Method and system for evaluating the anti-scour performance of cement stabilized laterite gravel semi-rigid base

Abstract

The application relates to the technical field of road engineering, in particular to a cement stabilized red soil gravel semi-rigid base anti-scouring performance evaluation method and system, which comprises the following steps: appearance detection is conducted on the test piece after scouring test, and appearance evaluation results are obtained; evaluation control indexes of the scouring test are set according to the scouring damage change of the test piece; the mass loss rate is calculated based on the evaluation control indexes and the mass of the test piece corresponding to the time; the mass loss rates of the test piece under different temperature conditions are obtained, and temperature gradient sorting results are obtained; and the anti-scouring performance of the test piece is evaluated according to the temperature gradient sorting results and the corresponding appearance evaluation results. Through the application, the problem that the anti-scouring performance evaluation is not comprehensive and lacks a systematic method after the scouring test of the cement stabilized red soil gravel semi-rigid base is effectively solved, the anti-scouring performance of the cement stabilized red soil gravel semi-rigid base is comprehensively evaluated from multiple factors, and the accuracy and the globality of the evaluation are improved.

Description

Technical Field

[0001] This invention relates to the field of road engineering technology, specifically to a method and system for evaluating the erosion resistance of cement-stabilized red soil gravel semi-rigid base courses. Background Technology

[0002] In recent years, with the rapid growth of my country's economy, the requirements for road traffic have become increasingly stringent. The increase in high-speed, overloaded, and heavy-duty vehicles has exacerbated the degree of road damage. Many road damages are not caused by insufficient load-bearing capacity of the base layer, but by other reasons. Among these reasons, the insufficient erosion resistance of semi-rigid base layers has become an important factor.

[0003] Although cement-stabilized red soil gravel semi-rigid base courses have advantages in various aspects of erosion resistance compared to ordinary semi-rigid base courses, the evaluation of erosion resistance performance remains of paramount importance.

[0004] The information disclosed in this background section is intended only to enhance the understanding of the general background of this disclosure and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0005] This invention provides a method and system for evaluating the erosion resistance of cement-stabilized red soil gravel semi-rigid base courses, thereby effectively solving the problems pointed out in the background art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base courses, the method comprising: The specimens after the scouring test were subjected to visual inspection, and the visual evaluation results were obtained. Based on the changes in erosion damage of the specimen, the evaluation and control indicators for the erosion test are set. Based on the evaluation control indicators and the specimen quality at the corresponding time, the quality loss rate is calculated; The mass loss rate of the specimens under different temperature conditions was obtained, and the temperature gradient ranking results were obtained. The erosion resistance of the specimen is evaluated based on the temperature gradient sorting results and the corresponding appearance evaluation results.

[0007] Furthermore, the specimens after the scouring test were subjected to visual inspection, and the visual evaluation results were obtained, including: An appearance detection model for the specimen is established based on a convolutional neural network. Based on the appearance inspection model, various appearance information of the specimen is inspected, and the appearance evaluation result is obtained, wherein the appearance information includes: crack condition, surface roughness and flatness.

[0008] Furthermore, based on a convolutional neural network, an appearance detection model for the specimen is established, including: Collect a dataset of surface images and label each image with crack location, surface roughness parameters, and smoothness information; A multi-output convolutional neural network model is constructed, which accepts an image as input and outputs multiple predictions of cracks, surface roughness, and smoothness. Define a multi-task loss function and train the model using labeled data; The model performance was tested using a validation set, and the model was optimized and fine-tuned based on the test results.

[0009] Furthermore, based on the changes in erosion damage observed in the specimen, evaluation control indicators for the erosion test are set, including: Based on historical test results, the change in scour volume over time was obtained; The limit time for scouring and damage is determined based on the aforementioned changes; The scouring amount corresponding to the limit time is set as the evaluation control index.

[0010] Further, based on the evaluation control indicators and the specimen quality at the corresponding time, the quality loss rate is calculated, including: Draw a change curve based on the changes described; The mass loss rate of the specimen is calculated based on the scouring amount and the specimen mass at the evaluation control index.

[0011] Furthermore, the mass loss rate of the specimen under different temperature conditions is obtained, and the temperature gradient ranking results are obtained, including: The test specimen was subjected to a scouring test at an adjusted test temperature, and the mass loss rate data of the specimen under different temperature conditions were obtained. Analyze and compare the mass loss rate of the specimens under different temperature conditions; Based on the temperature gradient, the mass loss rate of the specimens is sorted to obtain the temperature gradient sorting result.

[0012] Furthermore, based on the temperature gradient sorting results and the corresponding appearance evaluation results, the erosion resistance of the specimen is evaluated, including: Based on the appearance evaluation results, the erosion resistance of the specimen is qualitatively evaluated. The qualitative assessment results are converted into corresponding numerical indicators, and the qualitative assessment results are obtained. Based on the mass loss rate of the specimen and the temperature gradient ranking results, a correlation analysis was performed on the mass loss rate and the appearance evaluation results at different temperatures, and quantitative evaluation results were obtained. Based on the qualitative and quantitative evaluation results, the erosion resistance performance is classified into grades.

[0013] Furthermore, based on the mass loss rate of the specimen and the temperature gradient ranking results, a correlation analysis is performed on the mass loss rate and the appearance evaluation results at different temperatures, including: The correlation coefficient is used to measure the degree of linear correlation between the quality loss rate and the appearance evaluation results; Create a scatter plot to visualize and compare the temperature with the mass loss rate; Based on the analysis results, the correlation between temperature and quality loss rate and appearance evaluation was determined.

[0014] A system for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base courses, the system comprising: The appearance evaluation result acquisition module performs appearance inspection on the specimens after the scouring test and obtains the appearance evaluation results. The evaluation control index setting module sets the evaluation control index of the scouring test based on the changes in the scouring damage of the specimen. The quality loss rate calculation module calculates the quality loss rate based on the evaluation control indicators and the specimen quality at the corresponding time. The temperature gradient sorting module obtains the mass loss rate of the specimen under different temperature conditions and obtains the temperature gradient sorting results. The erosion resistance evaluation module evaluates the erosion resistance of the specimen based on the temperature gradient sorting results and the corresponding appearance evaluation results.

[0015] Furthermore, the erosion resistance evaluation module includes: The qualitative evaluation unit performs a qualitative evaluation of the erosion resistance of the specimen based on the appearance evaluation results. The numerical conversion unit transforms the qualitative evaluation results into corresponding numerical indicators and obtains the qualitative evaluation results. The quantitative evaluation unit performs a correlation analysis on the mass loss rate and appearance evaluation results at different temperatures based on the mass loss rate and temperature gradient ranking results of the specimen, and obtains quantitative evaluation results. The grading unit classifies the erosion resistance performance based on the qualitative and quantitative evaluation results.

[0016] The technical solution of this invention can achieve the following technical effects: This effectively solves the problem of incomplete scour resistance performance evaluation and lack of systematic methods after the previous scour test of cement-stabilized laterite gravel semi-rigid base course. It realizes the comprehensive evaluation of the scour resistance performance of cement-stabilized laterite gravel semi-rigid base course by considering multiple factors, thereby improving the accuracy and comprehensiveness of the evaluation.

[0017] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0018] 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 without creative effort.

[0019] Figure 1 A flowchart illustrating the method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base courses; Figure 2 A flowchart illustrating the process of establishing a specimen appearance inspection model; Figure 3 A flowchart illustrating the process for setting control indicators for scour test evaluation; Figure 4 A flowchart illustrating the process of obtaining temperature gradient sorting results; Figure 5 A flowchart illustrating the process of classifying the erosion resistance of test specimens. Figure 6 A flowchart illustrating the correlation analysis between mass loss rate and appearance evaluation results at different temperatures; Figure 7 A schematic diagram of the structure for evaluating the erosion resistance performance of cement-stabilized red soil gravel semi-rigid base courses. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0022] Example 1 like Figure 1 As shown, this invention provides a method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base courses. The method includes: S100: Perform visual inspection on the specimens after the scouring test and obtain the visual evaluation results; Specifically, visual inspection mainly involves a comprehensive examination of the surface information of the specimen after the scouring test to assess the degree of damage to the specimen surface, including possible cracks, dents, wear, and other visible physical changes. This helps to determine the extent of scouring damage to the specimen. At the same time, visual inspection provides preliminary information about the material properties. For example, cracks and dents may indicate poor scouring resistance of the specimen, while the absence of obvious damage may suggest good performance.

[0023] S200: Based on the changes in erosion failure of the specimen, set the evaluation control indicators for the erosion test; S300: Calculate the quality loss rate based on the evaluation control indicators and the specimen quality at the corresponding time. S400: Obtain the mass loss rate of the specimen under different temperature conditions and obtain the temperature gradient ranking results; Specifically, the performance of materials or structures may change significantly under different temperature conditions. By conducting tests at different temperatures, the erosion resistance of cement-stabilized red soil gravel semi-rigid base courses can be comprehensively evaluated. At the same time, road base courses are affected by different temperature conditions in actual applications, such as cold winters and hot summers. By simulating these actual usage conditions, the performance of semi-rigid base courses can be evaluated more accurately to ensure their stability and durability on roads.

[0024] S500: The erosion resistance of the specimens is evaluated based on the temperature gradient sorting results and the corresponding appearance evaluation results.

[0025] By comprehensively considering multiple factors such as temperature, mass loss rate, and appearance evaluation, the erosion resistance performance can be fully assessed, providing a more comprehensive understanding of the specimen's performance and helping to gain a deeper understanding of how the erosion resistance performance is under different conditions.

[0026] The technical solution of this invention effectively solves the problem that the scour resistance performance evaluation of cement-stabilized laterite gravel semi-rigid base courses was not comprehensive and lacked a systematic method after the scour test. It realizes the comprehensive evaluation of the scour resistance performance of cement-stabilized laterite gravel semi-rigid base courses by considering multiple factors, thereby improving the accuracy and comprehensiveness of the evaluation.

[0027] As a preferred embodiment of the above, step S100 involves performing an appearance inspection on the specimen after the scouring test and obtaining an appearance evaluation result, including: S110: Establish an appearance inspection model for the specimen based on a convolutional neural network; S120: Based on the appearance inspection model, various appearance information of the specimen is inspected and appearance evaluation results are obtained. The appearance information includes: crack condition, surface roughness and flatness.

[0028] Specifically, based on convolutional neural networks, a specimen appearance detection model is established. This requires training a CNN model that can recognize the appearance features of the specimen, enabling the model to learn how to identify appearance features such as cracks, surface roughness, and smoothness. Once the model has been trained, it can be applied to new specimen images to detect appearance information such as cracks, surface roughness, and smoothness. The model will analyze the image and provide results about these appearance features. The input of the CNN model is the image of the specimen, and the output can be a judgment or score about appearance information such as cracks, surface roughness, and smoothness.

[0029] As a preferred embodiment of the above, such as Figure 2 As shown, step S110 involves establishing an appearance detection model for the specimen based on a convolutional neural network, including: S111: Collect a dataset of surface images and label each image with crack location, surface roughness parameters, and smoothness information; S112: Construct a multi-output convolutional neural network model. The convolutional neural network model takes an image as input and outputs multiple predictions of cracks, surface roughness, and smoothness. S113: Define the multi-task loss function and use labeled data to train the model; S114: Use the validation set to test the model's performance and optimize and fine-tune the model based on the test results.

[0030] Specifically, the first step is to collect a large amount of surface image data of cement-stabilized red soil gravel semi-rigid base courses. These images should include specimens in different states, covering different degrees of cracking, surface roughness, and smoothness. Each image needs to be labeled to identify the location of cracks and measure surface roughness parameters and smoothness information. To build a multi-output convolutional neural network model, multiple branches need to be set in the output layer of the model, with each branch responsible for a prediction task. The model structure should be deep enough to capture complex features. To train the multi-output CNN model, a multi-task loss function needs to be defined, which compares the predictions of crack location, surface roughness, and smoothness with the labeled data. This loss function should comprehensively consider the importance of each task and guide the model to learn effective features during training. A validation set is used to evaluate the model's performance. The validation set includes images not used in training to test the model's generalization ability. Based on the validation results, the model can be optimized and fine-tuned, for example, by adjusting hyperparameters, increasing training data, or introducing regularization techniques to improve the model's accuracy and robustness.

[0031] As a preferred embodiment of the above, such as Figure 3 As shown, in step S200, based on the changes in erosion failure of the specimen, the evaluation control indicators for the erosion test are set, including: S210: Based on historical test results, obtain the change in scouring volume over time; S220: Determine the limit time for scouring failure based on the changing conditions; S230: Set the flushing amount corresponding to the limit time as the evaluation control index.

[0032] Specifically, analyzing historical test data to understand how the erosion rate changes over time is crucial. This can encompass different test results for different specimens, providing a comprehensive dataset. By observing test trends, the time dependence of the erosion rate can be determined, identifying the critical time to erosion failure—the point at which the specimen reaches erosion failure. This is typically determined based on trends and characteristics in historical test data. This time point represents a critical turning point in the specimen's erosion resistance during the experiment. Based on the determined critical time, the corresponding erosion rate is set as the evaluation control index. This evaluation control index can be considered one of the key test results, indicating the specimen's performance in the erosion test. Typically, this index is used to measure performance differences between different specimens and whether the specimen meets specific performance standards.

[0033] As a preferred embodiment of the above, step S300, calculating the quality loss rate based on the evaluation control index and the specimen quality at the corresponding time, includes: S310: Draw a change curve based on the changes; S320: Calculate the mass loss rate of the specimen based on the scouring amount and specimen mass at the evaluation control index.

[0034] Specifically, a change curve is plotted based on the data of the changes. This curve will help to understand more intuitively how the performance of the specimen changes over time. The curve usually shows the relationship between the scouring amount and time. The time point where the evaluation control index is located will be marked on the graph. The scouring amount at the evaluation control index and the mass data of the specimen are used to calculate the mass loss rate of the specimen. This index shows how much mass the specimen lost in the scouring test, thus reflecting its scouring resistance performance.

[0035] As a preferred embodiment of the above, such as Figure 4 As shown, in step S400, the mass loss rate of the specimen under different temperature conditions is obtained, and the temperature gradient ranking results are obtained, including: S410: Adjust the test temperature to conduct a flushing test on the specimen and obtain the mass loss rate data of the specimen under different temperature conditions; S420: Analyze and compare the mass loss rate of specimens under different temperature conditions; S430: Based on the temperature gradient, the mass loss rate of the specimens is sorted to obtain the temperature gradient sorting result.

[0036] Specifically, by analyzing and comparing the mass loss rate data of specimens under different temperature conditions, we can understand the differences in the erosion resistance performance of specimens under different temperature conditions. We will use temperature gradients to sort the mass loss rates of specimens. Temperature gradient sorting will help us determine the performance changes of specimens under different temperature conditions, thereby determining which temperature conditions the specimens are erosion resistant under, so as to evaluate the performance of the specimens in coping with different temperature conditions.

[0037] As a preferred embodiment of the above, such as Figure 5 As shown, in step S500, the erosion resistance of the specimen is evaluated based on the temperature gradient sorting results and the corresponding appearance evaluation results, including: S510: Based on the appearance evaluation results, conduct a qualitative evaluation of the erosion resistance of the specimen; S520: Convert the qualitative assessment results into corresponding numerical indicators and obtain the qualitative assessment results; S530: Based on the mass loss rate and temperature gradient ranking results of the specimens, a correlation analysis is performed on the mass loss rate and appearance evaluation results at different temperatures, and quantitative evaluation results are obtained. S540: Based on the qualitative and quantitative assessment results, the erosion resistance performance is classified into grades.

[0038] Specifically, the results obtained through visual inspection are used for subjective qualitative evaluation. Based on the visual evaluation results, the erosion resistance of the specimens is described, and the qualitative evaluation results are converted into corresponding numerical indicators. This may involve converting the qualitative descriptions into numerical grades to facilitate comparison with other data. Through correlation analysis, the mass loss rate, temperature gradient ranking results, and visual evaluation results are combined. Correlation analysis can reveal the correlation between the mass loss rate and the visual evaluation results under different temperature conditions, thereby providing more quantitative information for a more comprehensive evaluation of erosion resistance. Finally, based on the results of qualitative and quantitative evaluations, the erosion resistance of the specimens is classified into grades.

[0039] As a preferred embodiment of the above, such as Figure 6 As shown, based on the mass loss rate and temperature gradient ranking results of the specimens, a correlation analysis was performed on the mass loss rate and appearance evaluation results at different temperatures, including: A10: Use the correlation coefficient to measure the degree of linear correlation between the quality loss rate and the appearance evaluation results; A20: Create a scatter plot to visualize and compare temperature with mass loss rate; A30: Based on the analysis results, determine the correlation between temperature and the mass loss rate and appearance assessment.

[0040] Specifically, the correlation coefficient is used to measure the degree of linear association between the quality loss rate and the appearance evaluation results. The correlation coefficient is a statistical tool used to measure the linear relationship between two variables. By calculating the correlation coefficient, the correlation between the quality loss rate and the appearance evaluation results can be understood. A scatter plot is a data visualization tool used to display the distribution of data points. Presenting data points related to temperature values ​​and quality loss rate, as well as data points related to temperature values ​​and appearance evaluation results, on the same coordinate plane helps to observe the distribution and trends of data points. Based on the analysis results, the correlation between temperature and quality loss rate and appearance evaluation can be determined. By calculating the correlation coefficient and observing the scatter plot, it can be concluded whether temperature has a correlation with quality loss rate and appearance evaluation results. If the correlation coefficient is positive or negative and significant, or if the scatter plot shows a clear trend, it can be determined that temperature has an important influence on the relationship between these variables.

[0041] Example 2 Based on the same inventive concept as the method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base courses in the foregoing embodiments, this invention also provides a system for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base courses, such as... Figure 7 As shown, the system includes: The appearance evaluation result acquisition module performs appearance inspection on the specimens after the scouring test and obtains the appearance evaluation results. The evaluation control index setting module allows you to set evaluation control indexes for the scouring test based on the scouring failure of the specimen. The quality loss rate calculation module calculates the quality loss rate based on the evaluation control indicators and the specimen quality at the corresponding time. The temperature gradient sorting module obtains the mass loss rate of the specimen under different temperature conditions and obtains the temperature gradient sorting results. The erosion resistance evaluation module evaluates the erosion resistance of the specimens based on the temperature gradient sorting results and the corresponding appearance evaluation results.

[0042] The adjustment system described above in this invention can effectively realize the method for evaluating the erosion resistance of cement-stabilized red soil gravel semi-rigid base courses. The technical effects it can achieve are as described in the above embodiments, and will not be repeated here.

[0043] As a preferred embodiment of the above, the erosion resistance evaluation module includes: The qualitative evaluation unit performs a qualitative evaluation of the erosion resistance of the specimens based on the appearance evaluation results. The numerical conversion unit transforms the qualitative evaluation results into corresponding numerical indicators and obtains the qualitative evaluation results. The quantitative evaluation unit performs a correlation analysis on the mass loss rate and appearance evaluation results at different temperatures based on the mass loss rate and temperature gradient ranking results of the specimens, and obtains quantitative evaluation results. The grading unit classifies the erosion resistance performance based on the qualitative and quantitative evaluation results.

[0044] Similarly, the above-mentioned optimization schemes for the system can also achieve the optimization effects corresponding to the methods in Embodiment 1, which will not be repeated here.

[0045] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base courses, characterized in that, The method includes: The specimens after the scouring test were subjected to visual inspection, and the visual evaluation results were obtained. Based on the changes in erosion damage of the specimen, the evaluation and control indicators for the erosion test are set. Based on the evaluation control indicators and the specimen quality at the corresponding time, the quality loss rate is calculated. The mass loss rate of the specimens under different temperature conditions was obtained, and the temperature gradient ranking results were obtained. The erosion resistance of the specimen is evaluated based on the temperature gradient sorting results and the corresponding appearance evaluation results. Based on the erosion failure changes of the specimen, evaluation control indicators for the erosion test are set, including: Based on historical test results, the change in scour volume over time was obtained; The limit time for scouring and damage is determined based on the aforementioned changes; The scouring amount corresponding to the limit time is set as the evaluation control index.

2. The method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base course according to claim 1, characterized in that, The specimens after the scouring test were subjected to visual inspection, and the visual evaluation results were obtained, including: An appearance detection model for the specimen is established based on a convolutional neural network. Based on the appearance inspection model, various appearance information of the specimen is inspected, and the appearance evaluation result is obtained, wherein the appearance information includes: crack condition, surface roughness and flatness.

3. The method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base course according to claim 2, characterized in that, Based on a convolutional neural network, an appearance detection model for the specimen is established, including: Collect a dataset of surface images and label each image with crack location, surface roughness parameters, and smoothness information; A multi-output convolutional neural network model is constructed, which accepts an image as input and outputs multiple predictions of cracks, surface roughness, and smoothness. Define a multi-task loss function and train the model using labeled data; The model performance was tested using a validation set, and the model was optimized and fine-tuned based on the test results.

4. The method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base course according to claim 1, characterized in that, Based on the evaluation control indicators and the specimen quality at the corresponding time, the quality loss rate is calculated, including: Draw a change curve based on the changes described; The mass loss rate of the specimen is calculated based on the scouring amount and the specimen mass at the evaluation control index.

5. The method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base course according to claim 1, characterized in that, Obtain the mass loss rate of the specimens under different temperature conditions and obtain the temperature gradient ranking results, including: The test specimen was subjected to a scouring test at an adjusted test temperature, and the mass loss rate data of the specimen under different temperature conditions were obtained. Analyze and compare the mass loss rate of the specimens under different temperature conditions; Based on the temperature gradient, the mass loss rate of the specimens is sorted to obtain the temperature gradient sorting result.

6. The method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base course according to claim 1, characterized in that... Based on the temperature gradient sorting results and the corresponding appearance evaluation results, the erosion resistance of the specimen is evaluated, including: Based on the appearance evaluation results, the erosion resistance of the specimen is qualitatively evaluated. The qualitative assessment results are converted into corresponding numerical indicators, and the qualitative assessment results are obtained. Based on the mass loss rate of the specimen and the temperature gradient ranking results, a correlation analysis was performed on the mass loss rate and the appearance evaluation results at different temperatures, and quantitative evaluation results were obtained. Based on the qualitative and quantitative evaluation results, the erosion resistance performance is classified into grades.

7. The method for evaluating the erosion resistance of cement-stabilized laterite gravel semi-rigid base course according to claim 6, characterized in that... Based on the mass loss rate of the specimens and the temperature gradient ranking results, a correlation analysis is performed on the mass loss rate and the appearance evaluation results at different temperatures, including: The correlation coefficient is used to measure the degree of linear correlation between the quality loss rate and the appearance evaluation results; Create a scatter plot to visualize and compare the temperature with the mass loss rate; Based on the analysis results, the correlation between temperature and quality loss rate and appearance evaluation was determined.

8. A system for evaluating the erosion resistance performance of cement-stabilized laterite gravel semi-rigid base courses, characterized in that... The system includes: The appearance evaluation result acquisition module performs appearance inspection on the specimens after the scouring test and obtains the appearance evaluation results. The evaluation control index setting module sets the evaluation control index of the scouring test based on the changes in the scouring damage of the specimen. The quality loss rate calculation module calculates the quality loss rate based on the evaluation control indicators and the specimen quality at the corresponding time. The temperature gradient sorting module obtains the mass loss rate of the specimen under different temperature conditions and obtains the temperature gradient sorting results. The erosion resistance evaluation module evaluates the erosion resistance of the specimen based on the temperature gradient sorting results and the corresponding appearance evaluation results. Based on the erosion failure changes of the specimen, evaluation control indicators for the erosion test are set, including: Based on historical test results, the change in scour volume over time was obtained; The limit time for scouring and damage is determined based on the aforementioned changes; The scouring amount corresponding to the limit time is set as the evaluation control index.

9. The erosion resistance evaluation system for cement-stabilized laterite gravel semi-rigid base courses according to claim 8, characterized in that, The erosion resistance evaluation module includes: The qualitative evaluation unit performs a qualitative evaluation of the erosion resistance of the specimen based on the appearance evaluation results. The numerical conversion unit transforms the qualitative evaluation results into corresponding numerical indicators and obtains the qualitative evaluation results. The quantitative evaluation unit performs a correlation analysis on the mass loss rate and appearance evaluation results at different temperatures based on the mass loss rate and temperature gradient ranking results of the specimen, and obtains quantitative evaluation results. The grading unit classifies the erosion resistance performance based on the qualitative and quantitative evaluation results.

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