Heat pipe placement method based on frozen soil thaw settlement classification and temperature field distribution law

Abstract

This invention provides a method for heat pipe placement based on the grading of permafrost thaw settlement and the distribution of temperature fields. First, it objectively analyzes the weighting of indicators using the entropy method and combines this with an extension cloud model to determine the thaw settlement level. Then, it uses coupled hydrothermal numerical simulation to analyze the temperature field distribution at each level, and finally analyzes the heat pipe placement parameters based on the simulated temperature field results. This invention can more comprehensively classify thaw settlement levels, simulate the temperature field of different roadbed levels, accurately place heat pipes, reduce heat pipe costs, and improve the effectiveness of heat pipes. It is more suitable for areas with complex distributions of road thaw settlement levels and has practical engineering value and reference significance for reducing road thaw settlement damage, improving the efficiency of heat pipe use, and preventing roadbed diseases in extremely cold permafrost regions.

Description

Technical Field

[0001] This invention relates to the field of frozen soil construction technology, specifically to a method for laying heat pipes based on the thawing and settling classification and temperature field distribution law of frozen soil. Background Technology

[0002] Permafrost is a special type of soil where soil particles are cemented together by ice at temperatures below zero degrees Celsius. It is widely distributed across the Earth, and global warming has exacerbated its degradation. Thawing and settling deformation of roadbeds containing permafrost leads to uneven stress distribution in road engineering projects, altering the mechanical properties of the soil and rock, and seriously threatening road safety. Heat pipes are commonly used to maintain the stability of permafrost in roadbeds. However, during the installation of heat pipes, accurate analysis of the permafrost thaw risk level and temperature field distribution is necessary to improve the efficiency of thaw prevention.

[0003] In the existing technology, it is necessary to use JGJ 118—2011 "Code for Design of Building Foundations in Frozen Soil Areas" to evaluate the thaw settlement level of frozen soil. However, the existing evaluation methods for frozen soil thaw settlement level have the following drawbacks: 1) The evaluation indicators in the thaw settlement classification standard are relatively simple, which leads to deviations between the thaw settlement classification results and the actual situation; 2) The evaluation indicators in the thaw settlement classification standard include water content, void ratio, volumetric ice content and superplastic water content. There is a certain degree of fuzziness and randomness among the various indicators, which leads to deviations in the thaw settlement classification results.

[0004] Therefore, there is an urgent need for a more precise method for deploying heat pipes based on the thawing and settlement classification of frozen soil. Summary of the Invention

[0005] The purpose of this invention is to provide a method for laying out heat pipes based on the thawing and settlement classification and temperature field distribution law of frozen soil, so as to solve at least one problem existing in the prior art.

[0006] To achieve the above objectives, this invention provides a method for heat pipe placement based on frozen soil thaw settlement grading and temperature field distribution, the method comprising:

[0007] Acquire thaw settlement data of subgrade soil samples from the frozen soil subgrade to be constructed, preset frozen soil thaw settlement levels, and limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; among which, the thaw settlement evaluation index includes water content, void ratio, ice content and superplastic water content; the frozen soil thaw settlement level includes five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement and thaw collapse.

[0008] Based on the thaw settlement data of the subgrade soil samples of the frozen soil subgrade to be constructed, the preset thaw settlement level of the frozen soil, and the limit values ​​of the thaw settlement evaluation index corresponding to each thaw settlement level, the correlation degree of each thaw settlement level of the subgrade soil samples is obtained through the preset entropy value extension cloud comprehensive evaluation model; using the maximum correlation degree principle, the thaw settlement level of the subgrade soil samples is determined according to the correlation degree of each thaw settlement level of the subgrade soil samples.

[0009] Based on the preset temperature field hot water coupling numerical simulation, the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed is constructed by using the preset frozen soil subgrade temperature field hot water coupling model.

[0010] Heat pipe installation is carried out based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

[0011] Furthermore, a preferred method is the acquisition method of the entropy-based extended cloud comprehensive evaluation model, including:

[0012] Based on the preset permafrost thaw settlement levels and the limit values ​​of each thaw settlement evaluation index corresponding to each permafrost thaw settlement level, cloud digital feature values ​​are obtained.

[0013] The correlation degree of each thaw settlement evaluation index in the thaw settlement data of the subgrade soil sample is obtained by using cloud digital feature values, and an extension cloud matrix is ​​constructed based on the correlation degree. S The weight vector of the melting and sedimentation evaluation index is obtained using the entropy method. W According to the weight vector of the melting and settling evaluation index W He Ke Tuo Yun Matrix S The comprehensive extension cloud evaluation matrix is ​​obtained through the following formula. Q ;

[0014]

[0015] in, w t Indicates the first t The weight of each evaluation indicator for financial settlement, μ nm This indicates the correlation between various thaw settlement evaluation indicators in the thaw settlement data of subgrade soil samples. m express m Each level of subsidization n express n Individual evaluation indicators for financial settlement.

[0016] Furthermore, a preferred method is to obtain the weights of the melting and settling evaluation indicators using the entropy method, including:

[0017] according to r One sample to be evaluated and t Each set of evaluation indicators was used to obtain the original initial data matrix. X and ther The first sample t The original values ​​of the evaluation indicators for the project's financial settlement;

[0018] For the original initial data matrix X Perform normalization to obtain a standardized matrix. Y = ( y rt ), and according to the first r The first sample t The original values ​​of the evaluation index are obtained by standardizing the original values ​​to obtain the ratio of the original values ​​to the total values, and then the first value is obtained. t The entropy value of any index in the melting and sedimentation evaluation index e t and according to the first t The entropy value of any index in the melting and sedimentation evaluation index e t Get the t The coefficient of difference among various evaluation indicators of financial settlement;

[0019] According to the t The difference coefficient of the first sedimentation evaluation index is obtained by the following formula. t Weights of each sinking evaluation index w t :

[0020]

[0021] in, g t For the first t The coefficient of difference of the evaluation indicators of the project's sinking.

[0022] Furthermore, a preferred method is a method for obtaining temperature field coupled numerical simulation of hot water, including:

[0023] Establish the governing equations for the temperature field and the moisture field;

[0024] Based on the solid-liquid ratio and relative saturation, the temperature field control equation and the moisture field control equation are coupled to obtain a hot water coupled model of the temperature field of frozen soil subgrade.

[0025] The temperature field control equations and moisture field control equations in the coupled temperature field and hot water model of frozen soil subgrade are transformed into partial differential equations with coefficients that can be recognized by COMSOL Multiphysics software.

[0026] Using COMSOL Multiphysics software, a numerical simulation of the temperature field coupled with hot water was conducted based on the transformed temperature field hot water coupling model of the frozen soil subgrade.

[0027] Furthermore, a preferred method is to construct the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed using a pre-set thermo-thermal coupling model of the frozen soil subgrade temperature field. This method includes...

[0028] Construct a subgrade model for the frozen soil subgrade under construction;

[0029] Based on the subgrade model, the upper boundary conditions of the subgrade temperature field simulation, and the physical parameters of the subgrade to be constructed, the temperature field of the thaw settlement level of the subgrade to be constructed is constructed through the pre-set frozen soil subgrade temperature field hot water coupling model.

[0030] Furthermore, a preferred method is to construct heat pipe installation based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed, including:

[0031] Based on the annual ground temperature variation over time at a set distance downwards from the middle of the roadbed in the vertical direction, the temperature field contour map, and the temperature field curve at different locations of the roadbed, the heat pipe installation is carried out.

[0032] Among them, based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed, the thaw settlement level of the frozen soil subgrade to be constructed, and the annual temperature change at the frozen soil subgrade to be constructed, a diagram showing the annual ground temperature change over time at a set distance downward from the middle of the subgrade in the vertical direction is drawn.

[0033] Based on the annual ground temperature variation map, draw the temperature field contour map corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

[0034] Furthermore, a preferred method is to achieve the upper boundary condition for simulating the roadbed temperature field using the following formula based on boundary layer theory:

[0035]

[0036] in, T 0 This represents the local initial annual average temperature; G(t) The annual average temperature increases with each year, in °C. a ; ζ d The annual amplitude of the daily average temperature, in °C; t For the length of time, Φ = π .

[0037] This invention also includes a heat pipe deployment system based on the grading of frozen soil thaw settlement and the distribution law of temperature field. The system includes,

[0038] The data acquisition unit is used to acquire the thaw settlement data of the subgrade soil samples of the frozen soil subgrade to be constructed, the preset frozen soil thaw settlement level, and the limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; among them, the thaw settlement evaluation index includes water content, void ratio, ice content and superplastic water content; the frozen soil thaw settlement level includes five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement and thaw collapse.

[0039] The thaw settlement level determination unit is used to obtain the correlation degree of each thaw settlement level of the subgrade soil sample based on the thaw settlement data of the subgrade soil sample to be constructed, the preset thaw settlement level of the frozen soil, and the limit values ​​of each thaw settlement evaluation index corresponding to each thaw settlement level. It uses a preset entropy value extension cloud comprehensive evaluation model to obtain the correlation degree of each thaw settlement level of the subgrade soil sample. Using the maximum correlation degree principle, it determines the thaw settlement level of the subgrade soil sample based on the correlation degree of each thaw settlement level of the subgrade soil sample.

[0040] Temperature field construction unit is used to construct the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed based on the preset temperature field hot water coupling numerical simulation.

[0041] The construction unit is used to install heat pipes according to the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

[0042] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0043] Memory, storing at least one instruction; and

[0044] The processor executes the instructions stored in the memory to implement the steps in the adaptive deployment method of the power transmission inspection terminal described above.

[0045] The present invention also protects a computer-readable storage medium storing a computer program that, when executed by a processor, implements the adaptive deployment method for power transmission inspection terminals as described above.

[0046] As described above, the present invention provides a method and system for heat pipe placement based on the classification of permafrost thaw settlement and the distribution law of temperature field. This method constructs an entropy-weighted extension cloud model by embedding the entropy weighting method into the extension cloud model to determine the permafrost thaw settlement level. Then, it analyzes the temperature field distribution law of each thaw settlement level using a roadbed temperature field hot water model. Based on the roadbed temperature field of different thaw settlement levels, it designs heat pipe placement parameters and performs heat pipe placement construction. The beneficial effects are as follows:

[0047] 1) In view of the problems of fuzzy classification of existing frozen soil settlement level evaluation, inability to resolve fuzzy relationships between indicators, and the current specifications having single indicators, the evaluation results are difficult to accurately reflect the frozen soil settlement level. This invention can better solve the fuzzy problem between multiple indicators and evaluate the frozen soil settlement level; the roadbed temperature field numerical model can more intuitively simulate and predict the roadbed settlement, better analyze the temperature field distribution law, and design heat pipe layout parameters for different frozen soil settlement levels.

[0048] 2) To address the problem in existing technologies that struggle to distinguish between melt-settlement and strong melt-settlement when determining higher-level thawing levels, resulting in some bias in the determination results, the entropy method can objectively evaluate the weight of indicators. The extension cloud model can resolve the ambiguity between indicator levels, avoiding deviations in melt-settlement level classification due to this ambiguity. Therefore, the entropy extension cloud model is used to determine the thawing level of permafrost under multiple factors.

[0049] 3) Based on the entropy extension cloud model, the thaw settlement level of frozen soil is accurately determined. Then, combined with the temperature field-thermal coupling model, the characteristics of heat transfer in the soil's internal temperature transfer and the heat transfer during the ice-water phase change process are effectively analyzed. This invention studies the temperature field distribution law of different thaw settlement levels, and through the results of temperature field numerical simulation, it can more accurately and effectively analyze the layout parameters of heat pipes. This makes the model of this invention more applicable to scenarios with complex distribution of road thaw settlement levels.

[0050] To achieve the foregoing and related objectives, one or more aspects of the invention include the features that will be described in detail below and particularly pointed out in the claims. The following description details certain exemplary aspects of the invention. However, these aspects indicate only a few of the various ways in which the principles of the invention can be used. Furthermore, the invention is intended to include all such aspects and their equivalents. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the process principle of the heat pipe layout method based on the thawing and settling classification and temperature field distribution law of frozen soil according to an embodiment of the present invention.

[0052] Figure 2 This is a sample melting and settling grade classification diagram provided in the application examples of this invention;

[0053] Figure 3(a) is a diagram showing the classification of sample moisture content indices in the specification provided by the application example of this invention;

[0054] Figure 3(b) is a graph showing the porosity and volumetric ice content of the sample in the specification provided by the application example of this invention.

[0055] Figure 4(a) is a cloud droplet diagram of the water content of each evaluation index melting and settling level provided in the application example of the present invention;

[0056] Figure 4(b) is a porosity cloud droplet diagram of the melting and settling levels of various evaluation indicators provided in the application example of the present invention;

[0057] Figure 4(c) is a cloud droplet diagram of ice content for each evaluation index melt deposition level provided in the application example of the present invention;

[0058] Figure 4(d) is a superplastic moisture content cloud droplet diagram of each evaluation index melting and settling level provided in the application example of the present invention;

[0059] Figure 5(a) is a cross section of the roadbed model provided in the application example of the present invention;

[0060] Figure 5(b) is a grid division diagram of the roadbed model provided in the application example of the present invention;

[0061] Figure 6 This is a comparison chart of measured and simulated monthly average temperature values ​​provided in an embodiment of the present invention;

[0062] Figure 7(a) is a temperature field diagram of the melting and settling grade temperature field in January provided by an embodiment of the present invention;

[0063] Figure 7(b) is a temperature field diagram of the melting and settling grade temperature field in May provided by an embodiment of the present invention;

[0064] Figure 7(c) is a temperature field diagram of the melting and settling grade temperature field in October provided by an embodiment of the present invention;

[0065] Figure 7(d) is a temperature field diagram of the melting and settling grade temperature field in December provided by an embodiment of the present invention;

[0066] Figure 7(e) is a temperature field diagram of the strong melting and sinking grade temperature field in January provided by an embodiment of the present invention;

[0067] Figure 7(f) is a temperature field diagram of the strong melting and sinking grade temperature field in May provided by an embodiment of the present invention;

[0068] Figure 7(g) is a temperature field diagram of the strong melting and sinking grade temperature field in October provided by the embodiment of the present invention;

[0069] Figure 7(h) is a temperature field diagram of the strong melting and sinking grade temperature field in December provided by the embodiment of the present invention;

[0070] Figure 8(a) is a diagram showing the annual temperature variation of the thawed subgrade provided in the embodiment of the present invention;

[0071] Figure 8(b) is a diagram showing the overall temperature variation of the strongly fused subsidence roadbed provided in the embodiment of the present invention;

[0072] Figure 9(a) is a graph showing the change of site temperature over time in the thawed subgrade temperature provided in the embodiment of the present invention;

[0073] Figure 9(b) is a graph showing the change of site temperature over time in the strongly fused subgrade of the present invention.

[0074] Figure 10(a) is a contour map of the temperature field of the thawed roadbed provided in an embodiment of the present invention;

[0075] Figure 10(b) is a contour map of the temperature field of the strongly fused subsidence roadbed provided in an embodiment of the present invention;

[0076] Figure 11(a) is a temperature field curve of the road surface and the subgrade location provided in the embodiment of the present invention.

[0077] Figure 11(b) is a temperature field curve of the road surface and the subgrade location of the strong melting and settling subgrade provided in the embodiment of the present invention;

[0078] Figure 12 This is a schematic diagram of a heat pipe deployment system based on the thawing settlement classification and temperature field distribution law of frozen soil according to an embodiment of the present invention.

[0079] Figure 13 This is a schematic diagram of an electronic device based on the heat pipe layout method according to an embodiment of the present invention, which is based on the grading of frozen soil thawing and the distribution law of temperature field. Detailed Implementation

[0080] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention. Where specific techniques or conditions are not specified in the embodiments, they should be performed in accordance with the techniques or conditions described in the literature in this field, or according to the product instructions. Reagents or instruments whose manufacturers are not specified can be purchased from legitimate channels as conventional products.

[0081] The various embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0082] Figure 1 The process principle of the heat pipe placement method based on the thawing settlement classification and temperature field distribution law of the present invention is described in detail in this embodiment. Specifically, Figure 1 This is a schematic diagram illustrating the flow principle of the heat pipe placement method based on the thawing and settlement grading and temperature field distribution law of this invention. Figure 1 As shown, the method includes steps S110 to S140.

[0083] S110. Obtain the thaw settlement data of the subgrade soil samples of the frozen soil subgrade to be constructed, the preset frozen soil thaw settlement level, and the limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; wherein, the thaw settlement evaluation index includes water content, void ratio, ice content and superplastic water content; the frozen soil thaw settlement level includes five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement and thaw collapse.

[0084] Specifically, according to existing industry standards, samples are classified into thaw settlement levels based on thaw settlement coefficient and superplastic moisture content. In step 110, some samples showed thaw settlement coefficients that met the standard criteria, but their superplastic moisture content was outside the standard grading limits, posing a significant risk to the judgment results. By adding superplastic moisture content as an indicator affecting frozen soil thaw settlement, and selecting moisture content, void ratio, ice content, and superplastic moisture content as evaluation indicators, a comprehensive evaluation of frozen soil thaw settlement levels is conducted. The selection principles for the indicators are as follows: Moisture content is one of the important factors affecting permafrost thaw settlement. Due to rising average annual temperatures, the rate of permafrost thawing accelerates, increasing the moisture content inside the roadbed and reducing the bearing capacity of the soil, thus affecting the degree of roadbed thaw settlement. The void ratio has a significant impact on the content of pore ice in permafrost. Affected by external temperatures, the melting of pore ice inevitably leads to a large number of pores inside the soil, affecting secondary thaw settlement to a certain extent. Using void ratio, moisture content, ice content, and superplastic moisture content together as indicators for judging thaw settlement levels provides a more comprehensive assessment. Ice content is affected by air temperature and has a certain correlation with factors such as moisture content and void ratio. Superplastic moisture content characterizes the plastic state of the soil and is an essential factor in evaluating the degree of permafrost thaw settlement.

[0085] S120. Based on the thaw settlement data of the subgrade soil samples of the frozen soil subgrade to be constructed, the preset thaw settlement level, and the limit values ​​of each thaw settlement evaluation index corresponding to each thaw settlement level, the correlation degree of each thaw settlement level of the subgrade soil samples is obtained through the preset entropy value extension cloud comprehensive evaluation model; using the maximum correlation degree principle, the thaw settlement level of the subgrade soil samples is determined according to the correlation degree of each thaw settlement level of the subgrade soil samples.

[0086] Currently, existing standards for determining the level of permafrost thawing settlement use a single index, which fails to address the ambiguity and randomness between indices. When determining higher levels, it is difficult to distinguish between thawing settlement and strong thawing settlement, leading to certain biases in the results. However, the entropy method can objectively evaluate the weight of indices, and the extension cloud model can resolve the ambiguity between index levels, avoiding biases in thawing settlement classification caused by this ambiguity. Therefore, this invention embeds the entropy weighting method into the extension cloud model to construct an entropy-based extension cloud model, which is more suitable for determining the level of permafrost thawing settlement under multiple factors.

[0087] It should be noted that the extension cloud model uses the normal cloud model ( Ex , En , He To replace the characteristic values ​​of things in extension theory VTo characterize the randomness and fuzziness in the evaluation process, a standard extension cloud model for the evaluation indicators is constructed. Based on the different data sources and properties of the evaluation indicators, extension theory is used to classify the original data of each evaluation indicator into different levels; simultaneously, the cloud model is used to restore the random uncertainty of the boundary values ​​of the classification level constraint intervals of the evaluation indicators. The expected value of the evaluation indicator cloud model is calculated through the conversion relationship between interval numbers and the normal cloud model. Ex ,entropy En hyperentropy He Cmax and Cmin are the left and right boundary values ​​of the standard extensible cloud model, respectively.

[0088] In this embodiment, the extension cloud model is a multi-index evaluation method that combines the normal cloud model with the matter-element extension theory. By determining the cloud digital characteristic value (i.e. cloud parameter), correlation degree and weight of each index, the evaluation of the permafrost thaw settlement level can be achieved.

[0089] Specifically, the method for obtaining the entropy-valued extension cloud comprehensive evaluation model includes:

[0090] S1201. Obtain cloud digital feature values ​​based on the preset frozen soil thaw settlement levels and the limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; S1202. Obtain the correlation degree of each thaw settlement evaluation index in the thaw settlement data of the subgrade soil sample based on the cloud digital feature values, and construct an extension cloud matrix based on the correlation degree. S The weight vector of the melting and sedimentation evaluation index is obtained using the entropy method. W According to the weight vector of the melting and settling evaluation index W and the aforementioned extension cloud matrix S Obtain a comprehensive extension cloud evaluation matrix. Q .

[0091] The extension cloud model expression is:

[0092] (1)

[0093] (2)

[0094] In the formula: R j For the first j Each melting level corresponds to a unit of matter. N j For the first j Each level of subsidization c j For the first j Characteristic indicators of evaluation indicators in each level of subsidence. v j for N j Regarding cj The eigenvalues ​​are replaced with fixed eigenvalues ​​in the form of a cloud model.

[0095] Cloud model theory represents information with randomness and fuzziness as an uncertain mathematical model to achieve the transformation between qualitative and quantitative aspects of the research object's boundary, usually expressed as expectation. Ex ,entropy En and hyperentropy He Cloud digital feature value representation;

[0096] (3)

[0097] (4)

[0098] (5)

[0099] In the formula: C max , C min These are the maximum and minimum boundary values ​​for each level of melting and settling evaluation. He The values ​​can be adjusted according to the actual uncertainty of the corresponding evaluation indicators, that is, the values ​​can be determined based on the discreteness of the cloud droplets; the present invention takes... =0.0001.

[0100] Methods for obtaining the weights of melting and settling evaluation indicators using the entropy method include: S1211, based on... r One sample to be evaluated and t Each set of evaluation indicators was used to obtain the original initial data matrix. X and the r The first sample t The original values ​​of the evaluation index of the project sinking; S1212, the original initial data matrix X Perform normalization to obtain a standardized matrix. Y = ( y rt ), and according to the first r The first sample t The original values ​​of the evaluation index are obtained by standardizing the original values ​​to obtain the ratio of the original values ​​to the total values, and then the first value is obtained. t The entropy value of any index in the melting and sedimentation evaluation index e t and according to the first t The entropy value of any index in the melting and sedimentation evaluation index e t Get the t The difference coefficient of each melting and settling evaluation index; S1213, according to the first t The difference coefficient of the first sedimentation evaluation index is obtained by the following formula. tWeights of each sinking evaluation index w t .

[0101] In the specific implementation process, it is assumed that the settling level has m There are 1, n The complex element matrix model has several evaluation indicators. U for:

[0102] (6)

[0103] In the formula: μ nm ( x nm () represents the corresponding cloud cover value. x nm The degree of correlation, that is, representing ( Ex nm , En nm , He nm ), m and n These are the characteristic value serial numbers of the evaluation level and evaluation index, respectively, i.e., the object-cloud dimension.

[0104] The correlation between the subgrade soil samples and the various indices of the thaw settlement level of the frozen soil subgrade under evaluation was calculated based on the composite element matrix model.

[0105] Among them, Matlab software was used to generate En As the mean, with He Normal random numbers with standard deviation En nm ′ Let the deterministic values ​​in the sample to be evaluated be x nm The correlation degree is then calculated using formula (7):

[0106] (7)

[0107] The correlation degree of each thaw settlement index in the subgrade soil sample of the frozen soil subgrade to be evaluated was calculated according to Formula 7, and the evaluation result S was constructed by constructing the extension cloud matrix:

[0108] (8)

[0109] On the other hand, the entropy method is an objective evaluation method that reflects the importance of an indicator by calculating its entropy value. The formula for calculating the entropy value is as follows:

[0110] Assume there is r One sample to be evaluated. t Each evaluation indicator, its original initial data matrix X:

[0111] (9)

[0112] In the formula: β rt Indicates the first r The first sample t The raw values ​​of each evaluation indicator.

[0113] The corresponding matrix is ​​obtained after normalizing the data. Y = ( y rt ), y rt The original values ​​after standardization. β rt The proportion of the total value. Its calculation is shown in Equation 10:

[0114] (10)

[0115] Calculate the first t The entropy value of any indicator among the indicators e t :

[0116] (11)

[0117] In the formula: k This is called the Boltzmann constant, and is related to the number of evaluation indicators. t Relevant, take the constant value.

[0118] The importance of the sludge deposition index is determined by the coefficient of difference. g This reflects that the larger the difference coefficient, the greater the weight of the indicator. Therefore, the first value is calculated according to equation (12). t Coefficient of difference of the items g t Then, use equation (13) to calculate the corresponding weight, i.e., the entropy weight. w t :

[0119] (12)

[0120] (13)

[0121] It should be noted that determining the weights of each sinking evaluation index is a key aspect of the extension cloud model evaluation and crucial for accurate assessment. Different weighting methods result in different weights and thus different evaluation results. This invention employs the entropy method for objective evaluation of sinking levels, avoiding errors caused by subjective factors in other weighting methods, thus making the evaluation results more objective and accurate.

[0122] Based on the index weight vector W determined by the entropy method and the extension cloud matrix S, the comprehensive degree of determination matrix Q can be obtained, which is the entropy-valued extension cloud comprehensive evaluation model. Then, according to the principle of maximum correlation, the comprehensive evaluation result of the sample to be evaluated can be obtained. The formula for calculating Q is:

[0123] (14)

[0124] In other words, the correlation degree of each frozen soil thaw settlement level of the subgrade soil sample is obtained through the preset entropy value extension cloud comprehensive evaluation model; and the frozen soil thaw settlement level of the subgrade soil sample is determined according to the correlation degree of each frozen soil thaw settlement level of the subgrade soil sample using the maximum correlation degree principle.

[0125] S130. Based on the preset temperature field-thermal coupling numerical simulation, the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed is constructed through the preset frozen soil subgrade temperature field-thermal coupling model. That is, the thaw settlement level classification results of the subgrade sample obtained by the entropy value extension cloud comprehensive evaluation model in step S120 are substituted into the pre-constructed frozen soil subgrade temperature field-thermal coupling model, and temperature field models for different thaw settlement levels are established.

[0126] The migration and redistribution of soil moisture are related to the distribution of heat flow and temperature in the soil. Changes in the water content at various points in the soil will alter the main thermophysical parameters of the soil, while changes in temperature will change the physicochemical properties of soil moisture, thus leading to changes in the main soil parameters. The temperature field-thermal coupling model can better analyze different melting and settling levels and effectively analyze the temperature field distribution law of the roadbed. The method for obtaining the temperature field-thermal coupling numerical simulation includes steps S1310-S1340.

[0127] S1310. Establish the temperature field control equation and the moisture field control equation.

[0128] In the specific implementation process, only the soil heat conduction and ice-water phase transition in permafrost regions are considered, and the temperature field control equation is established accordingly:

[0129] (15)

[0130] In the formula: ρ For soil density, kg / m 3 ; C For heat capacity ( J / ( kg ℃ )); T For temperature, ℃ ; t For time, d ; λThermal conductivity, W / ( m ℃ ); L Latent heat of phase transition, taken as 334.5. kJ / kg ; ρ i The density of ice, kg / m 3 .

[0131] Using the Richards equation for water migration, considering the ice-water phase transition during permafrost thawing, and incorporating the ice-water phase transition term, the governing equation for the water field is shown in Equation 16:

[0132] (16)

[0133] In the formula: θ u This refers to the volumetric unfrozen water content. ρ w The density of water, kg / m 3 ; D ( θ u () represents the water diffusivity in the soil. m 2 / s ; k ( θ u () represents the soil permeability. m / s .

[0134] D ( θ u The diffusivity of water is shown in Equation 17:

[0135] (17)

[0136] In the formula: o ( θ u ) represents the specific water capacity, 1 / m .

[0137] I The impedance factor essentially describes the degree to which ice hinders the flow of water, and its expression is shown in Equation 18:

[0138] (18)

[0139] Soil permeability k ( θu The expression is shown in Equation 19:

[0140] (19)

[0141] Specific water capacity o ( θ u The expression is shown in Equation 20:

[0142] (20)

[0143] In the formula: k s Let be the soil permeability coefficient. m / s ; S The relative saturation of the soil; α 0 , m , l Relevant parameters that vary with soil properties.

[0144] S1320. Based on the solid-liquid ratio and relative saturation, the temperature field control equation is coupled with the moisture field control equation to obtain a hot water coupled model of the temperature field of frozen soil subgrade.

[0145] The temperature field governing equation and the moisture field governing equation require the solid-liquid ratio. B i With relative saturation S Only by using this as the coupling between the temperature field and the moisture field can a coupled model of the temperature field and hot water be established.

[0146] solid-liquid ratio B i With relative saturation S The expressions are shown in equations 21 and 22:

[0147] (twenty one)

[0148] (twenty two)

[0149] in: Tf Soil temperature ，℃；B For parameters related to soil type, the values ​​are typically 0.61 for sand, 0.47 for silt, and 0.56 for clay.

[0150] S1330. The temperature field control equation and the moisture field control equation in the coupled temperature field and hot water model of the frozen soil subgrade are converted into partial differential equations with coefficients that can be recognized by COMSOL Multiphysics software.

[0151] First, the temperature field control equation is transformed into a partial differential equation with coefficients that can be recognized by COMSOL Multiphysics software, that is, Equation 15 is transformed into a partial differential equation with coefficients, as shown in Equation 23:

[0152] (twenty three)

[0153] The final expression of the partial differential equation for the temperature field is shown in Equation 24:

[0154] (twenty four)

[0155] Then, the water field control equation is transformed again into a coefficient partial differential equation that can be recognized by COMSOL Multiphysics software, that is, Equation 16 is transformed into the coefficient partial differential equation form, as shown in Equation 25:

[0156] (25)

[0157] The final expression of the partial differential equation for the moisture field is shown in Equation 26:

[0158] (26)

[0159] S1340. Using COMSOL Multiphysics software, perform numerical simulation of temperature field-thermal coupling based on the transformed frozen soil subgrade temperature field-thermal coupling model.

[0160] The governing equations in the temperature field-hot water coupling model are transformed into partial differential equations with coefficients recognizable by COMSOL Multiphysics software, so that COMSOL Multiphysics software can be used for numerical simulation of the temperature field-hot water coupling.

[0161] The method for constructing the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed by using a pre-set frozen soil subgrade temperature field hot water coupling model includes: S131, constructing a subgrade model for the frozen soil subgrade to be constructed; S132, constructing the temperature field of the thaw settlement level of the subgrade to be constructed by using the pre-set frozen soil subgrade temperature field hot water coupling model based on the subgrade model, the upper boundary conditions of the subgrade temperature field simulation, and the physical parameters of the subgrade to be constructed.

[0162] S140. Heat pipe installation is carried out according to the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

[0163] A heat pipe is a high-efficiency heat conduction device made of seamless carbon steel pipe, buried 5 meters underground with 2 meters exposed above ground. It has special unidirectional heat transfer properties; heat can only be transferred from the lower end of the pipe to the upper end, and cannot be transferred in the opposite direction. In winter, the working medium inside the heat pipe changes from a liquid to a gaseous state, carrying away the heat inside the pipe. In the warm season, the heat pipe stops working. The structure of the heat pipe is roughly a sealed hollow long rod containing some liquid ammonia. Liquid ammonia has a low boiling point, and in winter, the heat in the soil causes the liquid to evaporate. It rises to the top, conducts heat to the air through heat sinks, and after cooling, it liquefies back down, keeping the permafrost frozen and preventing it from loosening.

[0164] The method for constructing heat pipe installation based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed includes: constructing heat pipes based on the annual ground temperature variation over time at a predetermined distance downwards from the middle of the subgrade in the vertical direction, a temperature field contour map, and temperature field curves at different locations of the subgrade. Specifically, based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed, the thaw settlement level of the frozen soil subgrade to be constructed, and the annual temperature variation at the frozen soil subgrade to be constructed, an annual ground temperature variation over time at a predetermined distance downwards from the middle of the subgrade in the vertical direction is drawn; based on the annual ground temperature variation over time, a temperature field contour map corresponding to the thaw settlement level of the frozen soil subgrade to be constructed is drawn.

[0165] The embodiments of the heat pipe layout method based on the thawing and settling classification and temperature field distribution law of the present invention will be described in detail below.

[0166] Example 1

[0167] Specifically, taking the Kugen Class I Highway project as an example, the effect of applying the entropy-based extension cloud model of this invention on the evaluation level of subsidence in this project is compared with the subsidence results obtained by existing standards and the k-means method. In addition, the temperature field of different subsidence levels of the subgrade is simulated by the roadbed hot water coupling model to design the heat pipe layout parameters.

[0168] The Kugen Class I Highway Project is located near the Greater Khingan Mountains. The region's average annual temperature ranges from -5 to -7 °C, increasing from west to east. July has the highest temperature, averaging 17.9 °C to 19.8 °C, while January has the lowest, averaging -30.9 to -27.3 °C. The terrain is characterized by ancient quasi-planar terrain and rounded mountains, generally relatively flat, with a well-developed river network, wide valleys, and gentle slopes (less than 15°) accounting for over 80% of the slopes. The relative elevation difference is 100–300 meters, resulting in relatively gentle terrain undulations. The study area in this example traverses the Greater Khingan Mountains, generally higher in the middle and lower on the east and west sides. The highest point is approximately 1300 meters above sea level, and the lowest point is approximately 470 meters above sea level. The physical parameters of the soil are shown in Table 1.

[0169] Table 1 Soil physical parameters

[0170]

[0171] According to existing standards, the thaw settlement level of samples is determined based on the thaw settlement coefficient and superplastic moisture content. The thaw settlement level of frozen soil is divided into five grades: Grade I (no thaw settlement), Grade II (weak thaw settlement), Grade III (thaw settlement), Grade IV (strong thaw settlement), and Grade V (thaw collapse). The results are as follows: Figure 2 As shown. By observation Figure 2 It was found that the melt-settling coefficients of many samples did not meet the discrimination criteria. While the melt-settling coefficients of many samples met the standard discrimination criteria, their superplastic moisture content was outside the standard grading limits, posing a significant potential risk to the discrimination results.

[0172] Therefore, four indicators—moisture content, void ratio, ice content, and superplastic moisture content—were selected as evaluation indicators for the thaw settlement level of frozen soil. The classification standards for each thaw settlement evaluation indicator and the limit values ​​of each thaw settlement evaluation indicator corresponding to each frozen soil thaw settlement level are shown in Table 2. The distribution maps of moisture content, void ratio, and ice content levels are shown in Figure 3. Figure 3(a) shows the moisture content map; Figure 3(b) shows the void ratio and volumetric ice content map.

[0173] Table 2 Classification Criteria for Evaluation Indicators

[0174]

[0175] The entropy values ​​of each melting and sedimentation evaluation index are calculated based on Formula 11 above. e j Calculate the corresponding difference coefficients according to formulas 12 and 13 respectively. g j With entropy weight w j The calculation results are shown in Table 3.

[0176] Table 3 Weighting of Entropy Values ​​for Evaluation Indicators

[0177]

[0178] Based on the evaluation index thresholds shown in Table 3, the expected value is calculated according to formulas 2 and 3. E x ,entropy E n and hyperentropy H e hyperentropy H e We set the value to 0.0001 and constructed a complex element matrix model. U As shown in Formula 1.

[0179] Based on the evaluation threshold values ​​obtained in Table 2, a complex cloud matrix model is established according to Formula 1. UAnd calculate the expected value according to Equations 3-5. E x Entropy E n and hyperentropy H e hyperentropy H e Set the value to 0.0001. Construct the complex cloud matrix model. U As shown in Formula 30:

[0180] (30)

[0181] Cloud droplet diagrams for each evaluation index's melt-settling level were plotted using the Matlab forward cloud generator. The cloud droplets for each evaluation index exhibited a normal distribution, but the boundary information for each evaluation index level showed a certain degree of fuzziness and randomness. Figure 4 shows the cloud droplet diagrams: Figure 4(a) for water content; Figure 4(b) for porosity ratio; Figure 4(c) for ice content; and Figure 4(d) for superplastic water content.

[0182] Based on formulas 6-7, an extension cloud matrix is ​​constructed. Taking melting and strong melting as examples, the results of the extension cloud matrix for evaluation indicators are summarized in Table 4. Based on formulas 9-14, a comprehensive extension cloud evaluation matrix is ​​constructed, as shown in Table 5.

[0183] Table 4. Evaluation Indicators and Extension Cloud Matrix

[0184]

[0185] Table 5 Comprehensive Evaluation Matrix of Extendable Cloud

[0186]

[0187] The correlation degree of each sample to be evaluated is accumulated, and the melting and settling level of the sample to be evaluated is calculated according to the principle of maximum correlation degree. The evaluation results are shown in Table 6.

[0188] Table 6 Evaluation Results of Subsidence and Strong Subsidence Extendable Clouds

[0189]

[0190] As shown in Table 6, when evaluating the level of permafrost thaw settlement, since the nature of permafrost thaw settlement is the result of multiple factors acting occasionally, improper or inaccurate classification will inevitably affect the safe operation of road traffic and increase related maintenance costs. Using the heat pipe layout method based on permafrost thaw settlement classification and temperature field distribution law of this invention, cluster analysis cannot solve the ambiguity and randomness between indicators, and the boundaries between levels are unclear. The extension cloud model can precisely solve this defect and distinguish between the two levels of thaw settlement and strong thaw settlement, which have a greater impact on pipeline safe service.

[0191] Based on the entropy-based extension cloud classification of permafrost thaw settlement levels, a coupled hydrothermal model of the subgrade temperature field was constructed. The subgrade model was built according to the actual conditions of the Kugen Highway. Subgrade section a has a height of 2.0 m, a surface width of 12.0 m, and a slope of 1:1.5. The width of region b in the model is 30 m, and the influence depth of the model is 10 m. The calculation profile was simplified as follows: the surface layer (0-2 m) of region a consists of subgrade fill material, and the soil layer below the surface in region b is silty clay. The cross-section of the model is shown in Figure 5(a). A mapped mesh was used, mapping from the subgrade surface to the entire shape. To increase calculation accuracy, a finer element size was selected for the mesh, as shown in Figure 5(b).

[0192] The top thermal boundary condition of the model is obtained based on the climate conditions of Genhe City, which is close to the test road, combined with the "boundary layer theory". The "boundary layer theory" can solve the boundary simplification problem; the "boundary layer" is also called the boundary layer. The boundary layer theory uses the temperature conditions at a certain depth as the upper boundary condition for simulating the roadbed temperature field. This boundary condition is called the boundary layer thermal boundary condition and can be expressed by Equation 27:

[0193] (27)

[0194] In the formula: T 0 The local initial annual average temperature is taken as -2.6℃; G(t) The annual average temperature increases with each year, and the rate of temperature increase is taken as 0.03℃ / a ; ζ d The annual amplitude of the daily average temperature is taken as 24.3℃ for this region; t This refers to the duration of the time. Φ The value is based on the temperature on October 1, 2020, the start date of the simulation. t =0 time T 0 = -2.6℃, Φ = π .

[0195] Considering the different temperatures of different surfaces, we take an increase of 5℃ for the roadbed temperature, 2.5℃ for the slope temperature, and 2℃ for the original ground temperature. The air temperature curve is shown below. Figure 6 As shown, that is Figure 6 A graph showing the comparison between measured and simulated monthly average temperatures is presented.

[0196] Based on the entropy-based extension cloud model, the thawing settlement level classification of frozen soil is determined, and combined with the physical parameters of the roadbed to be constructed, a roadbed temperature field thawing settlement and strong thawing settlement temperature field model is constructed.

[0197] The physical parameters of the roadbed to be constructed are shown in Table 7.

[0198] Table 7. Subgrade Physical Parameters

[0199]

[0200] Based on the subgrade physical parameters in Table 7, thaw settlement and strong thaw settlement models of the subgrade temperature field were constructed. Due to the heat absorption effect of the subgrade materials and frozen soil, their influence on soil temperature has a lag, and the maximum freeze-thaw depth usually occurs in October. The subgrade temperature fields for the two thaw settlement levels are shown in Figure 7 (a-d) for thaw settlement level and Figure 7 (e-h) for strong thaw settlement level. Specifically, Figure 7 (a-d) shows the temperature field for thaw settlement level in January, May, October, and December, and Figure 7 (e-h) shows the temperature field for strong thaw settlement level in January, May, October, and December.

[0201] As shown in Figure 7, from January to May, the upper part of the foundation darkened in color and continued to expand, indicating that during this period, cold air continuously penetrated downwards, causing the internal temperature of the foundation of the roadbed under construction to gradually decrease. In May, the ground began to thaw, and the temperature inside the roadbed reached sub-zero levels. From May to October, the thawing depth at the top of the foundation pit of the roadbed under construction gradually increased, reaching its maximum depth in October, at which point the original upper limit of the frozen soil was reached. In November, the ground soil returned to a frozen state, and cold air continued to penetrate downwards. From November to December, as the thickness of the frozen soil increased, the frozen soil area gradually decreased, until January of the following year, when the frozen soil in the area was completely frozen again.

[0202] Figure 7 shows the variations in the natural ground temperature field above and on both sides of the roadbed, based on seasonal temperatures. Both types of roadbeds reach their maximum frost depth in May and maximum thaw depth in October. However, at the maximum frost depth in May, the thawed soil does not completely freeze, but forms a thaw interlayer. Above this interlayer is the seasonally active layer of the roadbed, and below is the perennial permafrost. At this time, the frost depth in the strong thaw settlement section is greater than that in the thaw settlement section.

[0203] When the maximum thawing depth is reached in October, the strong thawing settlement zone of permafrost below the thawing interlayer is closer to the ground than the thawing settlement zone, and the upper limit of the strong thawing settlement zone is higher than that of the thawing settlement zone. Furthermore, there is a significant difference between the upper limit of the permafrost below the middle of the roadbed and the natural surfaces on both sides. This indicates that the roadbed construction generated significant heat disturbance to the natural foundation, causing the soil near the upper limit of the permafrost to thaw, thus forming a thawing zone. In addition, since the natural ground on both sides lacks the roadbed and can exchange heat with the outside air, a greater accumulation of cold air occurs on the ground over the following year, resulting in an uneven distribution of the natural temperature field beneath the roadbed.

[0204] Figure 8 shows the annual temperature variation patterns of thawed and strongly thawed roadbeds provided in this embodiment of the invention. Figure 8(a) shows the annual temperature variation pattern of the thawed roadbed, and Figure 8(b) shows the overall temperature variation pattern of the strongly thawed roadbed. Figure 8 illustrates the temperature variation patterns of the two different types of roadbeds at different times of different months. The temperature field distribution of the two types of roadbeds shows that the depth variation of the strongly thawed roadbed is greater than that of the thawed roadbed. Comparatively, the strongly thawed road section has poorer stability and is more prone to road damage.

[0205] To more accurately design the heat pipe layout parameters, the distribution law of the temperature field of the subsidence and strong subsidence roadbed, and the annual temperature variation of the roadbed were considered. Using the subsidence and strong subsidence levels as references, the ground temperature variation over time was plotted at five locations along the vertical direction from the middle of the roadbed downwards: -1m, -2.5m, -3m, -8m, and -12m. Figure 9 shows the ground temperature variation over time for subsidence and strong subsidence roadbeds provided in the application example of this invention. Figure 9(a) shows the ground temperature variation over time for subsidence roadbeds, and Figure 9(b) shows the ground temperature variation over time for strong subsidence roadbeds.

[0206] As shown in Figure 9, within a year, the phase of the sine curve corresponding to ground temperature shifts to the right and the amplitude gradually decreases with increasing depth. This indicates that the temperature needs time to transfer downwards along the roadbed, and the increasing thermal resistance with depth leads to a decrease in the amplitude of temperature change. Due to the presence of thermal resistance, the temperature change of the seasonally active layer always exhibits a lag effect along depth during the transfer of heat from the pavement along the roadbed. This lag effect causes the upper ice layer of the soil to melt, preventing water from draining and increasing the risk of melt-settlement damage to the roadbed.

[0207] The placement of heat pipes differs between thaw settlement and strong thaw settlement subgrades. It can be observed that the temperature fluctuations in the strong thaw settlement subgrade temperature field are excessive, indicating significant changes in the frozen soil state. This greatly increases the instability of the soil's internal structure, leading to thaw settlement failure. Observing Figure 9(a), which shows the temperature variation over time in the thaw settlement subgrade temperature field, reveals that the upper limit of the frozen soil is approximately 2.7-3 meters below the road surface. The frozen area of ​​the thaw settlement subgrade is relatively larger than that of the strong thaw settlement subgrade. The upper limit of the frozen soil is closer to the road surface, increasing the subgrade's stability. Therefore, it can be concluded that strong thaw settlement subgrades are more prone to thaw settlement failure than thaw settlement subgrades. When adding heat pipes, it is necessary to consider a denser design in the strong thaw settlement subgrade section to prevent thaw settlement failure.

[0208] The placement and burial depth of heat pipes play a role in preventing thaw settlement of frozen soil subgrades. To investigate the burial depth of the heat pipes, the month with the largest thaw settlement depth was selected, and the placement parameters of the heat pipes were analyzed. Contour lines of the temperature field for thaw settlement and severe thaw settlement subgrades were plotted, as shown in Figure 10. Figure 10 is a contour map of the temperature field for thaw settlement and severe thaw settlement subgrades provided in this embodiment of the invention. Figure 10(a) shows the contour map of the temperature field for thaw settlement subgrades, and Figure 10(b) shows the contour map of the temperature field for severe thaw settlement subgrades. As shown in Figure 10(a), the temperature field of the thaw settlement subgrade reaches its maximum thawing depth at around 3m, and the subgrade remains in a sub-zero temperature state below 3m. Due to the thawing of frozen soil, water cannot drain quickly from the soil layer, leading to thaw settlement damage in the road. For thaw settlement subgrades, the burial depth of the heat pipes should be around 3m to increase the upper limit of frozen soil in winter, slow down the thawing depth, and achieve the purpose of protecting the subgrade from settlement. As shown in Figure 10(b), the temperature field of the roadbed with strong thaw settlement indicates that due to the relatively high water content of the roadbed, the permafrost core inside the roadbed has not completely thawed, forming a high-altitude ice layer inside the roadbed. With repeated freeze-thaw cycles and rising temperatures, the roadbed experiences significant thaw settlement due to excessive water content and soil structure damage, potentially even compromising the safe operation of the road. Therefore, heat pipes should be designed with a burial depth of approximately 5 meters below the permafrost core to reduce the temperature of the permafrost layer inside the soil and protect the safe operation of the road.

[0209] The insertion method of the heat pipe will vary depending on the degree of subgrade thaw settlement. Figure 11 shows the temperature field curves of the subgrade, pavement, and subgrade locations for thaw settlement and strong thaw settlement subgrades provided in this embodiment of the invention. Figure 11(a) shows the temperature field curves of the subgrade, pavement, and subgrade locations for thaw settlement subgrades, and Figure 11(b) shows the temperature field curves of the subgrade, pavement, and subgrade locations for strong thaw settlement subgrades. Observing Figure 11(b), it can be seen that in the strong thaw settlement subgrade temperature field curve, there is a large fluctuation between the temperature curves below the pavement and below the middle of the subgrade, indicating that the thaw is deeper below the subgrade, while the original ground thaw depth is relatively smaller. Observing Figure 11(a), it can be seen that in the thaw settlement subgrade temperature field, due to the lower moisture content, the temperature below the subgrade is basically at the same level as the temperature field below the pavement, and the temperature is lower, indicating a frozen state. To protect road operation safety and improve the efficiency of heat pipes, when designing strong thawing subgrades, heat pipes should be kept at a certain angle and inserted below the subgrade to better exert their effect, increase the upper limit of frozen soil, and ensure safe road operation.

[0210] The heat pipe placement method of this invention, based on the classification of frozen soil thaw settlement and the distribution law of temperature field, allows for reasonable placement of heat pipes during construction, ensuring construction safety, by considering the results of thaw settlement classification and temperature field analysis. In road construction in frozen soil areas, the complexity of factors affecting thaw settlement and the significant damage caused by freeze-thaw cycles easily lead to structural settlement of the frozen soil. By using an entropy-based extension cloud model, the thaw settlement level can be more accurately determined, allowing for better simulation of the temperature field distribution law of each thaw settlement level in the roadbed, and designing heat pipe placement parameters more suitable for different thaw settlement levels.

[0211] Corresponding to the above-mentioned heat pipe layout method based on the classification of frozen soil thaw settlement and the distribution law of temperature field, the present invention also provides a heat pipe layout system based on the classification of frozen soil thaw settlement and the distribution law of temperature field. Figure 3 shows the functional modules of the heat pipe layout system based on the classification of frozen soil thaw settlement and the distribution law of temperature field according to an embodiment of the present invention.

[0212] like Figure 12 As shown, the heat pipe deployment system 200 based on the grading of frozen soil thaw settlement and the distribution law of temperature field provided by the present invention can be installed in an electronic device. Depending on the functions implemented, the heat pipe deployment system 200 based on the grading of frozen soil thaw settlement and the distribution law of temperature field can include a data acquisition unit 210, a thaw settlement level determination unit 220, a temperature field construction unit 230, and a construction unit 240. The unit described in this invention can also be called a module, referring to a series of computer program segments that can be executed by the processor of an electronic device and can perform a specific function, stored in the memory of the electronic device.

[0213] In this embodiment, the functions of each module / unit are as follows:

[0214] The data acquisition unit 210 is used to acquire the thaw settlement data of the subgrade soil sample of the frozen soil subgrade to be constructed, the preset frozen soil thaw settlement level, and the limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; wherein, the thaw settlement evaluation index includes water content, void ratio, ice content and superplastic water content; the frozen soil thaw settlement level includes five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement and thaw collapse.

[0215] The thaw settlement level determination unit 220 is used to obtain the correlation degree of each thaw settlement level of the subgrade soil sample based on the thaw settlement data of the subgrade soil sample to be constructed, the preset thaw settlement level of the frozen soil, and the limit values ​​of each thaw settlement evaluation index corresponding to each thaw settlement level, through a preset entropy value extension cloud comprehensive evaluation model; and to determine the thaw settlement level of the subgrade soil sample based on the correlation degree of each thaw settlement level of the subgrade soil sample using the maximum correlation degree principle.

[0216] Temperature field construction unit 230 is used for numerical simulation based on preset temperature field hot water coupling, and to construct the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed through preset frozen soil subgrade temperature field hot water coupling model.

[0217] Construction unit 240 is used to install heat pipes according to the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

[0218] The more specific implementations of the heat pipe layout system based on the grading of frozen soil thawing and the distribution law of temperature field provided by the present invention can all refer to the above-described embodiments of the heat pipe layout method based on the grading of frozen soil thawing and the distribution law of temperature field, and will not be listed one by one here.

[0219] This invention establishes a heat pipe deployment system based on the grading of permafrost thaw settlement and the distribution of temperature fields. First, it objectively analyzes the index weights using the entropy method and combines this with a Extension cloud model to determine the thaw settlement level. Then, it uses coupled hydrothermal numerical simulation to analyze the temperature field distribution at each level, and finally analyzes the heat pipe deployment parameters based on the simulated temperature field results. This invention can more comprehensively classify thaw settlement levels, simulate the temperature field of different roadbed levels, accurately deploy heat pipes, reduce heat pipe costs, and improve the effectiveness of heat pipes. It is more suitable for areas with complex thaw settlement level distributions and has practical engineering value and reference significance for reducing road thaw settlement damage, improving heat pipe utilization efficiency, and preventing roadbed diseases in extremely cold permafrost regions.

[0220] like Figure 13 As shown, the present invention provides an electronic device 3 based on the method of heat pipe layout according to the grading of frozen soil thawing and the distribution law of temperature field.

[0221] The electronic device 3 may include a processor 30, a memory 31 and a bus, and may also include a computer program stored in the memory 31 and capable of running on the processor 30, such as a heat pipe layout program 32 based on the grading of frozen soil thawing and the distribution law of temperature field.

[0222] The memory 31 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 31 can be an internal storage unit of the electronic device 3, such as a portable hard drive. In other embodiments, the memory 31 can be an external storage device of the electronic device 3, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 3. Furthermore, the memory 31 can include both internal and external storage units of the electronic device 3. The memory 31 can be used not only to store application software and various types of data installed on the electronic device 3, such as code for a heat pipe deployment program based on the grading of permafrost thawing and temperature field distribution, but also to temporarily store data that has been output or will be output.

[0223] In some embodiments, the processor 30 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 30 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 31 (e.g., a heat pipe layout program based on permafrost thawing and temperature field distribution laws), and calls data stored in the memory 31 to perform various functions and process data in the electronic device 3.

[0224] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 31 and at least one processor 30, etc.

[0225] Figure 3 only shows an electronic device with components. Those skilled in the art will understand that the structure shown in Figure 5 does not constitute a limitation on the electronic device 5, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0226] For example, although not shown, the electronic device 5 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 50 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 3 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0227] Furthermore, the electronic device 3 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 3 and other electronic devices.

[0228] Optionally, the electronic device 3 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 3 and to display a visual user interface.

[0229] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0230] The heat pipe placement program 32, stored in the memory 31 of the electronic device 3 and based on the grading of frozen soil thaw settlement and the temperature field distribution law, is a combination of multiple instructions. When run in the processor 30, it can: acquire thaw settlement data of the subgrade soil sample of the frozen soil subgrade to be constructed, preset frozen soil thaw settlement levels, and the limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; wherein, the thaw settlement evaluation index includes water content, void ratio, ice content, and superplastic water content; the frozen soil thaw settlement level includes five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement, and thaw collapse; based on the thaw settlement data of the subgrade soil sample of the frozen soil subgrade to be constructed... The system employs a pre-defined frozen soil thaw settlement level and the boundary values ​​of each thaw settlement evaluation index corresponding to each level. It then uses a pre-defined entropy-based extension cloud comprehensive evaluation model to obtain the correlation degree of each frozen soil thaw settlement level of the subgrade soil sample. Utilizing the principle of maximum correlation, the system determines the frozen soil thaw settlement level of the subgrade soil sample based on the correlation degree of each level. Based on a pre-defined temperature field hot water coupling numerical simulation, the system constructs the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed using a pre-defined frozen soil subgrade temperature field hot water coupling model. Finally, it performs heat pipe installation based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

[0231] Specifically, the processor 30's implementation method for the above instructions can be found in [reference needed]. Figure 1 The descriptions of the relevant steps in the corresponding embodiments are not repeated here. It should be emphasized that, in order to further ensure the privacy and security of the above-mentioned heat pipe deployment procedure based on the grading of permafrost thawing and the distribution law of temperature field, the above-mentioned heat pipe deployment procedure based on the grading of permafrost thawing and the distribution law of temperature field is stored in the node of the blockchain of this server cluster.

[0232] Furthermore, if the modules / units integrated in the electronic device 3 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0233] This invention also provides a computer-readable storage medium, which can be non-volatile or volatile. The storage medium stores a computer program, which, when executed by a processor, performs the following: acquiring thaw settlement data of subgrade soil samples from the frozen soil subgrade to be constructed, preset frozen soil thaw settlement levels, and limit values ​​of various thaw settlement evaluation indicators corresponding to each thaw settlement level; wherein the thaw settlement evaluation indicators include moisture content, void ratio, ice content, and superplastic moisture content; the frozen soil thaw settlement levels include five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement, and thaw collapse; based on the thaw settlement data of the subgrade soil samples from the frozen soil subgrade to be constructed... The data, preset frozen soil thaw settlement levels, and the boundary values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level are used to obtain the correlation degree of each frozen soil thaw settlement level of the subgrade soil sample through a preset entropy value extension cloud comprehensive evaluation model. Using the maximum correlation degree principle, the frozen soil thaw settlement level of the subgrade soil sample is determined according to the correlation degree of each frozen soil thaw settlement level. Based on the preset temperature field hot water coupling numerical simulation, the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed is constructed through the preset frozen soil subgrade temperature field hot water coupling model. Heat pipes are installed according to the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

[0234] Specifically, the specific implementation method of the computer program when executed by the processor can be referred to the description of the relevant steps in the embodiment of the heat pipe layout method based on the thawing and settlement classification and temperature field distribution law of frozen soil, which will not be repeated here.

[0235] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0236] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0237] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0238] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0239] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0240] The blockchain referred to in this invention is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying platform, a platform product service layer, and an application service layer. Blockchain can store medical data, such as personal health records, kitchen records, and examination reports.

[0241] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. The term "second class" is used to indicate names and does not indicate any specific order.

[0242] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for heat pipe layout based on frozen soil thaw settlement classification and temperature field distribution law, characterized in that the method... include: Acquire thaw settlement data of subgrade soil samples from the frozen soil subgrade to be constructed, preset frozen soil thaw settlement levels, and limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; wherein, the thaw settlement evaluation index includes water content, void ratio, ice content, and superplastic water content; the frozen soil thaw settlement level includes five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement, and thaw collapse. Based on the thaw settlement data of the subgrade soil samples of the frozen soil subgrade to be constructed, the preset thaw settlement level, and the limit values ​​of each thaw settlement evaluation index corresponding to each thaw settlement level, the correlation degree of each thaw settlement level of the subgrade soil samples is obtained through the preset entropy value extension cloud comprehensive evaluation model; using the maximum correlation degree principle, the thaw settlement level of the subgrade soil samples is determined according to the correlation degree of each thaw settlement level of the subgrade soil samples. Based on a pre-set temperature field-thermal coupling numerical simulation, the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed is constructed through a pre-set frozen soil subgrade temperature field-thermal coupling model. The method for constructing the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed through the pre-set frozen soil subgrade temperature field-thermal coupling model includes: constructing a subgrade model for the frozen soil subgrade to be constructed; and constructing the temperature field of the thaw settlement level of the subgrade to be constructed through the pre-set frozen soil subgrade temperature field-thermal coupling model based on the subgrade model, the upper boundary conditions of the subgrade temperature field simulation, and the physical parameters of the subgrade to be constructed. Heat pipe installation is carried out based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

2. The heat pipe layout method based on the thawing settlement classification and temperature field distribution law of frozen soil according to claim 1, characterized in that, The method for obtaining the entropy-based extended cloud comprehensive evaluation model includes: Based on the preset permafrost thaw settlement levels and the limit values ​​of each thaw settlement evaluation index corresponding to each permafrost thaw settlement level, cloud digital feature values ​​are obtained. The correlation degree of each thaw settlement evaluation index in the thaw settlement data of the subgrade soil sample is obtained based on the cloud digital feature values, and an extension cloud matrix is ​​constructed based on the correlation degree. S The weight vector of the melting and sedimentation evaluation index is obtained using the entropy method. W According to the weight vector of the melting and settling evaluation index W and the aforementioned extension cloud matrix S The comprehensive extension cloud evaluation matrix is ​​obtained through the following formula. Q ; in, w t Indicates the first t The weight of each evaluation indicator for financial settlement. μ nm This indicates the correlation between various thaw settlement evaluation indicators in the thaw settlement data of subgrade soil samples. m express m Each level of subsidization n express n Individual evaluation indicators for financial settlement.

3. The heat pipe layout method based on the thawing settlement classification and temperature field distribution law of frozen soil according to claim 2, characterized in that, Methods for obtaining the weights of melt-settlement evaluation indicators using the entropy method include: according to r One sample to be evaluated and t Each set of evaluation indicators was used to obtain the original initial data matrix. X and the r The first sample t The original values ​​of the evaluation indicators for the project's financial settlement; For the original initial data matrix X Perform normalization to obtain a standardized matrix. Y =( y rt ), and according to the first r The first sample t The original values ​​of the evaluation index are obtained by standardizing the original values ​​to obtain the ratio of the original values ​​to the total values, and then the first value is obtained. t The entropy value of any index in the melting and sedimentation evaluation index e t and according to the first t The entropy value of any index in the melting and sedimentation evaluation index e t Get the t The coefficient of difference among various evaluation indicators of financial settlement; According to the t The difference coefficient of the first sedimentation evaluation index is obtained by the following formula. t Weights of each sinking evaluation index w t : in, g t For the first t The coefficient of difference of the evaluation indicators of the project's sinking.

4. The heat pipe layout method based on the thawing settlement classification and temperature field distribution law of frozen soil according to claim 1, characterized in that, The method for obtaining the temperature field hot water coupled numerical simulation includes: Establish the governing equations for the temperature field and the moisture field; Based on the solid-liquid ratio and relative saturation, the temperature field control equation is coupled with the moisture field control equation to obtain a hot water coupled model of the temperature field of frozen soil subgrade. The temperature field control equations and moisture field control equations in the thermo-thermal coupling model of the frozen soil subgrade temperature field are transformed into partial differential equations with coefficients that can be recognized by COMSOL Multiphysics software. Using COMSOL Multiphysics software, a numerical simulation of the temperature field coupled with hot water was performed based on the transformed temperature field hot water coupling model of the frozen soil subgrade.

5. The heat pipe layout method based on the thawing settlement classification and temperature field distribution law of frozen soil according to claim 1, characterized in that, The method for constructing heat pipe installation based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed includes, Based on the annual ground temperature variation over time at a set distance downwards from the middle of the roadbed in the vertical direction, the temperature field contour map, and the temperature field curve at different locations of the roadbed, the heat pipe installation is carried out. Among them, based on the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed, the thaw settlement level of the frozen soil subgrade to be constructed, and the annual temperature change at the frozen soil subgrade to be constructed, a graph showing the annual ground temperature change over time at a set distance downward from the middle of the subgrade in the vertical direction is drawn. Based on the annual ground temperature variation diagram, draw a temperature field contour map corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

6. The heat pipe layout method based on frozen soil thaw settlement classification and temperature field distribution law according to claim 4, characterized in that, The upper boundary condition for the roadbed temperature field simulation is achieved based on the boundary layer theory using the following formula: in, T 0 This represents the local initial annual average temperature; G(t) The annual average temperature increases with each year, in °C. a ; ζ d The annual amplitude of the daily average temperature, in °C; t For the length of time, Φ = π .

7. A heat pipe deployment system based on the grading of frozen soil thaw settlement and the distribution law of temperature field, characterized in that, The system includes, The data acquisition unit is used to acquire thaw settlement data of subgrade soil samples of the frozen soil subgrade to be constructed, preset frozen soil thaw settlement levels, and limit values ​​of each thaw settlement evaluation index corresponding to each frozen soil thaw settlement level; wherein, the thaw settlement evaluation index includes water content, void ratio, ice content, and superplastic water content; the frozen soil thaw settlement level includes five levels: no thaw settlement, weak thaw settlement, thaw settlement, strong thaw settlement, and thaw collapse. The thaw settlement level determination unit is used to obtain the correlation degree of each thaw settlement level of the subgrade soil sample based on the thaw settlement data of the subgrade soil sample to be constructed, the preset thaw settlement level, and the limit values ​​of each thaw settlement evaluation index corresponding to each thaw settlement level, through the preset entropy value extension cloud comprehensive evaluation model; and to determine the thaw settlement level of the subgrade soil sample based on the correlation degree of each thaw settlement level of the subgrade soil sample using the maximum correlation degree principle. The temperature field construction unit is used to construct the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed based on the preset temperature field hot water coupling numerical simulation. The method of constructing the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed based on the preset frozen soil subgrade temperature field hot water coupling model includes: constructing a subgrade model for the frozen soil subgrade to be constructed; and constructing the temperature field of the thaw settlement level of the subgrade to be constructed based on the subgrade model, the upper boundary conditions of the subgrade temperature field simulation, and the physical parameters of the subgrade to be constructed based on the preset frozen soil subgrade temperature field hot water coupling model. The construction unit is used to install heat pipes according to the temperature field corresponding to the thaw settlement level of the frozen soil subgrade to be constructed.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the steps in the heat pipe layout method based on the thawing and settling classification and temperature field distribution law of any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the heat pipe layout method based on the thawing and settlement classification and temperature field distribution law of frozen soil as described in any one of claims 1 to 6.

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