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers according to claim 3, characterized in that, When the concentrated material triggers preset conditions in the primary medium-pressure flash devolatilization zone, the coupled prediction model is used to predict its solvent content at the outlet of the current devolatilization zone, and feedforward pre-correction is performed on the process parameters of the secondary high-shear surface updated devolatilization zone, including: When the concentrated material triggers the preset conditions in the first-stage medium-pressure flash devolatilization zone, the intelligent control system obtains the current state data and the initial process parameter settings of the second-stage high-shear surface to update the devolatilization zone, thus obtaining the baseline operating conditions. Using the baseline operating conditions as input, the virtual material particle tracking engine is used to deduce the state evolution trajectory of the material from its current position to the outlet of the first-stage medium-pressure flash devolatilization zone, and output the predicted solvent content at the outlet of the first-stage medium-pressure flash devolatilization zone. The feedforward correction decision module performs a risk assessment on the outlet prediction results of the first-stage medium-pressure flash devolatilization zone and generates a feedforward correction instruction for updating the process parameters of the second-stage high-shear surface devolatilization zone.

5. The method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers according to claim 1, characterized in that, When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the process parameters in this zone are adjusted based on the current state data using a material property-process parameter correlation model to obtain the reconcentrated material. Furthermore, a coupled prediction model is used to pre-correct the process parameters for the next zone, including: When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the intelligent control system dynamically adjusts the process parameters in this zone using the material characteristics-process parameter correlation model to obtain the reconcentrated material. When the material triggers preset conditions in the secondary high-shear surface renew devolatilization zone, the intelligent control system uses a coupled prediction model to pre-correct the process parameters of the tertiary high-vacuum-air stripping synergistic final devolatilization zone.

6. The method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers according to claim 5, characterized in that, When the concentrated material enters the secondary high-shear surface renewal devolatilization zone, the intelligent control system dynamically adjusts the process parameters in this zone using a material characteristic-process parameter correlation model to obtain the reconcentrated material, including: Obtain the structural configuration of the updated devolatilization zone on the secondary high-shear surface and set the initial process parameters for this zone; After the concentrated material enters, the intelligent control system collects status data in real time and calls the material characteristic-process parameter correlation model for closed-loop adjustment. The material is renewed and volatilized through a high-shear surface, further reducing the solvent content and yielding a reconcentrated material.

7. The method for devolatilization extrusion granulation of metallocene solution-processed polyolefin elastomers according to claim 1, characterized in that, When the reconcentrated material enters the three-stage high-vacuum-stripping synergistic final devolatilization zone, the process parameters of this zone are adjusted based on the current state data using a material characteristic-process parameter correlation model. A multi-objective optimization algorithm is then used to solve for the optimal process parameters of this zone and drive execution, resulting in the devolatilized melt, including: When the reconcentrated material enters the three-stage high vacuum-air stripping synergistic final devolatilization zone, the intelligent control system calls the material characteristic-process parameter correlation model to perform basic closed-loop adjustment. The intelligent control system invokes a multi-objective collaborative real-time optimization algorithm to solve for the optimal setpoints of temperature, absolute pressure, and gas stripping medium injection flow rate in the region, based on the basic adjustments provided by the correlation model.

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