Method and system for testing lubricant to improve melt fluidity

Abstract

The invention relates to the technical field of physical performance testing of high polymer materials, and particularly discloses a method and a system for testing lubricant to improve melt flowability, and the method comprises the following steps: acquiring motion state parameters and microstructure image data of a melt under the superposition action of rotary shearing and axial oscillation in real time; a sequence polarization image is collected, a synchronous data pair is generated through time alignment, and structural evolution parameters such as the molecular orientation relaxation rate and the interface slip layer thickness are quantized; a polarization intensity attenuation curve is fitted based on a single exponential attenuation model, and the effect of improving the internal friction of the melt body by the lubricant is directly represented; the difference between the apparent shear rate and the real shear rate is combined to deduce the thickness of an interface slip layer, and the efficiency of the lubricant for reducing external friction is quantified; and finally, a fluidity prediction report containing a multi-dimensional improvement degree index is generated, the efficiency change of the lubricant under different process parameters is revealed, and a scientific basis is provided for new material research and development and processing technology optimization.

Description

Technical Field

[0001] This invention belongs to the field of polymer material physical property testing technology, and relates to a method and system for testing the improvement of melt fluidity by lubricants. Background Technology

[0002] In the processing of polymer materials, such as injection molding and extrusion, melt flowability is a key physical property that determines product quality and production efficiency. To improve the processing performance of polymer materials and reduce melt viscosity, lubricants are typically added to the formulation. Therefore, accurately and efficiently testing and evaluating the effects of different lubricants on improving melt flowability is crucial for the research and development of new materials and the optimization of production processes.

[0003] In existing technologies, common methods for evaluating lubricant performance include testing with a melt flow rate meter or a capillary rheometer. A melt flow rate meter characterizes flowability by measuring the mass of melt extruded from a standard die within a certain time under fixed temperature and load; this is a single-point testing method. A capillary rheometer, on the other hand, obtains the melt's viscosity profile by measuring the pressure drop of the melt flowing through a capillary at different shear rates, thus providing richer information on flowability.

[0004] However, the aforementioned existing technologies have certain limitations. The test conditions of melt flow rate meters are relatively mild and static, which differs significantly from the dynamic, high-shear environments experienced in actual processing. While traditional capillary rheometers can provide data on viscosity changes with shear rate, they still measure macroscopic apparent viscosity. They cannot observe and distinguish in real time the contributions of lubricants to improving melt internal friction and reducing interfacial friction, which are two different mechanisms. They also cannot capture the instantaneous evolution of the melt's internal microstructure under complex dynamic flow fields. This makes the test results insufficiently revealing the true mechanism of lubricant action, and the comprehensiveness and accuracy of the assessment need to be improved. Summary of the Invention

[0005] In view of this, in order to solve the problems mentioned in the background art, a method and system for testing the improvement of melt fluidity of lubricants are proposed.

[0006] The objective of this invention can be achieved through the following technical solution: The first aspect of this invention provides a method for testing the improvement of melt flowability by a lubricant, comprising: S1, obtaining motion state parameters of a composite dynamic shear field applied to a melt sample containing a lubricant.

[0007] S2. Simultaneously acquire sequential polarization images of the melt sample using an in-situ optical observation system to obtain microstructure image data.

[0008] S3. Time-align the motion state parameters with the microstructure image data to generate synchronized data pairs.

[0009] S4. Based on the generated synchronous data pairs, quantify the structural evolution parameters of the melt sample.

[0010] S5. Evaluate the effect of lubricant on improving melt flowability based on the structural evolution parameters of melt samples, and provide feedback.

[0011] A second aspect of the present invention provides a system for testing the improvement of melt flowability by a lubricant, comprising: a motion state parameter acquisition module for acquiring motion state parameters of a composite dynamic shear field applied to a melt sample containing a lubricant.

[0012] The microstructure image acquisition module uses an in-situ optical observation system to simultaneously acquire sequential polarization images of the melt sample, thereby obtaining microstructure image data.

[0013] The synchronization data pair generation module aligns the motion state parameters with the microstructure image data in time to generate synchronization data pairs.

[0014] The structural evolution parameter quantification module quantifies the structural evolution parameters of the melt sample based on the generated synchronous data pairs.

[0015] The improvement effect evaluation and feedback module evaluates the effect of the lubricant on the melt flowability based on the structural evolution parameters of the melt sample and provides feedback.

[0016] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention combines the application of a composite dynamic shear field, in-situ optical observation and synchronous linkage control to achieve in-depth analysis from macroscopic flow phenomena to microscopic mechanisms. The test is no longer limited to obtaining a single flow value, but can quantify how the lubricant improves flow by influencing molecular chain orientation and promoting interfacial slip, providing a scientific basis for the mechanism study and formulation design of lubricants.

[0017] (2) The test results provided by this invention are closer to the actual processing technology and have a stronger predictive ability for the performance of lubricants under complex working conditions. By simulating the dynamic and complex shear environment commonly found in real processing and monitoring its microscopic response in real time, this invention overcomes the defect of traditional static or steady-state testing being disconnected from actual applications, and significantly improves the accuracy of the evaluation results and the industrial guidance value.

[0018] (3) This invention can provide a multi-dimensional performance evaluation report, which intuitively reveals the performance changes of the lubricant under different process parameters. The test results are no longer an isolated score, but a performance map showing the changes of lubricant performance with temperature, pressure, shear rate and other conditions, providing users with comprehensive and detailed decision support for optimizing the processing window and selecting the most suitable lubricant for a specific process. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0021] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0022] 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 embodiments of the present invention, and not all embodiments. 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.

[0023] Please see Figure 1 The first aspect of the present invention provides a method for testing the improvement of melt flowability by a lubricant, comprising: S1, obtaining motion state parameters of a composite dynamic shear field applied to a melt sample containing a lubricant.

[0024] In a specific embodiment of the present invention, the specific steps for obtaining the motion state parameters of the composite dynamic shear field applied to the melt sample containing lubricant include: controlling the composite spindle to perform rotational motion to generate rotational shear components.

[0025] It should be noted that the step of applying the composite dynamic shear field involves subjecting the molten sample loaded in the test chamber to principal dynamic loading, in order to reproduce the complex mechanical environment experienced by the melt during actual processing. This process is achieved through a specially designed composite spindle, which is controlled by an independent drive system and can simultaneously perform rotational and axial oscillating motions. First, the control system drives the rotary motor to make the composite spindle move at a set angular velocity. The material undergoes uniform rotation. This rotational motion generates a tangential displacement gradient in the melt sample between the surface of the composite spindle and the inner wall of the test chamber, thereby generating a stable rotational shear component. This rotational shear component mainly simulates the continuous shearing action of the material during screw extrusion.

[0026] The composite spindle is controlled to perform axial oscillation motion, generating axial oscillation shear components.

[0027] It should be noted that, simultaneously, the control system drives the linear actuator, causing the composite spindle to rotate at a predetermined frequency along its central axis. and amplitude The axial oscillating motion causes the melt sample to be repeatedly squeezed and stretched, generating an axial oscillating shear component that changes dynamically over time. This axial oscillating shear component mainly simulates the unsteady flow during the holding pressure and injection stages of the injection molding process.

[0028] The generated rotational shear component and axial oscillating shear component are superimposed to form a composite dynamic shear field, and the motion state parameters of the composite dynamic shear field are output.

[0029] It should be noted that, finally, by synchronously applying the control commands for the rotational motion and the axial oscillation motion to the composite spindle, the rotational shear component and the axial oscillation shear component are superimposed in time and space, acting together on the molten sample, thereby forming a total shear rate vector field within the test chamber. A composite dynamic shear field that changes dynamically over time is generated, and its motion state parameters are output. These parameters include the angular velocity and shear rate generated by the rotational shear component, the oscillation frequency and amplitude generated by the axial oscillation shear component, and the total shear rate resulting from their superposition. The total shear rate vector field is described below. This can be expressed as a rotational shear rate component. With axial oscillatory shear rate component The vector sum, i.e. equal and The sum of, among which The acquisition depends on angular velocity and cavity geometry, The acquisition depends on the oscillation frequency. ,amplitude and cavity geometry.

[0030] It should also be noted that the rotational shear rate component The calculation formula is: ,in, This indicates the inner radius of the test chamber. Indicates the height of the test chamber; the axial oscillation shear rate component The calculation formula is: ,in, The amplitude represents the oscillation speed.

[0031] This method generates a composite dynamic shear field by superimposing rotational shear and axial oscillation shear modes, significantly surpassing the limitations of single-mode shear testing. It no longer evaluates lubricant performance in isolation under steady-state flow or pure dynamic stress, but rather reveals the comprehensive performance of lubricants under the combined effects of steady-state and dynamic mechanical interactions commonly seen in real extrusion and injection molding processes within a unified test. This composite effect can more effectively stimulate the lubricant's interfacial slip and reduce internal friction mechanisms in complex flow fields, thus obtaining a more practical and predictive assessment of flowability improvement than traditional single-mode testing. This provides more accurate and reliable experimental evidence for lubricant formulation optimization and screening.

[0032] S2. Simultaneously acquire sequential polarization images of the melt sample using an in-situ optical observation system to obtain microstructure image data.

[0033] In a specific embodiment of the present invention, the specific steps of synchronously acquiring sequential polarization images of the melt sample using an in-situ optical observation system to obtain microstructure image data include: emitting polarized light through a polarized light source to generate transmitted polarized light that passes through the melt sample.

[0034] A high-speed polarization camera is used to receive transmitted polarized light passing through the molten sample to generate the original image sequence.

[0035] Image correction is performed on the generated original image sequence, and the sequence polarization image is extracted to form microstructure image data.

[0036] It should be noted that the process of acquiring a sequence of polarized images utilizes the principle of light-matter interaction to perform real-time, non-invasive observation of the internal structure of a molten sample undergoing a complex dynamic shear field. This process begins by emitting a beam of polarized light with a known polarization direction into a transparent observation window within the test chamber through a polarized light source, such as an LED light source filtered by a polarizer or a polarized laser, thus generating a stable incident polarized beam before the molten sample. When this incident polarized beam passes through the flowing molten sample, the melt exhibits a temporary stress birefringence effect due to the orientation of the polymer chains induced by shear stress, which alters the polarization state of the transmitted light. Subsequently, a high-speed polarization camera, equipped with an analyzer, positioned on the light-emitting side of the test chamber, receives and converts the transmitted polarized light carrying information about the internal structure of the melt, transforming the change in polarization state into a change in light intensity for imaging. Because the melt structure changes rapidly under dynamic shear, the high-speed polarization camera continuously captures images at a high frame rate, generating a raw image sequence recording the entire dynamic process. Finally, the original image sequence is subjected to necessary image preprocessing, such as performing dark field correction to eliminate the background noise of the camera sensor and flat field correction to compensate for the non-uniformity of the illumination field, thereby eliminating artifacts and interferences unrelated to the sample structure. Finally, a sequence of polarized images that can accurately reflect the stress distribution and molecular orientation changes inside the melt are extracted. This series of two-dimensional intensity distribution images with timestamps constitutes the microstructure image data.

[0037] This method integrates in-situ optical synchronous observation technology to achieve non-contact, real-time visualization of the internal structure of the melt. Its technological advantage lies in its fundamental breakthrough overcoming the limitation of traditional rheological testing, which can only obtain macroscopic mechanical response parameters. It can directly capture and record microscopic structural information of polymer melts under the action of lubricants in dynamic flow fields, such as molecular chain orientation, stress distribution, and phase interface evolution. This direct observation capability from macroscopic phenomena to microscopic mechanisms allows the analysis of lubricant action mechanisms to no longer rely on indirect inference but to be based on intuitive visual evidence. This greatly improves the scientific rigor and reliability of the evaluation results and reveals deeper flow behaviors that cannot be detected by simple mechanical testing.

[0038] S3. Time-align the motion state parameters with the microstructure image data to generate synchronized data pairs.

[0039] In a specific embodiment of the present invention, the specific steps of aligning motion state parameters with microstructure image data in time to generate synchronized data pairs include: obtaining synchronized triggering conditions for characterizing mechanical events.

[0040] Based on the obtained synchronization triggering conditions, determine the key time points in the motion state parameters.

[0041] At key time points in the motion state parameters, the in-situ optical observation system is triggered to acquire images, obtain synchronously acquired images corresponding to the key time points, and associate them with the corresponding motion state parameters to generate synchronous data pairs.

[0042] It is important to note that generating synchronized data pairs is the core step in establishing a precise temporal correlation between the applied composite dynamic shear field and the observed microstructural image data. This process first acquires motion state parameters by monitoring the real-time motion state of the composite dynamic shear field. Specifically, sensors in the system, such as motor encoders and linear displacement sensors, continuously collect data on the rotational angular velocity of the composite spindle, the frequency, amplitude, and instantaneous phase of the axial oscillation. These data collectively constitute the motion state parameters characterizing the mechanical loading environment. Next, the system aligns the acquired motion state parameters with the acquisition time points of the sequence of polarized images according to a preset synchronization trigger condition. This synchronization trigger condition is a logical rule: when the axial oscillation reaches the phase point of maximum shear rate, the central controller sends a hardware trigger signal to the high-speed polarization camera. The camera performs an exposure the instant it receives the signal, capturing a frame of image, thus forcibly locking its acquisition time point to the precise moment the mechanical event occurs. The system synchronously records this series of trigger moments and their corresponding motion state parameters, thereby generating time-aligned data. Finally, this time-aligned data, containing precise timestamps and mechanical parameters, is matched and merged with the same timestamped microstructural image data output by the camera. The data processing unit iterates through all the data, combining the motion state parameters at each acquisition time point with the microstructural image data at the same time point into an indivisible data unit, ultimately forming a sequence of synchronized data pairs containing complete causal chain information.

[0043] This method, through a mandatory synchronization mechanism, merges the originally independent mechanical loading data stream and optical observation data stream into a synchronized data pair with a precise causal relationship. The resulting technological advantage is a qualitative leap from state observation to causal analysis. Traditional asynchronous testing can only provide the macroscopic mechanical response and microscopic structural morphology of the melt within a vague time period, with the correlation between the two being ambiguous and speculative. This method, however, ensures that each frame of microstructural image precisely corresponds to an instantaneous, known mechanical state, thus directly and definitively revealing how a specific shear field leads to the evolution of a specific molecular structure. This capability enables unprecedented depth and precision in the analysis of lubricant action mechanisms, clearly identifying under what mechanical conditions and through what means the lubricant alters the internal structure of the melt, thereby improving fluidity. This transcends simple data overlay, providing a more insightful analytical tool for scientific research and industrial applications.

[0044] S4. Based on the generated synchronous data pairs, quantify the structural evolution parameters of the melt sample.

[0045] In a specific embodiment of the present invention, the specific steps for quantifying the structural evolution parameters of the melt sample include: extracting image features from the generated synchronous data pairs and generating a polarization intensity change sequence.

[0046] It should be noted that, specifically, the step of quantifying the evolution parameters of the internal structure of the melt is a process of extracting physical meaning from image data. Its core lies in establishing a quantitative correlation between changes in optical signals and the microscopic dynamic behavior and lubrication mechanism of the material. This process first extracts the changes in image features from the synchronous data pairs generated in the previous steps. Specifically, for a predetermined region of interest in the sequence of polarized images, the average light intensity value of each frame is calculated. Since the polarized light intensity is proportional to the stress birefringence inside the melt, and stress birefringence directly reflects the orientation degree of the polymer chains, this series of average light intensity values ​​arranged in chronological order constitutes a polarization intensity change sequence that can characterize the macroscopic changes in molecular orientation.

[0047] Based on the generated polarization intensity change sequence, the molecular orientation relaxation rate parameter is calculated.

[0048] In a specific embodiment of the present invention, the specific steps for calculating the molecular orientation relaxation rate parameter based on the generated polarization intensity change sequence include: identifying intensity decay data segments corresponding to the shear weakening stage from the generated polarization intensity change sequence.

[0049] The intensity decay data segment is fitted to the dynamic relaxation model to obtain the characteristic relaxation time.

[0050] The reciprocal of the acquired characteristic relaxation time is calculated to obtain the molecular orientation relaxation rate parameter.

[0051] It should be noted that the step of calculating the molecular orientation relaxation rate parameter involves a specific kinetic analysis and quantification of the obtained polarization intensity change sequence. This process first requires identifying the peak point in the polarization intensity change sequence, which corresponds to the moment when the shearing force is strongest or has just stopped, and the degree of orientation of the polymer chains inside the melt is highest. By scanning the polarization intensity change sequence on the time axis and finding its local maxima, the peak point can be determined, and the corresponding maximum polarization intensity value can be obtained. Subsequently, the system extracts time-series data from the peak point onwards. This data segment represents the relaxation process after the removal of the external force field, where the molecular chains spontaneously recover from an oriented state to a random coiled state due to internal stress and Brownian motion. For this segment of intensity decay, the software employs a nonlinear least squares fitting method to match the experimental data with a pre-defined kinetic relaxation model. A typical kinetic relaxation model is a single exponential decay model. In this formula, Represents the start of relaxation Intensity of polarized light at time [time] This is the maximum polarization intensity value that has been obtained. For relaxation time, Represents the natural constant, while This is the feature relaxation time to be determined. Through software fitting calculations, a unique feature relaxation time can be obtained. This value characterizes the speed of the relaxation process. Finally, this decay constant, i.e., the characteristic relaxation time, is extracted from the fitted relaxation curve. The reciprocal of this is used as the final molecular orientation relaxation rate parameter, which directly reflects the speed at which the molecular chain deorients.

[0052] This method achieves precise quantification of the internal dynamics of the melt by model fitting and parameter extraction of the polarization intensity decay process. Its technical advantage lies in transforming a dynamic, continuously changing physical process—molecular chain relaxation—into a single, quantitatively meaningful indicator: the molecular orientation relaxation rate parameter. Obtaining this parameter allows for scientific measurement that enables precise numerical comparisons, moving beyond qualitative observation to an evaluation of how lubricants improve internal melt friction and chain mobility. It objectively reflects the degree of reduction in internal friction within the melt under different lubricants or concentrations, providing a stable and reliable basis for a deeper understanding of lubricant mechanisms and performance ranking, significantly improving the resolution and discriminative power of the test.

[0053] By combining molecular orientation relaxation rate parameters and motion state parameters, the interface slip layer thickness parameters are derived, and the molecular orientation relaxation rate parameters and interface slip layer thickness parameters are used together as structural evolution parameters of the melt sample.

[0054] In a specific embodiment of the present invention, the specific steps for deriving the interface slip layer thickness parameter by combining the molecular orientation relaxation rate parameter and the motion state parameter include: extracting the apparent shear rate from the motion state parameter.

[0055] It should be noted that this step builds upon the molecular orientation relaxation rate parameters obtained in the previous step. Through a clever difference and model derivation method, it aims to quantify the lubricant behavior at the interface. First, the instrument geometry parameters set during the experiment, such as the parallel plate radius, are extracted from the motion state parameters contained in the synchronous data pairs. and gap and the measured composite spindle rotational angular velocity Based on these parameters, the apparent shear rate at the edge of the test geometry was calculated. The calculation formula is as follows: This apparent shear rate represents the theoretical flow rate assuming no slippage between the melt and the test wall, i.e., the melt velocity at the interface equals the wall velocity.

[0056] Based on the molecular orientation relaxation rate parameter and the melt constitutive relation, the actual shear rate experienced by the melt bulk is calculated.

[0057] It should be noted that, based on the known molecular orientation relaxation rate parameters and the constitutive relation of the melt, the actual shear rate experienced by the melt bulk is then calculated. Here, a constitutive model that reflects the viscoelasticity of the material is used, such as the simplified Maxwell model, with the following relationship: in, It is the actual shear stress borne by the melt body, which can be obtained from the torque recorded in the motion state parameters. Combining geometric relationships Calculated; It is the elastic modulus of the melt, a material constant that can be determined through independent static experiments or obtained from literature; while This is the characteristic relaxation time we know. By transforming the above constitutive equation, the true shear rate of the melt bulk can be solved. .

[0058] Based on the difference between the extracted apparent shear rate and the actual shear rate experienced by the melt body, and combined with the fluid slip model, the interface slip layer thickness parameters are calculated and derived.

[0059] It should be noted that, finally, based on the apparent shear rate Compared with the calculated true shear rate The difference between the values ​​is used, and combined with a fluid slip model, to calculate the interface slip layer thickness parameters. A generally accepted slip model indicates that the slip velocity at the interface... Shear stress at the wall surface Proportional, the proportionality coefficient is defined as the slip length. In a rotating flow field, the slip velocity is the difference between the apparent shear rate and the actual shear rate multiplied by half the gap height. Therefore, the slip length... The interface slip layer thickness parameter we are looking for can be calculated using the following formula. This slip length The equivalent thickness of the lubricating layer at the interface or its lubrication efficiency was quantified.

[0060] This method cleverly separates and quantifies the wall slip effect by using the microscopic dynamic parameter of molecular orientation relaxation rate as a probe, resulting in significant technical effects. It successfully decouples and independently evaluates the two main mechanisms of lubricant action: improving melt bulk fluidity by reducing internal friction (manifested as a change in molecular orientation relaxation rate) and reducing external friction by forming an interfacial slip layer. Traditional methods often only yield a comprehensive result of improved fluidity, unable to distinguish which mechanism is dominant. This method, through this progressive derivation, not only confirms the existence of interfacial slip but also provides a quantitative result of its equivalent thickness, offering more profound mechanistic guidance for lubricant design and screening, achieving a leap from phenomenological observation to mechanistic quantification. This synergistic analytical capability far exceeds the information value provided by simply measuring molecular relaxation or macroscopic slip phenomena.

[0061] S5. Evaluate the effect of lubricant on improving melt flowability based on the structural evolution parameters of melt samples, and provide feedback.

[0062] In a specific embodiment of the present invention, the specific steps for evaluating the effect of lubricant on melt flowability based on the structural evolution parameters of melt samples include: comparing the structural evolution parameters of the melt sample with the baseline structural evolution parameters of a baseline melt without lubricant to generate a quantified improvement index.

[0063] In a specific embodiment of the present invention, the specific steps for generating a quantitative improvement index include: obtaining weighting coefficients that characterize the importance of different lubrication mechanisms.

[0064] It should be noted that, specifically, this step aims to integrate the multi-dimensional improvement indicators obtained in the previous step into a single scalar that comprehensively reflects the overall performance of the lubricant. First, a set of weighting coefficients characterizing the importance of different lubrication mechanisms needs to be obtained. These two coefficients are the internal lubrication weighting coefficients. and interface lubrication weight coefficient This is a dimensionless value preset based on specific processing application requirements or expected lubrication effects. For example, in applications where improving the surface finish of products is of greater importance, interfacial slip may be set to a high value. A higher value can be set for thick-walled extrusion applications where a reduction in overall melt viscosity is required. The sum of these two weighting coefficients is usually normalized to 1, i.e. .

[0065] Based on the obtained weighting coefficients, the relative improvement values ​​of the molecular orientation relaxation rate parameter and the interface slip layer thickness parameter in the structural evolution parameters are weighted and summed to calculate the comprehensive improvement score.

[0066] The calculated overall improvement score is used as the improvement index.

[0067] It should be noted that, subsequently, based on the obtained weighting coefficients, the relative improvement values ​​of the molecular orientation relaxation rate parameter and the interface slip layer thickness parameter in the structural evolution parameters are weighted and summed to calculate the overall improvement score. This calculation process includes first obtaining the relative improvement values ​​of the two parameters. and The calculation methods are as follows: , in, and These are the molecular orientation relaxation rate parameter and the interface slip layer thickness parameter of the lubricated sample, respectively. and These are the corresponding parameters of the baseline melt. Then, these relative improvement values ​​are combined with weighting coefficients to calculate the overall improvement score. , Finally, the calculated overall improvement score will be... This value serves as a quantifiable indicator of improvement in the final output. It integrates the lubricant's contributions at both the internal and interfacial levels, reflecting the specific application scenario's bias.

[0068] The core technical advantage of this method lies in its ability to transform multiple independent and potentially contradictory evaluation dimensions into a unified, goal-oriented comprehensive evaluation system by introducing adjustable weighting coefficients. This method not only greatly simplifies the horizontal comparison between different lubricant formulations, making the decision-making process more intuitive and efficient, but more importantly, it introduces the concept of application-scenario customization into lubricant performance evaluation. By adjusting the weights, the same set of experimental data can be used to evaluate the suitability of lubricants under different process conditions, thus realizing a shift from general-purpose evaluation to specific-purpose evaluation. This makes the evaluation results no longer universally applicable, but closely linked to specific industrial needs, providing more scientific and practical guidance for the precise screening and formulation design of lubricants.

[0069] The quantitative improvement index is correlated with environmental condition data in the motion state parameters to generate a performance response surface.

[0070] It should be noted that, to investigate the performance changes of the lubricant under different processing environments, a series of experiments are required. These experiments systematically change the environmental conditions included in the motion state parameters, such as test temperature, mean shear rate, or oscillation frequency. Under each set environmental condition, the above testing and calculation process is repeated to obtain a set of corresponding quantitative improvement indices. These multiple sets of data are then integrated, using different environmental conditions as independent variable axes (e.g., temperature on the X-axis, mean shear rate on the Y-axis), and one of the quantitative improvement indices as the dependent variable axis (Z-axis). Interpolation and surface fitting are then performed using 3D plotting software to generate a visualized performance response surface. Each improvement index corresponds to an independent performance response surface.

[0071] Based on the generated performance response surface, a flow prediction report is generated that includes the performance changes of the lubricant under different operating conditions.

[0072] It should be noted that, finally, based on the generated performance response surface, a comprehensive analysis is performed to generate a flowability prediction report. This flowability prediction report determines the process window for optimal lubricant performance by interpreting the topological characteristics of the performance response surface, such as identifying peak regions on the surface. The flowability prediction report also analyzes the relative strengths and weaknesses of the two performance response surfaces in different regions to determine under what operating conditions internal lubrication mechanisms dominate and under what operating conditions interfacial slip mechanisms are more significant, and can interpolate and predict lubricant performance under environmental conditions that have not been directly tested.

[0073] This method achieves significant technical results by comprehensively evaluating microstructural evolution parameters in conjunction with macroscopic environmental conditions. It fundamentally changes the limitations of traditional testing, which only provides single, static scores, generating instead a dynamic and predictive flow forecast report. The core value of this report lies not only in answering the question of whether a lubricant is effective, but also in answering the crucial questions of under what processing conditions the lubricant is most effective and how its effectiveness varies with process parameters. This ability to directly correlate test results with process conditions allows for seamless integration of laboratory data with actual production applications, providing users with unprecedented, precise, and profound insights into lubricant formulation selection and process parameter optimization. Its guiding value far exceeds simply comparing the sum of two isolated data points.

[0074] Reference Figure 2 The second aspect of the present invention provides a system for testing the improvement of melt fluidity of lubricants, comprising: a motion state parameter acquisition module, a microstructure image acquisition module, a synchronous data pair generation module, a structure evolution parameter quantification module, and an improvement effect evaluation feedback module.

[0075] Both the motion state parameter acquisition module and the microstructure image acquisition module are connected to the synchronous data pair generation module, the synchronous data pair generation module is connected to the structure evolution parameter quantification module, and the structure evolution parameter quantification module is connected to the improvement effect evaluation feedback module.

[0076] The motion state parameter acquisition module acquires the motion state parameters of the composite dynamic shear field applied to the molten sample containing lubricant.

[0077] The microstructure image acquisition module uses an in-situ optical observation system to simultaneously acquire sequential polarization images of the melt sample to obtain microstructure image data.

[0078] The synchronization data pair generation module aligns the motion state parameters with the microstructure image data in time to generate synchronization data pairs.

[0079] The structure evolution parameter quantification module quantifies the structure evolution parameters of the melt sample based on the generated synchronous data pairs.

[0080] The improvement effect evaluation and feedback module evaluates the improvement effect of the lubricant on the melt flowability based on the structural evolution parameters of the melt sample and provides feedback.

[0081] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A method for testing the improvement of melt flowability of a lubricant, characterized in that, include: S1. Obtain the motion state parameters of the composite dynamic shear field applied to the melt sample containing lubricant; S2. Simultaneously acquire sequential polarization images of the melt sample using an in-situ optical observation system to obtain microstructure image data; S3. Time-align the motion state parameters with the microstructure image data to generate synchronized data pairs; S4. Based on the generated synchronous data pairs, quantify the structural evolution parameters of the melt sample; S5. Evaluate the effect of lubricant on improving melt flowability based on the structural evolution parameters of melt samples, and provide feedback.

2. The method for testing the improvement of melt fluidity of a lubricant according to claim 1, characterized in that, The specific steps for obtaining the motion state parameters of the composite dynamic shear field applied to the melt sample containing lubricant include: Control the composite spindle to perform rotational motion to generate rotational shear components; The composite spindle is controlled to perform axial oscillation motion, generating axial oscillation shear components; The generated rotational shear component and axial oscillating shear component are superimposed to form a composite dynamic shear field, and the motion state parameters of the composite dynamic shear field are output.

3. The method for testing the improvement of melt fluidity of a lubricant according to claim 1, characterized in that, The specific steps for obtaining microstructure image data by synchronously acquiring sequential polarization images of the melt sample using an in-situ optical observation system include: Polarized light is emitted by a polarized light source to generate transmitted polarized light that passes through the molten sample; A high-speed polarization camera is used to receive transmitted polarized light passing through the molten sample to generate a raw image sequence; Image correction is performed on the generated original image sequence, and the sequence polarization image is extracted to form microstructure image data.

4. The method for testing the improvement of melt fluidity of a lubricant according to claim 1, characterized in that, The specific steps for time-aligning motion state parameters with microstructure image data to generate synchronized data pairs include: Obtain the synchronization triggering conditions used to characterize mechanical events; Based on the acquired synchronization triggering conditions, determine the key time points in the motion state parameters; At key time points in the motion state parameters, the in-situ optical observation system is triggered to acquire images, obtain synchronously acquired images corresponding to the key time points, and associate them with the corresponding motion state parameters to generate synchronous data pairs.

5. The method for testing the improvement of melt fluidity of a lubricant according to claim 2, characterized in that, The specific steps for quantifying the structural evolution parameters of the melt sample include: Image features are extracted from the generated synchronous data pairs to generate a polarization intensity change sequence; Based on the generated polarization intensity change sequence, the molecular orientation relaxation rate parameter is calculated. By combining molecular orientation relaxation rate parameters and motion state parameters, the interface slip layer thickness parameters are derived, and the molecular orientation relaxation rate parameters and interface slip layer thickness parameters are used together as structural evolution parameters of the melt sample.

6. The method for testing the improvement of melt fluidity of a lubricant according to claim 5, characterized in that, The specific steps for calculating the molecular orientation relaxation rate parameter based on the generated polarization intensity change sequence include: Identify the intensity decay data segments corresponding to the shear weakening stage from the generated polarization intensity change sequence; The intensity decay data segment is fitted to the dynamic relaxation model to obtain the characteristic relaxation time; The reciprocal of the acquired characteristic relaxation time is calculated to obtain the molecular orientation relaxation rate parameter.

7. The method for testing the improvement of melt fluidity of a lubricant according to claim 5, characterized in that, The specific steps for deriving the interface slip layer thickness parameter by combining the molecular orientation relaxation rate parameter and motion state parameter include: Extract the apparent shear rate from motion state parameters; Based on the molecular orientation relaxation rate parameter and the melt constitutive relation, the actual shear rate experienced by the melt body is calculated. Based on the difference between the extracted apparent shear rate and the actual shear rate experienced by the melt body, and combined with the fluid slip model, the interface slip layer thickness parameters are calculated and derived.

8. The method for testing the improvement of melt flowability of a lubricant according to claim 1, characterized in that, The specific steps for evaluating the effect of lubricant on melt flowability based on the structural evolution parameters of melt samples include: The structural evolution parameters of the melt sample are compared with the baseline structural evolution parameters of the reference melt without lubricant to generate a quantitative improvement index. The quantitative improvement index is correlated with environmental condition data in the motion state parameters to generate a performance response surface; Based on the generated performance response surface, a flow prediction report is generated that includes the performance changes of the lubricant under different operating conditions.

9. A method for testing the improvement of melt flowability of a lubricant according to claim 8, characterized in that, The specific steps for generating the quantitative improvement index include: Obtain the weighting coefficients that characterize the importance of different lubrication mechanisms; Based on the obtained weighting coefficients, the relative improvement values ​​of the molecular orientation relaxation rate parameter and the interface slip layer thickness parameter in the structural evolution parameters are weighted and summed to calculate the comprehensive improvement score; The calculated overall improvement score is used as the improvement index.

10. A system for testing the improvement of lubricant melt flowability, characterized in that, include: The motion state parameter acquisition module acquires the motion state parameters of the composite dynamic shear field applied to the molten sample containing lubricant. The microstructure image acquisition module uses an in-situ optical observation system to simultaneously acquire sequential polarization images of the melt sample to obtain microstructure image data. The synchronization data pair generation module aligns the motion state parameters with the microstructure image data in time to generate synchronization data pairs. The structural evolution parameter quantification module quantifies the structural evolution parameters of the melt sample based on the generated synchronous data pairs. The improvement effect evaluation and feedback module evaluates the effect of the lubricant on the melt flowability based on the structural evolution parameters of the melt sample and provides feedback.

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