A method, storage medium and device for predicting thawing and consolidation of layered frozen soil

Abstract

The present invention discloses a method for predicting the thawing and consolidation of layered frozen soil, comprising the following steps: step one, obtaining parameters related to layered frozen soil; step two, solving the pore pressure distribution model of thawing and consolidation of layered frozen soil in seasonally frozen areas to obtain a pore pressure distribution relationship in the thawing area; step three, solving the consolidation ratio of thawing and consolidation of layered frozen soil in seasonally frozen areas. The present invention also discloses a storage medium, which stores a computer program for executing the aforementioned method. The present invention also provides a device, which includes a memory and a processor, and the memory stores a computer program for executing the aforementioned method. The present invention can reveal the influence mechanism of initial transient pressure and heat source thawing coefficient on the pore water pressure distribution of thawing and consolidation of layered frozen soil, while improving the consolidation efficiency and exploring the most suitable heat source thawing coefficient for different soil structures.

Description

Technical Field

[0001] The present invention belongs to the technical field of frozen soil thawing and consolidation, and in particular relates to a layered frozen soil thawing and consolidation prediction method, storage medium and equipment. Background Art

[0002] Permafrost refers to the freezing of moisture in soil under low-temperature conditions. Permafrost areas cover approximately 20% of Earth's land area, primarily in high-latitude and high-altitude regions. These regions, due to their unique climatic and geological conditions, have a significant impact on global climate change, ecosystems, and human activities. First, permafrost poses a significant threat to buildings. Research has shown that the frost heave force of permafrost poses a significant threat to buildings. With seasonal temperature fluctuations, the expansion and contraction of permafrost can damage building foundations. This problem is exacerbated by permafrost degradation caused by global warming, particularly in high-latitude and high-altitude regions. Furthermore, permafrost areas on the plateau are highly sensitive to climate change. Research has shown that with rising global temperatures, permafrost on the plateau is undergoing significant degradation, impacting the local ecological environment and posing significant challenges to human society. This also poses new challenges to the safe operation of roads. Therefore, studying the impact of climate change on permafrost stability and developing appropriate response strategies have become pressing issues. The long-term impact of roadbed engineering on permafrost in high-altitude regions presents a complex challenge. Long-term monitoring data indicates that engineering structures, such as railways and highways, significantly affect permafrost temperature fields, lowering the upper permafrost limit and increasing the thickness of the active layer. These changes can impact the stability of engineering structures and increase the risk of roadbed damage. Therefore, to ensure the long-term safety of transportation infrastructure, in-depth research on the impact of engineering practices on permafrost is crucial.

[0003] Existing methods for predicting the consolidation of layered soils do not account for the thawing consolidation of frozen soils. Existing frozen soil consolidation models lack consideration of soil heterogeneity and the effects of soil weight, leading to significant discrepancies between predicted results and actual conditions. Therefore, a new method for predicting the thawing consolidation of layered frozen soils is needed. Summary of the Invention

[0004] The purpose of the present invention is to provide a method, storage medium and equipment for predicting the thawing and consolidation of layered frozen soil, so as to solve the problem that the existing layered soil consolidation prediction method proposed in the background technology has not yet taken into account the thawing and consolidation of frozen soil, and the existing frozen soil consolidation model lacks consideration of the heterogeneity of the soil and the influence of its own weight, which results in huge errors between the prediction results and the actual situation.

[0005] To achieve the above object, the present invention provides a method for predicting thawing and consolidation of layered frozen soil, comprising the following steps:

[0006] Step 1: Obtain relevant parameters of layered frozen soil;

[0007] Step 2: Solve the pore pressure distribution model of thawing and consolidation of layered frozen soil in seasonally frozen areas to obtain the pore pressure distribution relationship in the thawing area; specifically, the steps include:

[0008] The first step is to input the external influencing parameters required by the model;

[0009] The second step is to construct boundary condition equations. Based on the different positions of the thaw line in the soil layer, the thaw line is defined as the first stage when it is at the top layer and the second stage when it is at the bottom layer. The bottom boundary conditions of the first stage and the second stage are obtained by solving the external influencing parameters and layered frozen soil related parameters in the first step. The top boundary condition is defined based on the completely permeable interface in Terzaghi's theorem.

[0010] The third step is to obtain the general solutions of the excess pore water pressure in the first and second stages of the model based on the governing equation of soil consolidation and the Gaussian error function.

[0011] Step 4: Based on the general solution of the first stage obtained in step 3 and combined with the bottom boundary conditions and top boundary conditions of the first stage, the pore pressure distribution of the single layer of soil during thawing and consolidation in the first stage is obtained. The initial conditions of the bottom layer in the second stage are obtained based on the pore pressure at the bottom of the model at the end of the first stage.

[0012] Step 5: Based on the general solution of the pore pressure of the bottom soil in the second stage obtained in the third step, combined with the bottom boundary conditions of the second stage and the initial conditions of the second stage obtained in the fourth step, the pore pressure distribution of the bottom soil in the second stage is obtained; then, based on the Schiffman continuity condition, the top boundary conditions and the general solution of the pore pressure of the top soil in the second stage, the pore pressure distribution of the top soil in the second stage is obtained;

[0013] Step 3: Calculate the consolidation ratio of thawing and consolidation of layered frozen soil in seasonally frozen areas:

[0014] Substitute the excess porosity pore pressure distribution obtained in the first and second stages in step 2 into the consolidation ratio solution formula respectively, and then obtain the consolidation ratio prediction structure of each stage. Compare the prediction results with the actual engineering requirements. If the engineering requirements are not met, return to the first step in step 2 to reset the external conditions until the engineering requirements are met.

[0015] In a specific embodiment, the layered frozen soil related parameters include the thickness, permeability coefficient, volume compression coefficient, and saturated density of different soil layers.

[0016] In a specific embodiment, the layered frozen soil related parameters further include the movement of the thaw line S(t), and the consolidation coefficients of the top soil and the bottom soil.

[0017] In a specific embodiment, the external influencing parameters include a thawing coefficient of a thawing heat source and an initial external transient pressure.

[0018] In a specific embodiment, in step 3, the first stage consolidation ratio obtained is:

[0019]

[0020] The consolidation ratio of the second stage is obtained as:

[0021]

[0022] The present invention also provides a storage medium storing a computer program, wherein the computer program is suitable for being loaded by a processor and executing the above-mentioned layered frozen soil thawing and consolidation prediction method.

[0023] The present invention also provides a device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the layered frozen soil thawing and consolidation prediction method as described above is run.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The present invention comprehensively considers the initial transient pressure, the thickness of different soil layers after stratification, the permeability coefficient, the volume coefficient and the saturated density, and the thawing coefficient of the thawing heat source. It can reveal the influence mechanism of the initial transient pressure and the thawing coefficient of the heat source on the pore water pressure distribution of thawing and consolidation of layered frozen soil, while improving the consolidation efficiency and exploring the most suitable heat source thawing coefficient for different soil structures.

[0026] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention is further described in detail below. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0028] Figure 1 This is a flow chart of a method for predicting thawing and consolidation of layered frozen soil according to the present invention;

[0029] Figure 2 is a schematic diagram of a layered frozen soil thawing model in one embodiment of the present invention;

[0030] Figure 3 1 is a schematic diagram of model rationality verification of the consolidation ratio in one embodiment of the present invention;

[0031] Figure 4 1 is a schematic diagram of the rationality verification of the excess pore water pressure distribution model in one embodiment of the present invention;

[0032] Figure 5 Schematic diagram of the difference in pore pressure prediction distribution between the homogeneous frozen soil model and the heterogeneous frozen soil model in the present invention;

[0033] Figure 6 It is a schematic diagram of the change of consolidation ratio of different models with thawing coefficient in the present invention. DETAILED DESCRIPTION

[0034] The embodiments of the present invention are described in detail below. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] See also Figure 1 The present invention provides a method for predicting the thawing and consolidation of layered frozen soil. The frozen soil is composed of two layers of soil with completely different properties. The top layer of soil is of limited thickness, and the bottom layer of soil is a semi-infinite space. Using the Neumann phase change heat conduction model, Terzaghi consolidation theory, and layered soil consolidation theory, the migration of water during consolidation conforms to Darcy's law. The thawed soil is saturated soil (excluding the influence of air). Based on the Gaussian error function, the consolidation control equation is assumed. The bottom boundary condition is obtained based on the thawing rate of the thawing front and the consolidation coefficient of the soil, thereby obtaining an analytical solution for the pore pressure distribution and establishing a layered frozen soil thawing model. The method specifically includes the following steps:

[0036] Step 1: Obtain relevant parameters of layered frozen soil.

[0037] Parameters related to layered frozen soil include the thickness, permeability, volume compression coefficient, and saturated density of different soil layers.

[0038] Step 2: Solve the pore pressure distribution model of thawing and consolidation of layered frozen soil in seasonally frozen areas to obtain the pore pressure distribution relationship in the thawing area; specifically, the steps include:

[0039] The first step is to input the external influencing parameters required by the model, including the thawing coefficient of the thawing heat source and the initial external transient pressure;

[0040] The second step is to construct the boundary condition equations. Based on the external influencing parameters and relevant soil parameters of the first step, the bottom boundary conditions of the first stage and the bottom boundary conditions of the second stage are obtained. The top boundary conditions are defined based on the completely permeable interface in Terzaghi's theorem.

[0041] The third step is to obtain the general solutions of the excess pore water pressure in the first and second stages of the model based on the governing equation of soil consolidation and the Gaussian error function.

[0042] Step 4: Based on the general solution of the first stage obtained in step 3 and combined with the bottom boundary conditions and top boundary conditions of the first stage, the pore pressure distribution of the single-layer soil thawing consolidation in the first stage is obtained, and the initial conditions of the second stage are obtained according to the pore pressure at the bottom of the model at the end of the first stage.

[0043] Step 5: Based on the general solution of the pore pressure of the bottom soil in the second stage obtained in the third step, combined with the bottom boundary conditions of the second stage and the initial conditions of the second stage obtained in the fourth step, the pore pressure distribution of the bottom soil in the second stage is obtained; then, based on the Schiffman continuity condition, the top boundary conditions and the general solution of the pore pressure of the top soil in the second stage, the pore pressure distribution of the top soil in the second stage is obtained;

[0044] Step 3: Calculate the consolidation ratio of thawing and consolidation of layered frozen soil in seasonally frozen areas:

[0045] Substitute the excess porosity pore pressure distribution obtained in the first and second stages in step 2 into the consolidation ratio solution formula respectively, and then obtain the consolidation ratio prediction structure of each stage. Compare the prediction results with the actual engineering requirements. If the engineering requirements are not met, return to the first step in step 2 to reset the external conditions until the engineering requirements are met.

[0046] Example 1

[0047] A method for predicting thawing and consolidation of layered frozen soil comprises the following steps:

[0048] Step 1: Obtain relevant parameters of layered frozen soil based on soil survey results, including the thickness, permeability, volume compression coefficient, and saturated density of different soil layers.

[0049] Layered frozen soil consists of two layers of soil with completely different properties: the top layer is finite in thickness, while the bottom layer is a semi-infinite volume. Given a heat source, the solution to the heat conduction problem was proposed by Newumann. The motion of the thaw line S(t) is given by:

[0050]

[0051] Where α is the thawing coefficient determined from the solution of the heat conduction problem, S(t) is the distance from the soil surface to the thaw surface, and t is the time.

[0052] Then the consolidation coefficient of each layer can be obtained through the permeability coefficient and volume compression coefficient:

[0053]

[0054] Among them, k v1 、k v2 Represent the permeability coefficient of the top soil and bottom soil respectively, m v1 、m v2Represent the volume compression coefficient of the top soil and bottom soil respectively, C v1 、C v2 denote the consolidation coefficients of the top soil and bottom soil, γ w Indicates the weight of water.

[0055] Step 2: Solve the pore pressure distribution model of thawing and consolidation of layered frozen soil in seasonally frozen areas.

[0056] The first step is to input the external influencing parameters required by the model, including the thawing coefficient of the thawing heat source and the initial external transient pressure.

[0057] The second step is to construct boundary condition equations. Because the thaw line is located in different soil layers, the first stage is defined when it is at the top layer, and the second stage is defined when it is at the bottom layer. The bottom boundary conditions for the first and second stages are obtained based on external influencing parameters and relevant parameters of the layered frozen soil. The top boundary condition is defined based on the completely permeable interface in Terzaghi's theorem.

[0058] Top boundary condition relationship:

[0059] u1(0,t)=0,t>0 Formula (3)

[0060] The specific method for solving the bottom boundary conditions is as follows:

[0061] At the thaw line, the ice in the frozen soil melts, releasing the resulting water; under the combined effects of transient pressure and deadweight, the water flows upward. For saturated soil consolidation, the boundary condition is that any flow out of the thaw line is replaced by a change in soil volume. According to Darcy's law, as the thaw line advances, the volume of pore fluid discharged from the bottom boundary, ΔV, increases with time:

[0062]

[0063] Where u1 and u2 are the excess pore water pressures of the top and bottom soils, respectively, and A R is the cross-sectional area of ​​the soil element. The volume change ΔV is also equal to the volume change of a layer with a thickness of ΔS(t), and the volume strain is:

[0064]

[0065] The volumetric strain of compressible soil is:

[0066]

[0067] Among them, Δσ i '(z,t) is the effective stress difference.

[0068] In equations (4) to (6), i refers to the position of the layer where the thaw line is located. When i = 1, the thaw line is located in the top layer of soil; when i = 2, the thaw line is located in the bottom layer of soil.

[0069] Therefore, the bottom boundary conditions of the two stages are:

[0070] Phase 1:

[0071] Phase 2:

[0072] Where h1 is the thickness of the top soil.

[0073] In the third step, the general solutions of the excess pore water pressure in the first and second stages of the model are obtained based on the control equation of soil consolidation and the Gaussian error function.

[0074] The governing equation for thawing consolidation in the first stage is:

[0075]

[0076] In the second stage:

[0077]

[0078] Where z is the depth and P0 is the transient pressure. Then, based on the consolidation equation and the Gaussian error equation, a two-stage general solution is obtained. In the first stage:

[0079]

[0080] Among them, A, B, and C are relevant hypothesis parameters.

[0081] In the second phase:

[0082]

[0083] Among them, A1, B1, C1, A2, B2, and C2 are relevant assumption parameters.

[0084] The fourth step is to obtain the pore pressure distribution of the single-layer soil thawing consolidation in the first stage based on the general solution of the first stage obtained in the third step and combined with the bottom boundary conditions and top boundary conditions of the first stage, and obtain the initial conditions of the second stage according to the bottom pore pressure at the end point of the first stage of pore pressure.

[0085] The parameters A, B, and C related to the first stage general solution are:

[0086]

[0087] C=0 formula (17)

[0088] in,

[0089] And obtain the bottom initial conditions of the second stage:

[0090]

[0091] The fifth step is to obtain the relationship between the pore pressure of the bottom soil in the second stage based on the general solution of the pore pressure of the bottom soil in the second stage obtained in the third step and combined with the bottom boundary conditions of the second stage and the initial conditions of the second stage obtained in the fourth step; then, the relationship between the pore pressure of the top soil in the second stage is obtained according to the Schiffman continuity condition, the top boundary condition and the general solution of the pore pressure of the bottom soil in the second stage.

[0092] The relevant parameters A2, B2, and C2 of the second-stage bottom soil pore pressure solution are obtained as follows:

[0093]

[0094] in, According to the Schiffman continuity condition:

[0095] u1(h1,t)=u2(h1,t) Formula (24)

[0096]

[0097] The relevant parameters A1, B1, and C1 of the second-stage top soil pore pressure solution are obtained as follows:

[0098]

[0099]

[0100] C1=0 formula (28)

[0101] Step 3: Substitute the excess pore pressure distribution obtained in the first and second stages into the consolidation ratio solution formula respectively, and then obtain the consolidation ratio prediction results of each stage. Compare the prediction results with the actual engineering requirements. If the engineering requirements are not met, return to step 2 to set the external conditions until the engineering requirements are met.

[0102] The consolidation ratio U1 of the first stage and the consolidation ratio U2 of the second stage are calculated by Stieltjes integral:

[0103]

[0104]

[0105] The present invention sets the good consolidation ratio to 0.8, so when U>0.8, the thawing consolidation engineering effect is good; when U≤0.8, the thawing consolidation effect is poor, and the external parameters need to be changed until U>0.8.

[0106] This embodiment further provides a storage medium storing a computer program, wherein the computer program is suitable for being loaded by a processor and executing the above-mentioned layered frozen soil thawing and consolidation prediction method.

[0107] This embodiment further provides a device, which includes a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the above-mentioned layered frozen soil thawing and consolidation prediction method is executed.

[0108] like Figure 2 As shown in the figure, the layered frozen soil model consists of two layers of soil with completely different properties. The top layer has a limited thickness, and the bottom layer is a semi-infinite space. v1 、k v2 Represent the permeability coefficient of the top soil and bottom soil respectively, m v1 、m v2 Represent the volume compression coefficient of the top soil and bottom soil respectively, C v1 、C v2 Represent the consolidation coefficients of the top and bottom soils, γ'1 and γ'2 represent the saturated density of the top and bottom soils, respectively, and h1 is the thickness of the top soil. The model undergoes thawing consolidation under the action of transient pressure P0 and heat source.

[0109] like Figure 3 and Figure 4 As shown, the technical solution of this embodiment is compared with the MN model and Zhou model for pore pressure distribution and consolidation ratio of thawing consolidation. Figure 3 and Figure 4 As is known, the present invention can also be applied to the thawing consolidation model of homogeneous frozen soil.

[0110] like Figure 5 As shown, the heterogeneous model in the technical solution of this embodiment is compared with the homogeneous model. The consolidation coefficients of each layer of the soil model are shown in Table 1, and the other parameters are P0 = 10kN, h1 = 0.5m, α = 3×10 -4 m / s 0.5 .

[0111] Table 1

[0112] Model Model A Model B Model C Model D <![CDATA[Coefficient of consolidation at the top layer, C v1 (×10 -8 m 2 / s)]]> 3 5 3 5 <![CDATA[Coefficient of consolidation of the underlying layer, C v2 (×10 -8 m 2 / s)]]> 3 5 5 3

[0113] Depend on Figure 5 As is known, ignoring the heterogeneity of layered frozen soil will affect the prediction of pore pressure distribution. This also reflects the advancement of the present invention.

[0114] like Figure 6 As shown (P0 = 10kN, h1 = 0.5m, C v2 =4×10 -8 m / s 2 In most cases, the consolidation ratio decreases as the thawing coefficient increases. This is primarily because a larger thawing coefficient means more ice thaws into water, and the soil's inherent drainage capacity is limited. Step three of the present invention adjusts the heat source to achieve the consolidation ratio required for the project. Therefore, if the consolidation ratio does not meet project requirements, the thawing coefficient can be reduced to bring it up to standard.

[0115] The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, several simple deductions and substitutions can be made without departing from the concept of the present invention, and all of these should be considered to fall within the scope of protection of the present invention.

Claims

1. A method for predicting thawing and consolidation of layered frozen soil, characterized in that: The steps include: Step 1: Obtain relevant parameters of layered frozen soil; Step 2: Solve the pore pressure distribution model of thawing and consolidation of layered frozen soil in seasonally frozen areas to obtain the pore pressure distribution relationship in the thawing area; specifically, the steps include: The first step is to input the external influencing parameters required by the model; The second step is to construct boundary condition equations. Based on the different positions of the thaw line in the soil layer, the thaw line is defined as the first stage when it is at the top layer and the second stage when it is at the bottom layer. The bottom boundary conditions of the first stage and the second stage are obtained by solving the external influencing parameters and layered frozen soil related parameters in the first step. The top boundary condition is defined based on the completely permeable interface in Terzaghi's theorem. The third step is to obtain the general solutions of the excess pore water pressure in the first and second stages of the model based on the governing equation of soil consolidation and the Gaussian error function. Step 4: Based on the general solution of the first stage obtained in step 3 and combined with the bottom boundary conditions and top boundary conditions of the first stage, the pore pressure distribution of the single layer of soil during thawing and consolidation in the first stage is obtained. The initial conditions of the bottom layer in the second stage are obtained based on the pore pressure at the bottom of the model at the end of the first stage. Step 5: Based on the general solution of the pore pressure of the bottom soil in the second stage obtained in the third step, combined with the bottom boundary conditions of the second stage and the initial conditions of the second stage obtained in the fourth step, the pore pressure distribution of the bottom soil in the second stage is obtained; then, based on the Schiffman continuity condition, the top boundary conditions and the general solution of the pore pressure of the top soil in the second stage, the pore pressure distribution of the top soil in the second stage is obtained; Step 3: Calculate the consolidation ratio of thawing and consolidation of layered frozen soil in seasonally frozen areas: Substitute the excess porosity pore pressure distribution obtained in the first and second stages in step 2 into the consolidation ratio solution formula respectively, and then obtain the consolidation ratio prediction structure of each stage. Compare the prediction results with the actual engineering requirements. If the engineering requirements are not met, return to the first step in step 2 to reset the external conditions until the engineering requirements are met.

2. The method for predicting thawing and consolidation of layered frozen soil according to claim 1, characterized in that: The layered frozen soil related parameters include the thickness, permeability coefficient, volume compression coefficient, and saturated density of different soil layers.

3. The method for predicting thawing and consolidation of layered frozen soil according to claim 2, characterized in that: The layered frozen soil related parameters also include the movement of the thaw line S(t), and the consolidation coefficients of the top soil and the bottom soil.

4. The method for predicting thawing and consolidation of layered frozen soil according to claim 1, wherein: The external influencing parameters include a thawing coefficient of a thawing heat source and an initial external transient pressure.

5. The method for predicting thawing and consolidation of layered frozen soil according to claim 1, wherein: In step 3, the first stage consolidation ratio obtained is: The consolidation ratio of the second stage is obtained as:

6. A storage medium, characterized in that The storage medium stores a computer program, and the computer program is suitable for being loaded by a processor and executing the layered frozen soil thawing and consolidation prediction method according to any one of claims 1 to 5.

7. A device, characterized in that The device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the method for predicting thawing and consolidation of layered frozen soil according to any one of claims 1 to 5 is executed.

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