A method for testing performance of roadbed materials in seasonally frozen areas

Abstract

The present invention relates to the field of performance testing technology, and in particular to a method for testing the performance of roadbed materials in seasonally frozen areas. It includes: collecting and preprocessing original temperature data, analyzing and optimizing the preprocessed temperature data, and obtaining an optimized temperature gradient; calculating the temperature distribution according to the optimized temperature gradient, and further calculating the freezing depth; calculating the strain data and moisture content of the roadbed material; using a comprehensive performance testing and evaluation algorithm to test and evaluate the performance of the roadbed material, and generate a comprehensive antifreeze performance evaluation coefficient for the roadbed material; testing the performance of the roadbed material according to the comprehensive antifreeze performance evaluation coefficient to obtain a test result; using the spatial distribution of the comprehensive antifreeze performance evaluation coefficient to identify the difference in antifreeze performance of the roadbed at different locations and different time periods, and optimizing the design and construction process of the roadbed material. It solves the technical problems of insufficient accuracy in freezing and thawing monitoring of the roadbed, large errors in freezing depth calculation, and insufficient dynamic strain monitoring.

Description

Technical Field

[0001] The invention relates to the technical field of performance detection, and in particular to a method for detecting the performance of roadbed materials in seasonally frozen areas. Background Art

[0002] In seasonally frozen areas, the roadbed is affected by the seasonal freeze-thaw phenomenon. The moisture in the soil freezes in a low-temperature environment and melts when the temperature rises, causing significant changes in the physical properties of the roadbed structure. The freeze-thaw effect has a direct impact on the stability and bearing capacity of the roadbed, especially the change in freezing depth, which often causes the expansion and contraction of the roadbed material, the generation of cracks, and the weakening of the soil shear strength, resulting in damage to the roadbed structure and affecting traffic safety. Therefore, how to accurately monitor and evaluate the freeze-thaw situation of the roadbed and promptly discover potential structural risks has become an important research topic in road engineering.

[0003] At present, the commonly used roadbed freeze-thaw monitoring method mainly relies on temperature sensors to estimate the freezing depth by measuring temperature changes at different depths. However, this method only calculates the freezing depth based on temperature data, ignoring the complex dynamic process of temperature gradient, soil moisture, soil composition changes and freeze-thaw cycles, resulting in low calculation accuracy of freezing depth and difficulty in accurately reflecting the actual situation of the freeze-thaw process. Traditional temperature monitoring equipment is usually fixedly installed in certain specific locations, unable to fully capture temperature changes at different depths and different parts, and unable to adapt to complex environments with large freeze-thaw changes and long time spans.

[0004] At the same time, the existing roadbed material performance testing methods have the following technical problems: insufficient accuracy of roadbed freeze-thaw monitoring, large errors in freezing depth calculation, and insufficient dynamic strain monitoring. Summary of the invention

[0005] The invention provides a method for detecting performance of roadbed materials in seasonally frozen areas, so as to solve the technical problems of insufficient accuracy of roadbed freeze-thaw monitoring, large calculation error of freezing depth and insufficient dynamic strain monitoring.

[0006] A method for detecting performance of roadbed materials in seasonally frozen areas comprises the following steps:

[0007] S1. Collect and preprocess the original temperature data to obtain the preprocessed temperature data; introduce the multivariable nonlinear heat conduction equation to analyze and optimize the preprocessed temperature data to obtain the optimized temperature gradient of the roadbed in the seasonal freezing area; calculate the temperature distribution according to the optimized temperature gradient; calculate the freezing depth based on the temperature distribution;

[0008] S2. calculating the strain data of the roadbed material, and calculating the moisture content through a temperature-resistivity-time coupled moisture content model based on the detected resistivity data;

[0009] S3. Based on the analysis of temperature data, strain data and resistivity data of roadbed materials by S1 and S2, the comprehensive performance detection and evaluation algorithm is used to detect and evaluate the performance of roadbed materials, and a comprehensive antifreeze performance evaluation coefficient of roadbed materials is generated; the performance of roadbed materials is detected according to the comprehensive antifreeze performance evaluation coefficient to obtain the test results; the spatial distribution of the comprehensive antifreeze performance evaluation coefficient is used to identify the differences in antifreeze performance of roadbeds at different locations and different time periods, and the design and construction process of roadbed materials are optimized.

[0010] Preferably, the S1 specifically includes:

[0011] The specific implementation formula of the multivariable nonlinear heat conduction equation is:

[0012] ,

[0013] in, represents the optimized temperature gradient; is the thermal diffusivity; is in position and time The pre-processed temperature data under It represents the rate of change of temperature gradient; is the correction factor of moisture content to the initial temperature gradient; is in position and time moisture content; is the initial moisture content of the roadbed material before freezing; is the moisture content impact index; is in position and time The preprocessed temperature data and the reference temperature The second spatial derivative of the difference between ; is the reference temperature; is the geothermal heat flow coefficient; is the geothermal heat flux.

[0014] Preferably, the S1 specifically includes:

[0015] Based on temperature distribution , introduce the multi-factor nonlinear freezing depth calculation formula to calculate the freezing depth. The specific formula is as follows:

[0016] ,

[0017] in, is in position and time Depth of freezing below; is the initial freezing depth; is the nonlinear coupling coefficient; is the experience index; is in position and time Resistivity data under; is the initial resistivity data; is the standardized temperature change term, which represents the temperature data in the current temperature distribution With reference temperature relative changes in is an exponential decay function that describes the effect of resistivity data on freezing depth.

[0018] Preferably, the S2 specifically includes:

[0019] The strain and resistivity coupling formula is introduced to calculate the strain data of the roadbed material. The specific formula is:

[0020] ,

[0021] in, is in position and time Strain data of roadbed materials under; is the proportionality coefficient of the roadbed material strain caused by temperature change; The sensitivity coefficient that represents the effect of temperature change on strain; is the proportionality coefficient of the strain of the roadbed material caused by the change in moisture content; is the coefficient of influence of resistivity change on strain; It is an index that describes the effect of resistivity change on strain.

[0022] Preferably, the S2 specifically includes:

[0023] The specific formula of the temperature-resistivity-time coupled moisture content model is as follows:

[0024] ,

[0025] in, is in position and time moisture content; is the proportionality constant between the resistivity data and the moisture content; is the power exponent of the exponential relationship between resistivity data and moisture content; is the temperature influence factor; is the temperature decay constant; is the time correction factor; is the time correction constant; is the coefficient related to time; is the power exponent of the time nonlinear effect.

[0026] Preferably, the S3 specifically includes:

[0027] In the process of implementing the comprehensive performance detection and evaluation algorithm, the influence of the number of freeze-thaw cycles is introduced, and a freeze-thaw cycle factor related to the number of freeze-thaw cycles is designed to represent the effect of freeze-thaw cycles on the antifreeze performance of roadbed materials.

[0028] Preferably, the S3 specifically includes:

[0029] In the process of realizing the comprehensive performance detection and evaluation algorithm, the temperature data and moisture content are subjected to dual nonlinear coupling processing through a composite dual nonlinear function to obtain the dual nonlinear coupling factor of temperature and moisture content.

[0030] Preferably, the S3 specifically includes:

[0031] In the process of implementing the comprehensive performance testing and evaluation algorithm, the microstructural changes of the soil are introduced to obtain the porosity of the soil.

[0032] Preferably, the S3 specifically includes:

[0033] The calculation formula of the comprehensive antifreeze performance evaluation coefficient is:

[0034] ,

[0035] in, is in position and time Comprehensive antifreeze performance evaluation coefficient; , , is the weighting coefficient; is the amplification index; is the weighted coefficient of soil porosity on frost resistance; Indicates the porosity of the soil; represents the freeze-thaw cycle factor; It is a dual nonlinear coupling factor of temperature and moisture content.

[0036] The beneficial effects of the technical solution of the present invention are:

[0037] 1. By setting monitoring points at different depths, real-time temperature data inside the roadbed is collected, and temperature distribution analysis is performed using the optimized temperature gradient and multivariable nonlinear heat conduction equation. This can accurately reflect the temperature changes of the roadbed during the freezing and thawing process, avoiding the limitations of temperature data collected by temperature sensors, thereby improving the accuracy of freezing depth calculation.

[0038] 2. Based on the temperature distribution, a multi-factor nonlinear freezing depth calculation formula is introduced to calculate the freezing depth in real time. The multi-factor nonlinear freezing depth calculation formula not only takes into account the temperature change, but also introduces the influence of factors such as resistivity and soil composition, thereby improving the accuracy and reliability of the freezing depth calculation.

[0039] 3. By introducing the strain and resistivity coupling formula, the strain data of the roadbed material is obtained, which can monitor in real time the volume changes of the roadbed material caused by temperature changes, water freezing / melting and other factors during the freezing and thawing process of the roadbed material, and provide key data for evaluating the performance of the roadbed material.

[0040] 4. Through comprehensive analysis of temperature data, strain data and resistivity data of roadbed materials, and using comprehensive performance detection and evaluation algorithm, a comprehensive antifreeze performance evaluation coefficient of roadbed materials is generated through multi-factor analysis and processing; the comprehensive antifreeze performance evaluation coefficient can provide a scientific basis for roadbed design, construction and maintenance, especially in seasonally frozen areas, and improve the antifreeze ability and long-term stability of the roadbed. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention is a flow chart of a method for detecting performance of roadbed materials in seasonally frozen areas. DETAILED DESCRIPTION

[0042] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] Unless defined otherwise, 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 belongs.

[0044] The specific scheme of the method for detecting the performance of roadbed materials in seasonally frozen areas provided by the present invention is described in detail below with reference to the accompanying drawings.

[0045] See attached Figure 1 , which shows a flow chart of a method for detecting performance of roadbed materials in seasonally frozen areas provided by an embodiment of the present invention, the method comprising the following steps:

[0046] S1. Collect and preprocess the original temperature data to obtain the preprocessed temperature data; introduce the multivariable nonlinear heat conduction equation to analyze and optimize the preprocessed temperature data to obtain the optimized temperature gradient of the roadbed in the seasonally frozen area; calculate the temperature distribution according to the optimized temperature gradient; calculate the freezing depth based on the temperature distribution.

[0047] Firstly, through the address survey data of seasonally frozen areas, the expert experience method is used to analyze the distribution of frozen soil layer and freeze-thaw depth of the roadbed, and the key monitoring depths (such as 30cm, 60cm, 90cm, 120cm, etc.) are determined as monitoring points. At the same time, temperature sensors suitable for low temperature environment and long-term stability (such as RTD temperature sensors or thermocouples) are selected to collect temperature data inside the roadbed in real time at monitoring points at different depths to obtain the original temperature data.

[0048] Furthermore, the original temperature data is preprocessed using existing preprocessing means to obtain preprocessed temperature data.

[0049] The temperature distribution is not only determined by the thermal conductivity of the soil itself, but also affected by factors such as moisture content. The multivariable nonlinear heat conduction equation is introduced to analyze and optimize the preprocessed temperature data to obtain the optimized temperature gradient of the roadbed in the seasonally frozen area. The specific formula is as follows:

[0050] ,

[0051] in, represents the optimized temperature gradient; It is the thermal diffusivity, a physical quantity used to describe the heat diffusion capacity, which is calculated through experimental data or the physical properties of the material (thermal conductivity, density, specific heat capacity); is in position and time The pre-processed temperature data under It indicates the rate of change of temperature gradient, reflects the diffusion of heat inside the roadbed material, and is used to describe the transfer of heat from a higher temperature area to a lower temperature area. is the correction coefficient of moisture content on the initial temperature gradient, taking into account the nonlinear effect of moisture content on heat conduction; is in position and time The moisture content is obtained through resistivity data, and there is a specific process in the subsequent steps; It is the initial moisture content of the roadbed material before freezing, determined by preliminary testing of the roadbed material or analysis of environmental conditions. It is a constant used to standardize the rate of change of moisture content over time; is the moisture content influence index, which indicates the nonlinear influence of moisture content on the optimized temperature gradient; is in position and time The preprocessed temperature data and the reference temperature The second spatial derivative of the difference between the two represents the rate of change of the relative temperature gradient; It is the reference temperature, indicating the temperature at which water begins to freeze; is the geothermal flow coefficient, which indicates the effect of the earth's internal heat flow on the roadbed temperature; It is the geothermal flux density, which represents the heat flow per unit area.

[0052] The specific derivation process of the temperature gradient after optimization of the roadbed in seasonally frozen areas is as follows:

[0053] First calculate the preliminary temperature gradient:

[0054] ,

[0055] in, is the initial temperature gradient, indicating the temperature after pretreatment at time Initial rate of change on is in position and time The pre-processed temperature data under is the thermal diffusivity, a physical quantity used to describe the ability of heat diffusion, which is calculated through experimental data or the physical properties of the material (thermal conductivity, density, specific heat capacity); It indicates the rate of change of temperature gradient, reflects the diffusion of heat inside the roadbed material, and is used to describe the transfer of heat from a higher temperature area to a lower temperature area. is the geothermal flow coefficient, which indicates the effect of the earth's internal heat flow on the roadbed temperature; It is the geothermal flux density, which represents the heat flow per unit area.

[0056] In order to further improve the accuracy of the temperature gradient, the effect of moisture content on freezing depth, that is, the moisture variable of the roadbed material, is introduced to optimize the preliminary temperature gradient and obtain the optimized temperature gradient. :

[0057] ,

[0058] in, is the correction coefficient of moisture content on the initial temperature gradient, taking into account the nonlinear effect of moisture content on heat conduction; is in position and time The moisture content is obtained through resistivity data, and there is a specific process in the subsequent steps; It is the initial moisture content of the roadbed material before freezing, determined by preliminary testing of the roadbed material or analysis of environmental conditions. It is a constant used to standardize the rate of change of moisture content over time; is the moisture content influence index, which indicates the nonlinear influence of moisture content on the optimized temperature gradient; is in position and time The preprocessed temperature data and the reference temperature The second spatial derivative of the difference between the two represents the rate of change of the relative temperature gradient; It is the reference temperature, indicating the temperature at which water begins to freeze.

[0059] Furthermore, according to the optimized temperature gradient, the temperature distribution is obtained by solving the multivariable nonlinear heat conduction equation through existing numerical methods, such as the finite difference method. , represents a temperature field, that is, at all locations and all the time The temperature value below is obtained by solving the multivariable nonlinear heat conduction equation at position and time Temperature data in the temperature distribution below.

[0060] Based on the temperature distribution, a multi-factor nonlinear freezing depth calculation formula is introduced to calculate the freezing depth in real time. The freezing depth changes with the temperature. The specific formula for freezing depth is as follows:

[0061] ,

[0062] in, is in position and time The freezing depth is the depth of frozen water in the soil, which reflects the depth of the frozen soil layer and is affected by many factors such as temperature and resistivity. is the initial freezing depth, which indicates the initial value of the freezing depth without external interference; is the nonlinear coupling coefficient, describing the effect of temperature change on freezing depth, which is related to soil composition and particle size; It is an empirical index used to control the nonlinear effect of temperature change on freezing depth. It determines the intensity of the influence of temperature on freezing depth. Its value ranges from 0.5 to 2 and depends on factors such as soil composition, moisture, and particle structure. is in position and time Resistivity data under; It is the initial resistivity data. In the absence of freezing, the resistivity data of the soil is taken, which indicates the conductivity of the soil in the initial state and is closely related to the type and moisture of the soil. is the standardized temperature change term, which represents the temperature data in the current temperature distribution With reference temperature The relative change and empirical index To enhance or weaken the effect of temperature change on freezing depth, and to simulate the nonlinear effect of temperature on freezing depth; is an exponential decay function that describes the effect of resistivity data on freezing depth.

[0063] When calculating the freezing depth, the temperature distribution is used Temperature data in , rather than directly using the temperature data collected by the temperature sensor, because the temperature distribution of the roadbed is a dynamic process, which is affected by multiple factors, such as the thermal conductivity of the soil, humidity changes, geothermal flow, etc. Different monitoring points and locations of temperature data will lead to different temperature distributions. Although the temperature data provided by the temperature sensor is real-time and very important in practical applications, the limitations of its temperature data collection make it impossible to rely solely on these temperature data to calculate the freezing depth. On the contrary, using the change of temperature gradient to estimate the temperature distribution can overcome these limitations and provide a more comprehensive and accurate basis for the calculation of freezing depth.

[0064] S2. Calculate the strain data of the roadbed material, and calculate the moisture content through a temperature-resistivity-time coupled moisture content model based on the detected resistivity data.

[0065] In order to obtain the strain data of roadbed materials in real time, the strain and resistivity coupling formula is introduced, as follows:

[0066] ,

[0067] in, is in position and time The strain data of the roadbed material under the condition of freezing and thawing reflects the volume change of the roadbed material during freezing and thawing, which is the expansion or contraction caused by freezing and thawing process; It is the proportional coefficient of the strain of the roadbed material caused by temperature change, which reflects the sensitivity of the roadbed material to temperature change; The sensitivity coefficient that represents the effect of temperature change on strain describes the relationship between temperature change and strain; is the proportional coefficient of the strain of the roadbed material caused by the change of moisture content, which represents the effect of moisture content on the volume change of the roadbed material; is in position and time The moisture content is obtained through resistivity data, and there is a specific process in the subsequent steps; It is the initial moisture content of the roadbed material before freezing, determined by preliminary testing of the roadbed material or analysis of environmental conditions. It is a constant used to standardize the rate of change of moisture content over time; is the coefficient of influence of resistivity change on strain, which indicates the influence of resistivity change (such as moisture change) on soil volume change; It is an index that describes the effect of resistivity change on strain and indicates the sensitivity of resistivity change.

[0068] Furthermore, a resistivity sensor is used to detect the resistivity data inside the roadbed material. Based on the resistivity data combined with the temperature data, the temperature-resistivity-time coupled moisture content model is used to analyze the distribution and change of moisture freezing / thawing process in the roadbed material. The specific formula of the temperature-resistivity-time coupled moisture content model is as follows:

[0069] ,

[0070] in, is in position and time moisture content; is the proportionality constant between resistivity data and moisture content, obtained based on the experimental data fit; is the power exponent of the exponential relationship between resistivity data and moisture content, obtained by fitting the experimental data; It is the temperature influence factor, which is used to adjust the effect of temperature on moisture content. It is a constant and depends on the thermal response characteristics of the roadbed material used. It is the temperature decay constant, which indicates the decay rate of the relationship between temperature and moisture content. It is obtained by fitting the thermophysical parameters of specific roadbed materials and experimental data. It is the time correction factor, which is used to adjust the speed of moisture change over time. It is obtained through experiments and reflects the nonlinear characteristics of moisture change. It is the time correction constant used to adjust the amplitude of time change, obtained through experimental fitting, and adjusted according to the specific roadbed material characteristics and environmental conditions; It is a time-related coefficient used to adjust the nonlinear degree of moisture content change over time. It represents the rate of change of moisture content with the increase of time and is obtained by fitting experimental data. It is the power exponent of the nonlinear effect of time, which is used to control the acceleration of the change of moisture content with time. It is obtained by fitting the experimental data and is used to control the effect of time on moisture content.

[0071] S3. Based on the analysis of temperature data, strain data and resistivity data of roadbed materials by S1 and S2, the comprehensive performance detection and evaluation algorithm is used to detect and evaluate the performance of roadbed materials, and a comprehensive antifreeze performance evaluation coefficient of roadbed materials is generated; the performance of roadbed materials is detected according to the comprehensive antifreeze performance evaluation coefficient to obtain the test results; the spatial distribution of the comprehensive antifreeze performance evaluation coefficient is used to identify the differences in antifreeze performance of roadbeds at different locations and different time periods, and the design and construction process of roadbed materials are optimized.

[0072] Based on the analysis of temperature data, strain data and resistivity data of roadbed materials in step S1 and step S2, the comprehensive performance detection and evaluation algorithm is used to detect and evaluate the performance of roadbed materials. The comprehensive performance detection and evaluation algorithm generates a comprehensive antifreeze performance evaluation coefficient of roadbed materials through multi-factor analysis and processing. The performance of roadbed materials is detected according to the comprehensive antifreeze performance evaluation coefficient to obtain the detection results. The specific process is as follows:

[0073] First, the influence of freeze-thaw cycles is introduced. The freeze-thaw process includes the evolution of multiple freeze-thaw cycles. Therefore, the number of freeze-thaw cycles is introduced in the evaluation of antifreeze performance. Design freeze-thaw cycle factors related to the number of freeze-thaw cycles , which represents the effect of freeze-thaw cycles on the antifreeze performance of roadbed materials. The formula is as follows:

[0074] ,

[0075] in, It is the maximum value of the attenuation of the antifreeze performance of the roadbed material. is the decay rate of the effect of freeze-thaw cycles on antifreeze properties; is the number of freeze-thaw cycles, indicating the number of stages of the freeze-thaw process.

[0076] Furthermore, double nonlinear coupling processing is performed on the temperature data and moisture content;

[0077] The changes in temperature data and moisture content not only affect the antifreeze performance of roadbed materials independently, but also interact and influence each other. Moisture content plays an important role in the freezing depth and the expansion effect of roadbed materials. The interaction between the changes in temperature data and moisture content shows a highly nonlinear relationship during the freeze-thaw process. In order to increase this nonlinear coupling effect, the following composite dual nonlinear function is used to describe the coupling between temperature and moisture content:

[0078] ,

[0079] in, It is the dual nonlinear coupling factor of temperature and moisture content, indicating the combined effect of temperature and moisture content on antifreeze performance; is the coefficient of coupling between temperature and moisture content; is the adjustment coefficient of the effect of moisture content on temperature; It is the index of the influence of moisture content on temperature, indicating the nonlinear influence of moisture content on temperature. and are the nonlinear indices of the effects of temperature and moisture content on antifreeze performance, respectively.

[0080] Furthermore, the microstructural changes of the soil are introduced; after multiple freeze-thaw cycles, the physical properties of the soil, such as porosity, bonding strength between particles, and microcracks, change, and the microstructural changes of the soil are introduced into the comprehensive frost resistance performance evaluation coefficient. The soil microstructure changes dynamically with the number of freeze-thaw cycles and temperature changes, and can be expressed as:

[0081] ,

[0082] in, is the initial soil porosity; is the influence coefficient of temperature on soil porosity; and It is a nonlinear index that represents the mutual influence of temperature change and freeze-thaw cycle on soil porosity; is the initial number of freeze-thaw cycles.

[0083] Finally, the calculation formula of the comprehensive antifreeze performance evaluation coefficient is obtained:

[0084] ,

[0085] in, is in position and time The comprehensive antifreeze performance evaluation coefficient indicates the antifreeze ability of the roadbed; , , It is a weighted coefficient, which reflects the contribution of each factor to the antifreeze performance and needs to be determined based on experimental data; is the amplification index, which amplifies the effect of moisture content on antifreeze performance, and its value ranges from 1 to 2; It is the weighted coefficient of soil porosity on antifreeze performance, reflecting the impact of soil microstructure changes on antifreeze performance.

[0086] Furthermore, the performance of the roadbed materials was tested and evaluated based on the comprehensive antifreeze performance evaluation coefficient, and the test results were obtained, including:

[0087] When the comprehensive antifreeze performance evaluation coefficient approaches 1, it indicates that the antifreeze performance of the roadbed material at this location is superior and can withstand the damage caused by freeze-thaw cycles;

[0088] When the comprehensive antifreeze performance evaluation coefficient approaches 0, it means that the antifreeze performance of the roadbed material at this location is poor and may be easily affected by freeze-thaw effects, resulting in structural damage.

[0089] Furthermore, the spatial distribution of the comprehensive antifreeze performance evaluation coefficient can be used to identify the differences in the antifreeze performance of the roadbed at different locations and different time periods. For example, the area close to the roadbed surface may show a greater decline in antifreeze performance due to the direct impact of temperature changes, while the deeper area may be relatively stable. At the same time, according to the distribution of the comprehensive antifreeze performance evaluation coefficient, engineers can optimize the design and construction process of the roadbed material. For example, for areas with poor antifreeze performance, more frost-resistant materials can be selected, or heating and insulation measures can be used to improve the antifreeze ability of the area.

[0090] In summary, a method for testing the performance of roadbed materials in seasonally frozen areas was completed.

[0091] The order of the embodiments of the invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0092] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0093] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for detecting the performance of roadbed materials in seasonally frozen areas, characterized in that: The following steps are involved: S1. Collect and preprocess the original temperature data to obtain the preprocessed temperature data; introduce the multivariable nonlinear heat conduction equation to analyze and optimize the preprocessed temperature data to obtain the optimized temperature gradient of the roadbed in the seasonally frozen area. The specific implementation formula of the multivariable nonlinear heat conduction equation is: ， in, represents the optimized temperature gradient; is the thermal diffusivity; is in position and time The pre-processed temperature data under It represents the rate of change of temperature gradient; is the correction factor of moisture content to the initial temperature gradient; is in position and time moisture content; is the initial moisture content of the roadbed material before freezing; is the moisture content impact index; is in position and time The preprocessed temperature data and the reference temperature The second spatial derivative of the difference between ; is the reference temperature; is the geothermal heat flow coefficient; is the geothermal flux density; According to the optimized temperature gradient, the temperature distribution is calculated; based on the temperature distribution , introduce the multi-factor nonlinear freezing depth calculation formula to calculate the freezing depth. The specific formula is as follows: ， in, is in position and time Depth of freezing below; is the initial freezing depth; is the nonlinear coupling coefficient; is the experience index; is in position and time Resistivity data under; is the initial resistivity data; is the standardized temperature change term, representing the temperature data in the current temperature distribution With reference temperature relative changes in is an exponential decay function describing the effect of resistivity data on freezing depth; S2. Introduce the strain and resistivity coupling formula to calculate the strain data of the roadbed material. The specific formula is: ， in, is in position and time Strain data of roadbed materials under; is the proportionality coefficient of the roadbed material strain caused by temperature change; The sensitivity coefficient that represents the effect of temperature change on strain; is the proportionality coefficient of the strain of the roadbed material caused by the change in moisture content; is the coefficient of influence of resistivity change on strain; It is an index that describes the effect of resistivity change on strain; is obtained by solving the multivariable nonlinear heat conduction equation at position and time Temperature data in the temperature distribution below; It is the reference temperature, indicating the temperature at which water begins to freeze; is in position and time moisture content; is the initial moisture content of the roadbed material before freezing; is in position and time Resistivity data under; is the initial resistivity data; The moisture content is calculated based on the detected resistivity data through the temperature-resistivity-time coupled moisture content model. The specific formula is as follows: ， in, is in position and time moisture content; is the proportionality constant between the resistivity data and the moisture content; is the power exponent of the exponential relationship between resistivity data and moisture content; is the temperature influence factor; is the temperature decay constant; is the time correction factor; is the time correction constant; is the coefficient related to time; is the power exponent of the time nonlinear effect; is in position and time Resistivity data under; is obtained by solving the multivariable nonlinear heat conduction equation at position and time Temperature data in the temperature distribution below; It is the reference temperature, indicating the temperature at which water begins to freeze; S3. Based on the analysis of temperature data, strain data and resistivity data of roadbed materials by S1 and S2, the comprehensive performance detection and evaluation algorithm is used to detect and evaluate the performance of roadbed materials, and the comprehensive antifreeze performance evaluation coefficient of roadbed materials is generated. The calculation formula is: ， in, is in position and time Comprehensive antifreeze performance evaluation coefficient; , , is the weighting coefficient; is the amplification index; is the weighted coefficient of soil porosity on frost resistance; Indicates the porosity of the soil; represents the freeze-thaw cycle factor; is the dual nonlinear coupling factor of temperature and moisture content; is in position and time Depth of freezing below; is in position and time Strain data of roadbed materials under; is in position and time Resistivity data under; is the initial resistivity data; is in position and time moisture content; is the initial moisture content of the roadbed material before freezing; is obtained by solving the multivariable nonlinear heat conduction equation at position and time Temperature data in the temperature distribution below; The performance of the roadbed materials is tested according to the comprehensive antifreeze performance evaluation coefficient to obtain the test results. The spatial distribution of the comprehensive antifreeze performance evaluation coefficient is used to identify the differences in the antifreeze performance of the roadbed at different locations and different time periods, and the design and construction process of the roadbed materials are optimized.

2. A method for detecting the performance of roadbed materials in seasonally frozen areas according to claim 1, characterized in that: The S3 specifically includes: In the process of implementing the comprehensive performance testing and evaluation algorithm, the number of freeze-thaw cycles is introduced The influence of freeze-thaw cycle number on the design of freeze-thaw cycle factor , which represents the effect of freeze-thaw cycles on the antifreeze performance of roadbed materials. The formula is as follows: ， in, It is the maximum value of the attenuation of the antifreeze performance of the roadbed material. is the decay rate of the effect of freeze-thaw cycles on antifreeze properties; is the number of freeze-thaw cycles, indicating the number of stages of the freeze-thaw process.

3. A method for detecting the performance of roadbed materials in seasonally frozen areas according to claim 1, characterized in that: The S3 specifically includes: In the process of implementing the comprehensive performance detection and evaluation algorithm, the temperature data and moisture content are subjected to dual nonlinear coupling processing through a composite dual nonlinear function to obtain the dual nonlinear coupling factor of temperature and moisture content. The formula is as follows: ， in, is the dual nonlinear coupling factor of temperature and moisture content; is the coefficient of coupling between temperature and moisture content; is the adjustment coefficient of the effect of moisture content on temperature; is the influence index of moisture content on temperature, and are the nonlinear indexes of antifreeze performance due to temperature and moisture content changes, respectively; is obtained by solving the multivariable nonlinear heat conduction equation at position and time Temperature data in the temperature distribution below; It is the reference temperature, indicating the temperature at which water begins to freeze; is in position and time moisture content; It is the initial moisture content of the roadbed material before freezing.

4. A method for detecting the performance of roadbed materials in seasonally frozen areas according to claim 1, characterized in that: The S3 specifically includes: In the process of implementing the comprehensive performance testing and evaluation algorithm, the microstructure changes of the soil are introduced to obtain the soil porosity , the formula is as follows: ， in, is the initial soil porosity; is the influence coefficient of temperature on soil porosity; is in position and time The pre-processed temperature data under It is the reference temperature, indicating the temperature at which water begins to freeze; and It is a nonlinear index that represents the mutual influence of temperature change and freeze-thaw cycle on soil porosity; is the number of freeze-thaw cycles; is the initial number of freeze-thaw cycles.

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