A method for predicting the wet-increase settlement of loess high fill induced by drainage blind ditch failure

Abstract

This invention provides a method for predicting the moisture-induced settlement of loess embankments caused by drainage ditch failure. Relevant data on compacted loess is collected, and a damage function is obtained based on this data, showing the effect of different compaction degrees on the moisture content of loess under moist conditions. A simulation method is established based on the damage function to simulate the impact of drainage ditch failure on the moisture-induced settlement of loess embankments. The variation patterns of displacement, stress, and moisture fields are analyzed, and evaluation parameters for the moisture-induced effect of drainage ditch failure on loess embankments are defined. A prediction model is constructed based on these parameters and variation patterns. The obtained prediction model is then used to analyze the moisture-induced settlement of loess embankments. This invention employs the aforementioned method for predicting the moisture-induced settlement of loess embankments caused by drainage ditch failure, accurately predicting the impact of groundwater uplift induced by drainage ditch failure on the stability of the embankment and foundation deformation in loess embankment projects, providing a scientific basis for engineering design and construction.

Description

Technical Field

[0001] This invention relates to the field of loess high fill, and in particular to a method for predicting the wetted settlement of loess high fill induced by drainage blind ditch failure. Background Technology

[0002] Drainage blind ditches are a common drainage measure in loess high fill projects. Their main function is to reduce the collapsibility of loess by removing groundwater and lowering the groundwater level, thereby reducing the moisture content and deformation of the fill soil. However, if the drainage blind ditch measures fail, it will affect the humidification, deformation, and settlement of the loess high fill.

[0003] When drainage blind ditches fail, the following problems may occur: (1) Rising groundwater level: The failure of drainage blind ditches may lead to a rise in groundwater level, which will increase the moisture content of the fill soil. Loess is sensitive to moisture. When the moisture content increases, its water absorption and collapsibility will also increase, leading to the collapse of the fill soil. Under the influence of gravity, this will further increase the amount of surface settlement, bringing instability and safety hazards to the project. (2) Reduced shear strength: Under high humidity conditions, the shear strength of loess will decrease. The failure of drainage blind ditches will lead to an increase in the humidity of the fill soil, and the shear strength of loess will decrease accordingly, thereby increasing the risk of shear failure of the fill soil.

[0004] Therefore, the failure of drainage blind ditches can negatively impact the moisture-induced deformation and settlement of loess high fills. The resulting rise in groundwater levels due to drainage blind ditch failure leads to increased moisture in the fill soil, causing moisture-induced deformation of the fill foundation. To ensure the safety and stability of the project, effective measures need to be taken to repair or improve the drainage system, restore drainage function in a timely manner, and control the moisture and deformation of the fill soil. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting the humidification and settlement of loess high fill embankments induced by drainage ditch failure, so as to more accurately predict the impact of groundwater rise induced by drainage ditch failure on the stability of the fill body and foundation deformation in loess high fill engineering projects, and provide a scientific basis for engineering design and construction.

[0006] To achieve the above objectives, this invention provides a method for predicting the humidification settlement of loess high embankments induced by drainage blind ditch failure, comprising the following steps:

[0007] Data on compacted loess were collected, and the damage function of loess under different compaction degrees as moisture content increased under moist conditions was obtained based on the data.

[0008] A simulation method for the impact of drainage blind ditch failure on the wetting of loess high fill was established based on the damage function. The variation laws of displacement field, stress field and moisture field under the initial state, seepage state and steady state were analyzed, and a prediction model was obtained based on the variation law.

[0009] The obtained prediction model was used to analyze the wetted settlement of loess high fill, including the average water level rise, wetted deformation, and wetted deformation ratio.

[0010] Preferably, the relevant data for compacted loess include cohesion c and internal friction angle under different compaction degrees and moisture contents of the fill. Compression modulus E s And data on the unit weight γ of the soil.

[0011] Preferably, based on relevant data of compacted loess, the damage function of compacted loess under different compaction degrees as the water content increases under moistening conditions is obtained.

[0012]

[0013] In the formula, c represents cohesion. E is the internal friction angle. s γ is the compression modulus, γ is the unit weight of the soil, and θ is the compressibility modulus. w The value represents the volumetric moisture content, and m1, m2, m3, m4, n1, n2, n3, and n4 are constants related to the degree of compaction.

[0014] Preferably, a simulation method for establishing the impact of drainage blind ditch failure on the wetting of loess high embankments based on damage functions includes the following steps:

[0015] Analysis of initial displacement field and initial moisture field;

[0016] The study was set as a steady-state study; the computational model was divided into equivalent elements using Comsol, and the initial moisture field w0, initial stress field σ0 and initial displacement field S0 in the fill were obtained by setting initial conditions.

[0017] Displacement field analysis under the influence of infiltration due to drainage ditch failure;

[0018] Set the total time and output time step for drainage blind ditch leakage; set the pressure head boundary conditions; set the dependent variable to the initial value of the last solution of the steady-state analysis to be used for the analysis of the seepage state; calculate the water field w1, stress field σ1 and displacement field S1 of the soil after wetting in the high embankment foundation under different compaction degrees and different blind ditch failure rates using the Comsol seepage module.

[0019] Displacement field analysis after seepage stabilization in drainage blind drains

[0020] Set the total time and output time step of the settlement stabilization process. The dependent variable is set to the last solution of the transient analysis of the seepage state study as the initial value of the steady state study. At this time, the seepage stage is completed, and the last solution of the seepage stage study is used as the initial value of the steady state study to simulate the settlement stabilization process of loess high fill surface after the failure of drainage blind ditch.

[0021] The moisture field w2, stress field σ2, and displacement field S2 of the soil in the high embankment foundation after the drainage blind ditch fails and seepage stabilizes are calculated using the Comsol seepage module. The difference between S2 and S0 is the foundation wetting deformation caused by the failure of the drainage blind ditch, as shown in the following formula.

[0022] ΔS = S2 - S1;

[0023] In the formula, △S represents the amount of surface humidification and deformation during seepage.

[0024] Preferably, the three parameters used to describe the wetting effect of loess high embankments induced by blind drain failure are: wetting deformation ratio ζ, blind drain failure rate β, and average water level rise height Δh, including

[0025] Moisture-increase deformation ratio ζ: The ratio of moisture-increase deformation caused by groundwater level rise due to drainage ditch failure to the average rise in groundwater level is defined as the moisture-increase deformation ratio ζ caused by water level rise.

[0026]

[0027] In the formula, △S represents the surface wetting deformation during seepage, and △h max l represents the maximum rise in water level, l represents the groundwater level depth in the model, and l0 represents the initial groundwater level depth.

[0028] Blind drain failure rate β: The degree of failure of a blind drain is defined as the failure rate β of the blind drain, expressed as follows:

[0029]

[0030] In the formula, Q represents the amount of water infiltrating from the inside of the blind drain into the backfill. 总 This represents the total amount of water infiltrating from inside the blind drain into the fill material under the condition of complete blind drain failure.

[0031] Average water level rise Δh: Average water level rise Δh refers to the average increase in water level at a measuring point over a certain period of time. It is used to describe the changes in water levels within high embankments. The expression is...

[0032]

[0033] In the formula, b is the width of the fill.

[0034] Preferred empirical prediction models for average water level rise height Δh, humidification deformation ΔS, and humidification deformation ratio ζ under different compaction degrees and blind drain failure rates.

[0035] Δh=(-74.002β+16.449)λ+87.985β-19.616;

[0036] ΔS=(1433.7β-1.7995)λ-1991.5β+583.09;

[0037] ξ=(0.0083ln(β)-0.0521)ln(λ)+0.0023e 0.1386β ;

[0038] In the formula, λ represents the compaction degree of different fill masses.

[0039] Therefore, the present invention employs the above-mentioned method for predicting the wettability settlement of loess high embankments induced by drainage blind ditch failure, and the technical effects are as follows:

[0040] (1) The incremental law of the highest water level change under the same compaction degree and different blind ditch failure rates: Under the same compaction degree, the highest water level rise height increases rapidly in the early stage with the increase of the blind ditch failure rate β, and then the growth rate gradually slows down and eventually stabilizes. When the compaction degree λ of the fill decreases from 0.98 to 0.88 and the blind ditch failure rate β increases from 25.42% to 100%, the highest water level rise height Δh in the foundation is... max The length increased from 7.91m to 23.13m;

[0041] (2) The incremental law of average water level change under the same compaction degree and different blind ditch failure rates: Under the same compaction degree, the average water level rise height increases rapidly in the early stage as the blind ditch failure rate β increases, and the growth rate gradually slows down and eventually stabilizes. When the compaction degree λ of the fill decreases from 0.98 to 0.88 and the blind ditch failure rate β increases from 25.42% to 100%, the average water level rise height Δh in the foundation increases from 3.89m to 21.69m.

[0042] (3) The wet deformation ratio ζ decreases as the compaction degree λ of the fill and the failure rate β of the blind drain increase. As the failure rate β of the blind drain increases, the wet deformation ratio ζ will gradually decrease and not change much. This phenomenon may be the result of the combined effects of factors such as the increase of soil saturation, the gradual equilibrium of soil settlement, and the gradual weakening of the influence of rising water level on the soil.

[0043] (4) By comparing with the results of the deep immersion test in the actual project, it was found that the humidification deformation ratio ζ of the deep immersion test in the actual project was 1.2%, while the range of the humidification deformation ratio of the numerical simulation test results was 0.4%-1.1%. The obtained humidification deformation ratio curve was close to the measured value. Attached Figure Description

[0044] Figure 1 For finite element and mesh numerical models;

[0045] Figure 2 A model for the failure and leakage of blind drainage ditches;

[0046] Figure 3 This is a schematic diagram illustrating the failure process of a drainage blind ditch due to blockage.

[0047] Figure 4 The curves showing the average water level rise height under different compaction degrees and blind drain failure rates; Figure 4 (a) shows the curves of average water level rise under different compaction degrees; Figure 4 (b) shows the curves of average water level rise under different blind drain failure rates;

[0048] Figure 5 The curve showing the relationship between the failure rate of blind drains and the average water level rise is a fitted parameter curve.

[0049] Figure 6 Curves showing the changes in humidification deformation under different compaction degrees and blind drain failure rates; Figure 6 (a) shows the curves of humidification deformation under different compaction degrees; Figure 6 (b) shows the humidification deformation curves under different blind drain failure rates;

[0050] Figure 7 The curve showing the relationship between the failure rate of blind drains and the fitting parameters of humidification deformation;

[0051] Figure 8 Curves showing the change in humidification deformation ratio under different compaction degrees and blind drain failure rates; Figure 8 (a) shows the variation curves of the wetted deformation ratio under different compaction degrees; Figure 8 (b) shows the variation curves of humidification deformation ratio under different blind drain failure rates;

[0052] Figure 9 The curve showing the relationship between the failure rate of blind drains and the humidification deformation ratio is a fitted parameter curve. Detailed Implementation

[0053] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0054] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0055] Example 1

[0056] A method for predicting the wetted settlement of loess high embankments induced by drainage ditch failure includes the following steps:

[0057] Step 1: Collect relevant data on compacted loess and obtain the damage function of compacted loess with different degrees of compaction as the water content increases under moist conditions.

[0058] The parameters of the soil displacement field model under different compaction degrees are shown in Table 1.

[0059] Table 1 Displacement field model parameters

[0060] Compaction degree λ 0.88 0.9 0.93 0.95 0.98 Poisson's ratio v 0.36 0.35 0.34 0.33 0.32 <![CDATA[Density ρ, g / cm 3 > 1650 1690 1750 1790 1840

[0061] Table 2 shows the relevant parameters of the moisture field model and the parameters of the VG water-holding model under different compaction degrees.

[0062] Table 2. Parameters of water field model and water holding capacity model

[0063]

[0064] Based on the results of consolidation compression tests and shear strength tests of Q3 compacted loess at different compaction degrees and moisture contents, the cohesion c and internal friction angle of the fill at different compaction degrees and moisture contents were obtained. Compression modulus E S0.1-0.2 The variation law of soil mechanical strength parameters. Taking the test results of compaction degree λ=0.93 as an example, the least squares method curve fitting was used to obtain the cohesion c and internal friction angle of the compacted loess at Q3. Compression modulus E S Parameters such as the unit weight γ of the soil change with the volumetric water content θ w The variation pattern is shown in equation (1).

[0065]

[0066] In the formula, c represents cohesion. E is the internal friction angle. s γ is the compression modulus, γ is the unit weight of the soil, and θ is the compressibility modulus. w This represents the volumetric water content.

[0067] By summarizing, the cohesion c and internal friction angle of Q3 compacted loess were obtained. Compression modulus E S These parameters change with compaction degree and volumetric moisture content θ w The variation pattern is shown in Table 3.

[0068] Table 3. Variation of mechanical strength parameters of reconstituted Q3 loess.

[0069]

[0070]

[0071] Based on relevant data of compacted loess, the damage function of compacted loess with different compaction degrees as water content increases under moistening conditions was obtained.

[0072]

[0073] In the formula, c represents cohesion. E is the internal friction angle. s γ is the compression modulus, γ is the unit weight of the soil, and θ is the compressibility modulus. w Let m1, m2, m3, m4, n1, n2, n3, and n4 be volumetric water content, and m1, m2, m3, m4, n4 be constants.

[0074] Step 2: Based on the damage function, establish a simulation method for the impact of drainage blind ditch failure on the wetting of loess high fill, analyze the variation law of displacement field, stress field and moisture field under the initial state, seepage state and steady state, and obtain the prediction model based on the variation law;

[0075] To meet research needs, a geometric model of a 110m loess embankment foundation under the condition of drainage blind ditch failure was established. To improve computational efficiency and accuracy, the mesh of the embankment soil within the seepage and moisture-increasing range of the drainage blind ditch was densified, while the mesh of the embankment soil outside this range was loosened. The model height was set at 110m, the drainage blind ditch type was a full gravel blind ditch, the upper bottom width was 0.41m, the lower bottom width was 0.33m, and the height was 0.2m. The soil was set as fill, the groundwater level was 105m deep, and the drainage blind ditch was 5m above the bottom of the embankment. The specific numerical model is as follows: Figure 1 As shown.

[0076] (1) Initial state study: analysis of initial displacement field and initial moisture field;

[0077] The study was set to steady-state; the pressure head boundary condition in the Richards equations (dl) module was disabled. The computational model was divided into equivalent elements using Comsol, and the initial water state field w0, initial stress field σ0, and initial displacement field S0 within the fill were obtained by setting initial conditions.

[0078] (2) Seepage state study: Displacement field analysis under the influence of infiltration due to drainage blind ditch failure;

[0079] Set the total time and output time step for drainage blind drain leakage; enable pressure head boundary conditions; set the dependent variable to the initial value of the last solution of the steady-state analysis to be used as the initial value for the seepage state analysis. Calculate the moisture field w1, initial stress field σ1, and initial displacement field S1 of the soil after wetting in the high embankment foundation under different compaction degrees and different blind drain failure rates using the Comsol seepage module.

[0080] (3) Steady state study: displacement field analysis after seepage in drainage blind ditch stabilizes.

[0081] Set the total time and output time step for the settlement stabilization process, and disable the pressure head boundary condition; the dependent variable is set to use the last solution of the transient analysis of the seepage state as the initial value for the steady-state study. At this point, the seepage stage is complete, and the last solution of the seepage stage study is used as the initial value for the steady-state study, which can simulate the surface settlement stabilization process of loess high fill after the failure of drainage blind ditches.

[0082] The moisture field w2, initial stress field σ2, and initial displacement field S2 of the soil in a high-fill foundation after seepage stabilization following the failure of the drainage ditch were calculated using the Comsol seepage module. The difference between S2 and S0 represents the soil wetting deformation caused by the failure of the drainage ditch, as shown in the following formula:

[0083] ΔS=S2-S1 (3);

[0084] In the formula, △S represents the amount of surface humidification and deformation during seepage.

[0085] The above simulation method is used for simulation.

[0086] In the analysis of unsaturated loess wetting deformation, changes in the water environment conditions cause changes in the soil's moisture field, leading to a weakening of the soil's mechanical strength parameters. Therefore, to simulate the wetting process using numerical analysis software, the soil parameters must be changed in real time and accordingly to simulate the actual soil wetting process. Thus, in the specific analysis below, we first set the interpolation function between the soil parameters and the effective saturation / volume water content. In the subsequent seepage calculation, the soil's mechanical and stiffness parameters will change with the changes in the effective saturation / volume water content under the influence of seepage. By assigning new mechanical and stiffness parameters to the soil based on the changed seepage field, we can simulate the soil wetting deformation process under the influence of changes in the moisture field.

[0087] Comsol software's Richards equations seepage module can analyze unsaturated seepage in loess high-fill foundations caused by water infiltration. By setting up the Richards equations and solid mechanics physics field interface, fluid-structure interaction analysis of unsaturated loess can be performed. The approach to analyzing humidification deformation in this paper is to calculate the initial displacement field S0 under the initial state and the displacement S2 after water infiltration stabilizes; the difference between these two displacements represents the humidification deformation of the unsaturated loess caused by humidification.

[0088] In the Comsol software, the specific module selection and calculation interface settings are as follows:

[0089] (1) Setting up the seepage field: After the blind drain fails, seepage occurs in the fill soil within the high-fill ditch, forming a saturated-unsaturated seepage zone. Therefore, the Richards equation, which can simulate unsaturated soil seepage, is selected in the software. At the same time, the fluid material parameters and porous matrix material parameters in the unsaturated porous medium are set. The fluid material parameters are the density of the fluid, and the porous matrix material parameters are the porosity and hydraulic conductivity (permeability) of the soil. A water-holding model based on the VG function is also set. The relevant soil parameters and boundary conditions of the model that affect the seepage of unsaturated soil are input.

[0090] (2) Setting the stress field: In the software, select the solid mechanics interface. First, set the soil model to an ideal elastoplastic model and input the relevant basic soil parameters. Then, replace the soil cohesion, internal friction angle, and Young's modulus with interpolation functions E = f1(S) related to the water content change. e ), c = f2(S e ), The relevant model boundary conditions are then set. The changes in the displacement field are ultimately obtained through fluid-structure interaction analysis.

[0091] (3) Setting up fluid-structure interaction analysis: By consulting relevant literature, the fitting functions of soil mechanical strength parameters and volumetric water content were summarized, and the relationship between soil parameters and water content under different compaction degrees was obtained as E=f1(θ w ), c = f2(θ) w ), According to equation (4), E, ​​c, and ... are then established in the software respectively. Regarding the interpolation function for the effective saturation Se, we get E = int1(S e ), c = int2(S e ), That is, “E=f1(S e ), c = f2(S e ),

[0092]

[0093] S e θ represents the effective saturation; θ represents the volumetric water content (%). r Residual volumetric moisture content / %; θ s The saturated volumetric water content is expressed as %.

[0094] Substituting the above interpolation function into the elastoplastic constitutive model, the change in the displacement field within the foundation caused by humidification can be obtained through calculation, thereby obtaining the amount of humidification deformation of the loess high-fill foundation. The soil is set as an isotropic material, and the magnitude of the Biot-Willis coefficient represents the interaction between soil stress and moisture in the soil, as shown in equation (5), which is a built-in calculation formula in the software.

[0095] σ=Dε v -α B pI (5);

[0096] In the formula, σ is the soil stress, D is the stiffness matrix; ε v p is the volumetric strain; p is the pore water pressure in Pa; I is the identity matrix; α B This represents the Biot-Willis coefficient.

[0097] A schematic diagram of the specific drainage blind ditch model and calculation results is shown below. Figure 2 As shown.

[0098] When drainage blind ditches become blocked or geotextiles fail, the water in the drainage blind ditches cannot be effectively drained, causing the water in the drainage blind ditches to infiltrate into the surrounding soil, thereby causing the groundwater level to rise. This change in the moisture field will cause the soil particles in the humidified area to rearrange and compact, resulting in surface subsidence.

[0099] Gravel drainage blind drains are a common type of surface drainage system used to collect and discharge surface runoff to prevent hydrological disasters and soil erosion. However, these drainage systems can fail due to sediment accumulation, silt erosion, and debris blockage. These factors accumulate over time, gradually worsening the blockage. As the blockage increases, the drainage efficiency of the blind drain gradually decreases, eventually leading to complete failure. A schematic diagram illustrating the general process of blockage failure in gravel drainage blind drains is shown below. Figure 3 As shown.

[0100] Three parameters are used to describe the wetting effect of loess high embankments induced by blind drain failure: wetting deformation ratio ζ, blind drain failure rate β, and average water level rise height Δh, including...

[0101] Moisture-increase deformation ratio ζ: The ratio of moisture-increase deformation caused by groundwater level rise due to drainage ditch failure to the average rise in groundwater level is defined as the moisture-increase deformation ratio ζ caused by water level rise.

[0102]

[0103] In the formula, △S represents the surface wetting deformation during seepage, and △h maxl represents the maximum rise in water level, l represents the groundwater level depth in the model, and l0 represents the initial groundwater level depth.

[0104] Blind drain failure rate β: The degree of failure of a blind drain is defined as the failure rate β of the blind drain, expressed as follows:

[0105]

[0106] In the formula, Q represents the amount of water infiltrating from the inside of the blind drain into the backfill. 总 This represents the total amount of water infiltrating from inside the blind drain into the fill material under the condition of complete blind drain failure.

[0107] Average water level rise Δh: Average water level rise Δh refers to the average increase in water level at a measuring point over a certain period of time. It is used to describe the changes in water levels within high embankments. The expression is...

[0108]

[0109] In the formula, b is the width of the fill.

[0110] Taking a typical unsaturated loess high fill project as the object of numerical analysis, with a fill height of 110.0m and a groundwater level of 105m below ground, the humidification deformation caused by leakage due to the failure of drainage blind ditches in the unsaturated loess high fill is numerically analyzed to obtain its variation law.

[0111] 1. Distribution of water field within backfill soil under different drainage ditch failure conditions

[0112] (1) Variation of the highest water level rise under different compaction degrees and different blind drain failure rates

[0113] After the failure and leakage of the deep drainage blind ditch in the loess high-fill foundation, the highest water level in the foundation initially increased rapidly, but the rate of increase gradually slowed down and eventually stabilized. When the soil compaction degree was 0.88, after 100 years of seepage, and the blind ditch failure rate β was 100%, the maximum rise in the highest water level within the high-fill foundation was 23.13 m; when the soil compaction degree was 0.98, after 100 years of seepage, and the blind ditch failure rate β was 25.42%, the minimum rise in the highest water level within the high-fill foundation was 7.91 m. This shows that as the external water pressure increases and the moisture content of the surrounding soil increases, the water pressure inside and outside the drainage blind ditch gradually balances, eventually reaching a stable state. The higher the failure rate (β) of the blind drain, the greater the water pressure within the drain, the faster the water level rises, and the higher the achievable maximum water level. Conversely, the greater the soil compaction, the more difficult it is for water leaking from the drain due to failure to infiltrate into the surrounding soil, resulting in a slower water level rise and a lower achievable maximum water level. Conversely, the smaller the compaction and the lower the failure rate (β), the shorter the time it takes for the maximum water level to reach a stable level.

[0114] (2) Variation of average water level rise under different compaction degrees and different blind drain failure rates

[0115] After the failure and leakage of deep drainage blind ditches in loess high-fill foundations, the average water level in the high-fill foundation initially rises rapidly, then the rate of rise gradually slows down and eventually stabilizes. When the soil compaction degree is 0.88, after 100 years of seepage, when the failure rate β = 100%, the maximum rise in average water level within the high-fill foundation is 21.69 m; when the soil compaction degree is 0.98, after 100 years of seepage, when the failure rate β = 25.42%, the minimum rise in average water level within the high-fill foundation is 3.89 m. The greater the failure rate β of the blind ditch, the greater the water pressure within the drainage blind ditch, the faster the average water level rises, and the higher the achievable average water level. Conversely, the greater the soil compaction degree, the more difficult it is for the leaked water from the drainage blind ditch to infiltrate into the surrounding soil, resulting in a slower rate of rise in average water level and a lower achievable maximum water level. The smaller the compaction degree and the failure rate β of the blind drain, the shorter the time it takes for the average water level rise to reach a stable state.

[0116] 2. Distribution law of displacement field inside the backfill under different drainage blind ditch failure conditions

[0117] As compaction increases, the moisture-increasing deformation of the embankment foundation gradually decreases; as the failure rate of the blind drain increases, the moisture-increasing deformation of the embankment foundation gradually increases. Due to the influence of the overburden weight of the drainage blind drain, the closer to the ground surface, the greater the foundation deformation.

[0118] After 100 years of seepage, under the same compaction degree, the greater the failure rate β of the blind drain, the greater the surface wetting deformation ΔS. Under the same blind drain failure rate, the greater the compaction degree of the backfill, the smaller ΔS. When the compaction degree is 0.88 and the blind drain failure rate β is 100%, the maximum ΔS is -204.93 mm; when the compaction degree is 0.98 and the blind drain failure rate β is 25.42%, the minimum ΔS is -15.73 mm. Under the same backfill compaction degree, the greater the blind drain failure rate β, the greater the water pressure in the drainage blind drain and the greater the internal and external water pressure difference with the surrounding soil. Water in the drainage blind drain can be discharged into the surrounding soil more quickly, resulting in greater wetting deformation due to water level rise. Under the same blind drain failure rate β, the greater the backfill compaction degree, the denser the backfill, the smaller the pores between soil particles, and the more difficult it is for water in the drainage blind drain to infiltrate into the surrounding backfill. The smaller the wetting deformation due to water level rise.

[0119] After 100 years of seepage, under the same backfill compaction conditions, the larger the blind drain failure rate β, the smaller the wet deformation ratio ζ; under the same blind drain failure rate conditions, the larger the backfill compaction, the smaller the wet deformation ratio ζ. When the compaction degree is 0.88 and the blind drain failure rate β is 19.64%, ζ is at its maximum of 1.1%; when the compaction degree is 0.98 and the blind drain failure rate β is 100%, ζ is at its minimum of 0.4%.

[0120] As the failure rate of blind drains increases, the wetted deformation ratio ζ gradually decreases and remains relatively stable. This phenomenon may be the result of a combination of factors, including increased soil saturation, soil settlement gradually reaching equilibrium, and the weakening impact of rising water levels on the soil. Specifically, it manifests as follows:

[0121] (1) The soil saturation gradually increases: When the drainage blind ditch is blocked and the geotextile fails, the infiltration of water will gradually saturate the soil around the drainage blind ditch. The saturated soil will gradually become denser, thus reducing the wet deformation ratio ζ and gradually stabilizing.

[0122] (2) Soil settlement gradually reaches equilibrium: In the initial stage, the blockage of drainage blind ditches will lead to a faster rate of surface settlement. However, as time goes by, the moisture in the soil will gradually reach equilibrium, and the rate of surface settlement will gradually decrease.

[0123] (3) The impact of rising water levels on soil gradually weakens: In the initial stage, rising water levels may have a significant impact on soil compaction, resulting in a faster rate of surface subsidence. As time goes by, the impact of rising water levels on soil may gradually weaken, leading to a slower rate of surface subsidence.

[0124] Empirical Model of Humidification Deformation Caused by Drainage Ditch Failure

[0125] (1) Simplified empirical models of the average water level rise Δh with different blind drain failure rates β and different fill compaction degrees λ are shown in Tables 4 and 5.

[0126] Table 4. Fitting formulas for average water level rise in reconstituted loess under different blind drain failure rates.

[0127] Compaction degree λ Fitting formula Fitting accuracy 0.88 Δh = 10.6081ln(β) + 2.9282 0.9533 0.9 Δh = 10.3471ln(β) + 2.9615 0.9562 0.93 Δh = 9.5277ln(β) + 3.1368 0.9605 0.95 Δh = 9.105ln(β) + 3.2414 0.9755 0.98 Δh = 7.0094ln(β) + 3.1862 0.9704

[0128] Table 5. Fitting formulas for the average water level rise height of reconstituted loess under different compaction degrees.

[0129]

[0130] From the data in Tables 4 and 5 above, we can obtain the variation law of the average water level rise height under different fill compaction degrees and blind drain failure rates, see... Figure 4 .

[0131] Table 5 shows the relationship between the average water level rise Δh and the compaction degree λ of different fill masses.

[0132] Δh=a1·λ+b1 (9);

[0133] In the formula, a1 and b1 are the fitting curve parameters related to the average water level rise.

[0134] To more accurately reflect the changes in the water field caused by the rise in water level after the failure of the drainage blind ditch and to obtain its average water level rise height, the parameters a1 and b1 in equation (9) can be used to establish a functional relationship with the blind ditch failure rate β, as shown in Table 6. Figure 5 As shown.

[0135] Table 6. Fitting parameters and formulas for blind drain failure rate ± and average water level rise.

[0136] parameter Fitting formula Fitting accuracy <![CDATA[a1]]> <![CDATA[a1=-74.002β+16.449]]> 0.9625 <![CDATA[b1]]> <![CDATA[b1=87.985β-19.616]]> 0.8008

[0137] (2) Simplified empirical models of humidification deformation ΔS with different blind drain failure rates β and different fill compaction degrees λ are shown in Tables 7 and 8.

[0138] Table 7. Fitting formulas for moisture-increasing deformation and blind drain failure rate under different compaction degrees.

[0139] Compaction degree λ Fitting formula Fitting accuracy 0.88 ΔS = -95.021ln(β) - 36.712 0.9541 0.9 ΔS = -76.65ln(β) - 30.521 0.9561 0.93 ΔS = -59.68ln(β) - 24.412 0.9589 0.95 ΔS = -42.99ln(β) - 18.861 0.9635 0.98 ΔS = -26.221ln(β) - 13.526 0.9725

[0140] Table 8. Fitting formulas for humidification deformation and compaction degree under different blind drain failure rates.

[0141] Blind drain failure rate, % Fitting formula Fitting accuracy 21.63 ΔS = 324.43λ - 332.81 0.9934 42.77 ΔS = 591.8λ - 607.91 0.9921 61.95 ΔS = 886.95λ - 906.33 0.9937 82.29 ΔS = 1168.9λ - 1192.1 0.9936 100 ΔS = 1444λ - 1470.7 0.9932

[0142] From the data in Tables 7 and 8 above, we can obtain the variation law of wetting deformation under different fill compaction degrees and blind drain failure rates, see... Figure 6 .

[0143] As shown in Table 8, the relationship between the average water level rise Δh and the compaction degree λ of different fill bodies conforms to the characteristics of Equation (10).

[0144] ΔS=a2·λ+b2 (10);

[0145] In the formula, a2 and b2 are the fitting curve parameters related to humidification deformation, respectively.

[0146] To more accurately reflect the displacement field changes caused by the rise in water level after the failure of the drainage blind ditch and obtain its humidification deformation, the parameters a2 and b2 of equation (10) can be used to establish a functional relationship with the blind ditch failure rate β, as shown in Table 9. Figure 7 As shown.

[0147] Table 9 Fitting Parameters and Formulas for Blind Drain Failure Rate and Wetness Deformation

[0148] parameter Fitting formula Fitting accuracy <![CDATA[a2]]> <![CDATA[a2=1433.7β-1.7995]]> 0.9989 <![CDATA[b2]]> <![CDATA[b2=-1991.5β+583.09]]> 0.5843

[0149] (3) Simplified empirical models of the humidification deformation ratio ζ with different blind drain failure rates β and different fill compaction degrees λ are shown in Tables 10 and 11.

[0150] Table 10 Fitting formulas for wettability deformation ratio and blind drain failure rate under different compaction degrees

[0151] Compaction degree λ Fitting formula Fitting accuracy 0.88 ξ=-0.0011ln(β)+0.0112 0.9541 0.9 ξ = -0.0011ln(β) + 0.0093 0.9561 0.93 ξ=-0.0011ln(β)+0.0073 0.9589 0.95 ξ=-0.0011ln(β)+0.0057 0.9635 0.98 <![CDATA[ξ=0.0041e -0.017β ]]> 0.5312

[0152] Table 11 Fitting Formulas for Wetting Deformation Ratio and Compaction Degree of Fill under Different Blind Drain Failure Rates

[0153]

[0154] From the data in Tables 10 and 11 above, the variation law of the wetting deformation ratio under different fill compaction degrees and blind drain failure rates was obtained, see... Figure 8 .

[0155] The relationship between the wettability deformation ratio ζ and the compaction degree λ of different fill masses:

[0156] ξ=a3ln(λ)+b3 (11);

[0157] In the formula, a3 and b3 are the fitting curve parameters related to the humidification deformation ratio.

[0158] To more accurately reflect the change in the humidification deformation ratio caused by the rise in water level after the failure of the drainage blind ditch, and to obtain a simplified empirical model of the humidification deformation ratio, the parameters a3 and b3 in equation (11) can be functionally related to the blind ditch failure rate β, as shown in Table 12. Figure 9 As shown.

[0159] Table 12 Fitting parameters and formulas for blind drain failure rate and humidification deformation ratio

[0160] parameter Fitting formula Fitting accuracy <![CDATA[a3]]> <![CDATA[a3=0.0083ln(β)-0.0521]]> 0.6239 <![CDATA[b3]]> <![CDATA[b3=0.0023e 0.1386β ]]> 0.4962

[0161] pass Figures 4 to 9 The fitted parameter relationship curves can be used to obtain prediction models for the average water level rise height Δh, humidification deformation ΔS, and humidification deformation ratio ζ under different compaction degrees and blind drain failure rates.

[0162] Δh=(-74.002β+16.449)λ+87.985β-19.616 (12);

[0163] ΔS=(1433.7β-1.7995)λ-1991.5β+583.09 (13);

[0164] ξ=(0.0083ln(β)-0.0521)ln(λ)+0.0023e 0.1386β (14);

[0165] In the formula, β represents the failure rate of the blind drain, and λ represents the compaction degree of different fill materials.

[0166] Step 3: Analyze the wetted settlement of loess high fill using the obtained prediction model, including the average water level rise, wetted deformation, and wetted deformation ratio.

[0167] The above methods were used for prediction and compared with actual measured cases.

[0168] The topography of the planned area of ​​Yan'an New Area is characterized by interspersed gullies and ridges, with varying elevations, generally higher in the southeast and lower in the northwest. The elevations of the gullies and ridges range from 974 to 1294 meters. Based on the distribution and orientation of the ridges and slopes, Yan'an New Area can be divided into four watersheds: Huanghaowa Watershed, Liushudian Watershed, Yefuzigou Watershed, and Wangchagou Watershed. The specific landforms consist of tops, gullies, ridges, and slopes, with an overall slope of approximately 2-3%. The original topography of the proposed project site is highly undulating, encompassing three independent main watersheds: Huanghaowa Watershed, Yefuzigou Watershed, and Liushudian Hougou Watershed.

[0169] In a certain drainage blind ditch scheme, the internal structure of the drainage blind ditch combines crushed stone and culverts, with geotextile fabric laid on the outside. Based on the cross-sectional flow rate of each watershed, the diameter of the culverts in the main blind ditch is 500–800 mm. The crushed stone placement above the culverts effectively reduces the pressure of the overlying soil, protecting the culverts from crushing damage. Gabion mesh is placed on both sides of the culverts, with crushed stone placed within the gabion mesh. A 40cm thick geogrid-reinforced crushed stone cushion layer is laid on top of the gabion mesh, creating a soil arch effect and further reducing the overlying soil pressure on the pipe. The culverts in the drainage blind ditch are made of plastic pipes; as flexible materials, they reduce the pressure of the crushed stone on the pipe top, acting as a buffer and protecting the culvert.

[0170] The established model uses the same cross-sectional dimensions as the drainage blind ditch arranged in the actual project, and the drainage blind ditch type is selected as a full crushed stone blind ditch. The model is then established and numerical analysis is performed based on this.

[0171] A deep immersion test was conducted using the Yan'an New Area project as an example to study the impact of rising deep groundwater on the soil's wetting and deformation. The rising process of the groundwater level was simulated by continuous water injection.

[0172] The soil samples used in the deep immersion test came from loose loess of the Middle and Late Pleistocene strata excavated from the Yan'an New Area project. The compacted soil was obtained through a method of loose spreading, moistening, rolling and testing. The moisture content of each layer of the fill soil was continuously monitored by using a TDR moisture meter that was installed in advance.

[0173] The deep immersion test was conducted on high-fill sites where the soil settlement of each layer had basically stabilized 12 months after completion. The deep immersion lasted for 30 days, and the groundwater level rose by 10 meters. Monitoring showed that the wetting deformation of the fill soil reached 58 mm, with a wetting deformation ratio ζ of 1.2%. Due to the early filling time and long compaction time experienced during construction in actual projects, the compacted soil had a high degree of compaction and a very low wetting deformation coefficient, resulting in a small amount of wetting deformation at the bottom of the fill.

[0174] The model established in this paper has a fill depth of 110m, a fill width of 40m, a depth l from the top surface of the fill to the groundwater level of 105m, and a seepage time of 100 years. The compacted loess parameters used in the experiment are: relative density of soil particles d. s =2.70, initial void ratio e0 is 0.47-0.64, natural dry density ρ d The concentration is 1.65-1.84 g / cm³. 3 The natural moisture content (w) of the soil sample ranged from 9.5% to 12.8%, and the hydraulic conductivity (K) was... s It is 8.1×10 -10 -7.29×10 -9 m / s.

[0175] When the compaction degree is 0.88 and the blind drain failure rate β is 19.64%, the maximum wettability deformation ratio ζ is 1.1%; when the compaction degree is 0.98 and the blind drain failure rate β is 100%, the minimum wettability deformation ratio ζ is 0.4%. Since the dry density of the soil tested in actual engineering projects is lower than that of the compacted soil used in this simulation, the actual deep immersion test results show greater wettability deformation due to the rise in groundwater level, and thus a larger wettability deformation ratio. Comparison with the test results of the deep immersion test in the aforementioned actual engineering projects reveals that the wettability deformation ratio curve obtained from the simulation is close to the measured value. A comparison of the parameters and results between the measured and simulated values ​​is shown in Table 13.

[0176] Table 13 Comparison of Measured and Simulated Values ​​and Results

[0177] parameter L / m <![CDATA[d s ]]> Β / % △h / m △S / mm Z / ％ Measured value 50 2.71 100 10 58 1.2 Simulated values 105 2.70 19.64-100 3.9-21.7 15.73-204.93 0.4-1.1

[0178] Therefore, the present invention adopts the above-mentioned method for predicting the wetted settlement of loess high fill induced by the failure of drainage blind drains, which more accurately predicts the impact of groundwater rise induced by the failure of blind drains on the stability of the fill body and the deformation of the foundation in loess high fill projects, and provides a scientific basis for engineering design and construction.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. 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 still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for predicting the humidification settlement of loess high fill induced by drainage blind ditch failure, characterized in that, Includes the following steps: Data on compacted loess were collected, and the damage function of loess under different compaction degrees as moisture content increased under moist conditions was obtained based on the data. A simulation method for the impact of drainage blind ditch failure on the moistening of loess high fill was established based on the damage function. The variation laws of displacement field, stress field and moisture field under the initial state, seepage state and steady state were analyzed. The evaluation parameters of the moistening effect of loess high fill induced by blind ditch failure were further defined, and a prediction model was constructed based on the evaluation parameters and variation laws. The obtained prediction model was used to analyze the wetted settlement of loess high fill, including the average water level rise, wetted deformation, and wetted deformation ratio. A simulation method for the impact of drainage blind ditch failure on the wetting of loess high embankments is established based on the damage function, including the following steps: Analysis of initial displacement field and initial moisture field; The study was set as a steady-state study; the computational model was divided into equivalent elements using Comsol, and the initial moisture field within the fill was obtained by setting initial conditions. Initial stress field and initial displacement field ; Displacement field analysis under the influence of infiltration due to drainage ditch failure; Set the total time and output time step for drainage ditch leakage; set the pressure head boundary conditions; set the dependent variable to the initial value of the last solution of the steady-state analysis to be used as the initial value for the seepage state study; calculate the moisture field of the soil after wetting in the high embankment foundation under different compaction degrees and different ditch failure rates using the Comsol seepage module. Stress field and displacement field ; Displacement field analysis after seepage stabilization in drainage blind drains; Set the total time and output time step of the settlement stabilization process. The dependent variable is set to the last solution of the transient analysis of the seepage state study as the initial value of the steady state study. At this time, the seepage stage is completed, and the last solution of the seepage stage study is used as the initial value of the steady state study to simulate the settlement stabilization process of loess high fill surface after the failure of drainage blind ditch. The moisture field within the soil of a high-fill foundation after seepage stabilization following the failure of the drainage blind ditch was calculated using the Comsol seepage module. Stress field and displacement field , and The difference is due to the soil moisture deformation caused by the failure of the drainage blind ditch, as shown in the following formula. ； In the formula, This represents the amount of surface moisture increase and deformation during seepage. Three evaluation parameters for the wetting effect of loess high embankments induced by blind drain failure include: Humidification deformation ratio The ratio of the increase in moisture deformation caused by the rise in groundwater level due to the failure of drainage blind ditches to the average rise in water level is defined as the ratio of the increase in moisture deformation caused by the rise in water level. ,as follows: ； In the formula, This represents the surface moisture increase and deformation during seepage. This represents the maximum water level rise height. The depth of the groundwater level in the model. This represents the initial groundwater level depth. Blind drain failure rate The failure rate of blind drains is defined as the degree of failure of blind drains. The expression is: ； In the formula, This represents the amount of water infiltrating from inside the blind drain into the fill material. This represents the total amount of water infiltrating from inside the blind drain into the fill material under the condition of complete blind drain failure. Average water level rise Average water level rise It refers to the average increase in water level at a measuring point over a certain period of time, used to describe the changes in water quality within a high embankment. The expression is: ； In the formula, This refers to the width of the fill body; Average water level rise under different compaction degrees and blind drain failure rates Humidification deformation and humidification deformation ratio Empirical prediction model ； ； ； In the formula, This indicates the compaction degree of different fill materials.

2. The method for predicting the humidification and settlement of loess high embankments induced by drainage blind ditch failure according to claim 1, characterized in that, Relevant data on compacted loess include cohesion under different compaction degrees and moisture contents of the fill. internal friction angle 、 compression modulus and the unit weight of the soil The data.

3. The method for predicting the humidification and settlement of loess high embankments induced by drainage blind ditch failure according to claim 1, characterized in that, Based on relevant data of compacted loess, the damage function of compacted loess with different compaction degrees as water content increases under moistening conditions was obtained. ； In the formula, For cohesion, It is the internal friction angle. For compressibility modulus, The unit weight of the soil. This refers to the volumetric moisture content. It is a constant and related to the degree of compaction.

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