CN112364543A - Seepage simulation method based on soft plastic loess tunnel double-row type cluster well precipitation model - Google Patents
Seepage simulation method based on soft plastic loess tunnel double-row type cluster well precipitation model Download PDFInfo
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Abstract
The invention relates to a seepage simulation method based on a soft-plastic loess tunnel double-row type cluster well precipitation model, which takes soft-plastic loess as a test object, establishes a three-dimensional soft-plastic loess geologic body and disperses grids according to hydrogeological parameters and engineering geological parameters; loess is used as an elastic material, and finite element grid element feature analysis and seepage model calculation formats are established; considering grid steady-state well models and underground water level changes under different precipitation conditions; and solving the established coupling model of the groundwater seepage and the double-row precipitation well, and carrying out the sensitivity analysis of groundwater level parameters on different water inflow amounts and permeability coefficients.
Description
Technical Field
The invention relates to the technical field of groundwater seepage simulation, in particular to a seepage simulation method based on a soft plastic loess tunnel double-row type group well precipitation model.
Background
At present, the seepage simulation process of establishing a soft plastic loess precipitation model in a finite element method has the following problems:
1. the testing method mostly adopts indoor tests or field tests with insufficient depth, and is difficult to accurately simulate the seepage process of the groundwater in the soft plastic loess area.
2. The results of the soft plastic loess area in the exploration period are lack of analysis, and are difficult to rise to the mechanism level, so that the influence change of the underground water is not known.
3. At present, the change of soft plastic loess areas under the seepage action is lack of system analysis, and researchers are limited to the analysis of a certain layer, so that the whole process of complete natural seepage, drainage, precipitation and water level recovery is difficult to accurately describe, and the system research on the underground water motion characteristics of different loess areas is lack.
Disclosure of Invention
The invention aims to provide a seepage simulation method based on a double-row group well precipitation model of a soft-plastic loess tunnel.
The technical scheme adopted by the invention is as follows:
seepage simulation method based on soft plastic loess tunnel double-row type cluster well precipitation model is characterized in that:
the method comprises the following steps:
s1, taking the soft plastic loess as a test object, and establishing a three-dimensional soft plastic loess geologic body and dispersing grids according to the hydrogeological parameters and the engineering geological parameters;
s2, building a finite element grid element feature analysis and seepage model calculation format by taking loess as an elastic material;
s3, considering grid steady-state well models and underground water level changes under different precipitation conditions;
s4, solving the established underground water seepage and double-row precipitation well coupling model, and carrying out underground water level parameter sensitivity analysis on different water inflow and permeability coefficients.
Step S2 includes the following steps:
the equilibrium equation in the basic equation used in the linear elasticity analysis of elastic materials is as follows:
Ku＝p (1)
the symbols in the formula are defined as follows: k is a structural rigidity matrix, u is a displacement vector, and p is a load vector or an unbalanced force vector;
taking an elastic material as a model base, the total strain generated under the action of load comprises elastic strain and plastic strain:
ε＝εe+εp (2)
wherein the symbols define ε as the total strain εeIs elastically strained, epsilonpIs plastic strain;
the stress is determined by the elastic part of the rate of change of strain, i.e. the standard plastic constitutive equation:
dσ＝De(dε-dεp)＝De(dε-dλa) (3)
in the formula, DeFor the elastic stiffness matrix, the slight strain change rates are as follows:
dσ＝Cdε-dλCa (4)
performing iterative computation by adopting a Newton-Laplacian method, and accelerating convergence rate by using a coordinated stiffness matrix:
and,
step S3 includes the following steps:
the basic equation of seepage theory is as follows:
the symbols in the formula are defined as follows: h is the total head, kxPermeability coefficient in x direction, kyPermeability coefficient in the y direction, kzThe permeability coefficient in the z direction is shown, Q is the flow, theta is the volume water content, and t is the time;
the equation means that the variation of inflow and outflow of a tiny volume at any position and at any time is the same as the variation of the volume water content, and the sum of the flow variation in the x, y and z directions and the external flow is the same as the variation of the volume water content;
at a certain elevation, the derivative function over time is zero, becoming the following equation:
the finite element equations representing the fundamental equations using the Galerkin method of emphasizing residuals are as follows:
∫([B]T[C][B])dV{H}+∫(λ<N>T<N>)dV{H}t＝q∫(<N>T)dA (10)
the symbols in the formula are defined as follows: [ B ]]Is a running water gradient matrix, [ C]Is the unit permeability coefficient matrix, { H } is the node head vector,<N>for the shape function vector, q is the unit flow λ ═ m on the unit sidewγwIs a choked flow term for unsteady flows,
is the head of water over time;
the finite element solution of the unsteady flow analysis is a function of time, and the integral of the time uses a finite difference method; the finite element equation is expressed using a finite difference method as follows:
(ωΔt[K]+[M]){H1}＝Δt((1-ω){Q0}+ω{Q1})+([M]-(1-ω)Δt[K]){H0} (11)
the symbols in the formula are defined as follows: Δ t is the time increment, ω: ratio between 0 and 1, { H1Water head at the end of time increment, { H }0Water head at the beginning of time increment, { Q }1{ Q } is the node flow at the end of the time increment0The flow rate of a node at the beginning of time increment is defined as { K } unit characteristic matrix, and the quality matrix of the unit is defined as { M };
the MIDAS/GTS uses a back-off difference method, and omega of the method is 1.0; the omega of the finite element equation for unsteady flow analysis is 1.0, so
(Δt[K]+[M]){H1}＝Δt{Q1}+[M]{H0} (12)。
The invention has the following advantages:
1. the invention makes full field in-situ test for soft plastic loess area, and the field sampling test is closer to the actual situation compared with the indoor physical model or test, thus providing a foundation for the depth and precision of the model.
2. The invention adopts a finite element method, and has abundant data and graph post-processing modes when interacting with a computer.
3. The invention sets different boundary conditions, researches the underground water seepage process under various conditions, and provides theoretical reference for engineering practice.
Drawings
FIG. 1: and (5) a three-dimensional model generalized diagram.
FIG. 2: and (5) a three-dimensional model grid division diagram of tunnel precipitation.
FIG. 3: and (4) arranging pumping wells of the three-dimensional model of tunnel precipitation.
FIG. 4: water level change diagram in the water pumping stage.
FIG. 5: water level change diagram in water level recovery stage.
FIG. 6: the relation graph of the flow rate of the pumping well and the depth reduction.
FIG. 7: and (3) a permeability coefficient and a depth reduction relation graph.
Detailed Description
The present invention will be described in detail with reference to specific embodiments.
The invention relates to a seepage simulation method based on a soft plastic loess tunnel double-row type group well precipitation model, which is a seepage simulation process for establishing the soft plastic loess tunnel double-row type group well precipitation model based on a finite element method and specifically comprises the following steps:
in step S1, the stratigraphic structure of the investigation region is revealed from the borehole, a generalized stratigraphic is established for the model and the influence of the boundary conditions is fully considered.
In the step of S2, coupling the soft plastic loess tunnel model with the groundwater seepage numerical simulation analysis process, wherein the key point is to adopt a stratum material model.
In the step S3, a seepage model is established by combining the steps S1 and S2, and in order to simulate the rainfall seepage situation more truly, a tetrahedral automatic solid mesh splitting method is adopted, so that the model precision is guaranteed.
In the step S4, different boundary conditions are set, underground water seepage processes under various conditions are researched, and theoretical reference is provided for engineering practice.
Example of implementation, Yinxi high-speed railway Yima tunnel
And step S1: three-dimensional model generalization and boundary condition setting
The groundwater runoff of the highland of the directors is generally flowing from the center of the highland with a higher water level to the highland, the runoff speed is relatively slow, the water slope of the center of the highland is relatively flat and 8.5 per thousand, and the water slope of the area beside the highland can reach 33 per thousand. The groundwater seepage flow around the first relay horse tunnel also flows from the center of the tableland to the tableland.
According to the water pumping test results, the model has the total width and length of 800m, the width of 600m and the soil layer thickness of 200m, and the total number is generalized to 4 geological layers: updating the loess on the first layer, wherein the thickness is 20 m; updating the loess above the underground water level to be uniform with the thickness of 30 m; the loess aquifer of the renewal system in the third step is the 2 nd layer with the thickness of 60 m; fourthly, the lower middle renewal loess layer is the 3 rd layer and has the thickness of 90 m. The initial groundwater level is the boundary between the second and third layer (fig. 1).
The model mainly considers the condition of groundwater seepage in one year of construction period, the two sides of the tunnel are generalized to be constant water head boundaries, rainfall infiltration is considered to cause the rise of groundwater level, the tunnel is a zero-pressure boundary, the tunnel excavation is in a natural seepage state, and lining is not considered.
And step S2: coupling groundwater seepage model theory and stratum material model
Darcy's law originated from the pervasive analysis of saturated soils and was later generalized for application to pervasive analysis of unsaturated soils. The difference between the two states of soil is that the water permeability coefficient of unsaturated soil is not constant, but varies with the change of water content and pore water pressure. The basic equation of seepage theory is as follows:
wherein,
h total head kxPermeability coefficient in x direction
kyPermeability coefficient k in the y-directionzPermeability coefficient in z direction
Q flow rate theta volume water content
t is time
This equation means that the amount of change in the inflow and outflow of minute volumes at any position and at any time is the same as the amount of change in the volumetric water content. In short, the sum of the flow rate change in the x, y, z direction and the external flow rate is the same as the change in the volumetric water content.
At a certain elevation, the derivative function with respect to time is zero, becoming the following equation.
The finite element equations representing the fundamental equations using the Galerkin method of emphasizing residuals are as follows.
∫([B]T[C][B])dV{H}+∫(λ<N>T<N>)dV{H}t＝q∫(<N>T)dA (3)
Wherein,
[B] the method comprises the following steps The dynamic water gradient matrix [ C ]: matrix of cell permeability coefficients
{ H }: node head vector < N >: vector of shape function
q: unit flow λ ═ m on the unit sidewγw: choked flow term of unsteady flow
The finite element solution of the unsteady flow analysis is a function of time, and the integration of time can use a finite difference method. The finite element equation is expressed using a finite difference method as follows:
(ωΔt[K]+[M]){H1}＝Δt((1-ω){Q0}+ω{Q1})+([M]-(1-ω)Δt[K]){H0} (4)
wherein,
Δ t: time increment ω: a ratio between 0 and 1.
{H1}: water head at end of time increment H0}: head at the beginning of time increment
{Q1}: node flow at end of time increment { Q0}: node flow at the beginning of time increment
{ K }: cell characteristics matrix { M }: cell mass matrix
MIDAS/GTS uses a back-off difference method, where ω is 1.0. The omega of the finite element equation for unsteady flow analysis is 1.0, so
(Δt[K]+[M]){H1}＝Δt{Q1}+[M]{H0} (5)
As can be seen from equation (5), to calculate the head at the final stage of the time increment, the head at the initial stage must be known. In general, unsteady flow analysis must give initial conditions.
The formation is given parameters isotropically using a Moore-Coulomb model.
TABLE 1 soil parameter table
TABLE 2 soil non-linear parameter table
And step S3: three-dimensional model building and mesh generation
For three-dimensional meshing, a tetrahedral automatic solid meshing manner is adopted. The grid is divided into the following graphs, and after the division is completed, 196912 units are formed, and 183408 nodes are formed (in the graph of fig. 2).
In order to ensure the accuracy of the model operation process, the boundary conditions of the modeling process are mainly set from two aspects of a fixed flow boundary and a fixed head boundary of a pumping well, and the pumping well is arranged as shown in (figure 3)).
The initial water head is a constant water head, and the water level burial depth is 50 m. The node water head is mainly characterized in that a constant pressure head value for steady-state analysis and a variable pressure head value for transient analysis can be input by applying a seepage boundary condition function. The nodal head is used as a boundary condition for percolation/consolidation analysis (full coupling).
And step S4: analysis of groundwater seepage process
In order to calculate the response condition of different flow rates of the pumping well to the decline of the underground water level, three flow rate boundaries are selected for the pumping well at this time, and Q is 80m3/d，Q＝90m3/d，Q＝100m3And d. The pressure head drop and water level recovery under the three flow boundary conditions are shown in fig. 4 and 5.
From the above figure, it can be seen that under the three flow boundary conditions, the time for the water level to drop to a stable state is basically the same although the drop depth is different, which indicates that the change of the flow has little influence on the change of the formation precipitation speed.
The relationship between the three flow rates and the depth reduction shows that the maximum depth reduction and the flow rate of the pumping well are in a linear relationship, and the larger the flow rate of the pumping well is, the larger the depth reduction is (figure 6).
Depth reduction change of different permeability coefficients
Analyzing the response degree of different permeability coefficients to the pumping test depth reduction based on a three-dimensional numerical model. Setting a permeability coefficient of 0.1m3/d、0.2m3/d、0.3m3/d、0.4m3And d, continuing the three-dimensional numerical model simulation for each penetration respectively, wherein the simulation result is shown in figure 7.
According to the model result, the response degree of the permeability coefficient to the pumping test depth reduction is large, further, the fact that the pumping test based on the permeability coefficient needs to be tightly attached to the original stratum is further shown, and the most appropriate pumping test method is found to improve the efficiency.
The invention is not limited to the examples, and any equivalent changes to the technical solution of the invention by a person skilled in the art after reading the description of the invention are covered by the claims of the invention.
Claims (3)
1. Seepage simulation method based on soft plastic loess tunnel double-row type cluster well precipitation model is characterized in that:
the method comprises the following steps:
s1, taking the soft plastic loess as a test object, and establishing a three-dimensional soft plastic loess geologic body and dispersing grids according to the hydrogeological parameters and the engineering geological parameters;
s2, building a finite element grid element feature analysis and seepage model calculation format by taking loess as an elastic material;
s3, considering grid steady-state well models and underground water level changes under different precipitation conditions;
s4, solving the established underground water seepage and double-row precipitation well coupling model, and carrying out underground water level parameter sensitivity analysis on different water inflow and permeability coefficients.
2. The seepage simulation method based on the soft plastic loess tunnel double-row type group well precipitation model as claimed in claim 1, wherein:
step S2 includes the following steps:
the equilibrium equation in the basic equation used in the linear elasticity analysis of elastic materials is as follows:
Ku＝p (1)
the symbols in the formula are defined as follows: k is a structural rigidity matrix, u is a displacement vector, and p is a load vector or an unbalanced force vector;
taking an elastic material as a model base, the total strain generated under the action of load comprises elastic strain and plastic strain:
ε＝εe+εp (2)
wherein the symbols define ε as the total strain εeIs elastically strained, epsilonpIs plastic strain;
the stress is determined by the elastic part of the rate of change of strain, i.e. the standard plastic constitutive equation:
dσ＝De(dε-dεp)＝De(dε-dλa) (3)
in the formula, DeFor the elastic stiffness matrix, the slight strain change rates are as follows:
dσ＝Cdε-dλCa (4)
performing iterative computation by adopting a Newton-Laplacian method, and accelerating convergence rate by using a coordinated stiffness matrix:
and,
3. the seepage simulation method based on the soft plastic loess tunnel double-row type group well precipitation model as claimed in claim 2, wherein:
step S3 includes the following steps:
the basic equation of seepage theory is as follows:
the symbols in the formula are defined as follows: h is the total head, kxPermeability coefficient in x direction, kyPermeability coefficient in the y direction, kzThe permeability coefficient in the z direction is shown, Q is the flow, theta is the volume water content, and t is the time;
the equation means that the variation of inflow and outflow of a tiny volume at any position and at any time is the same as the variation of the volume water content, and the sum of the flow variation in the x, y and z directions and the external flow is the same as the variation of the volume water content;
at a certain elevation, the derivative function over time is zero, becoming the following equation:
the finite element equations representing the fundamental equations using the Galerkin method of emphasizing residuals are as follows:
∫([B]T[C][B])dV{H}+∫(λ<N>T<N>)dV{H}t＝q∫(<N>T)dA (10)
the symbols in the formula are defined as follows: [ B ]]Is a running water gradient matrix, [ C]Is the unit permeability coefficient matrix, { H } is the node head vector,<N>for the shape function vector, q is the unit flow λ ═ m on the unit sidewγwIs a choked flow term for unsteady flows,
is the head of water over time;
the finite element solution of the unsteady flow analysis is a function of time, and the integral of the time uses a finite difference method; the finite element equation is expressed using a finite difference method as follows:
(ωΔt[K]+[M]){H1}＝Δt((1-ω){Q0}+ω{Q1})+([M]-(1-ω)Δt[K]){H0} (11)
the symbols in the formula are defined as follows: Δ t is the time increment, ω: ratio between 0 and 1, { H1Water head at the end of time increment, { H }0Water head at the beginning of time increment, { Q }1{ Q } is the node flow at the end of the time increment0The flow rate of a node at the beginning of time increment is defined as { K } unit characteristic matrix, and the quality matrix of the unit is defined as { M };
the MIDAS/GTS uses a back-off difference method, and omega of the method is 1.0; the omega of the finite element equation for unsteady flow analysis is 1.0, so
(Δt[K]+[M]){H1}＝Δt{Q1}+[M]{H0} (12)。
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113866066A (en) * | 2021-10-26 | 2021-12-31 | 贵州乌江水电开发有限责任公司东风发电厂 | Three-dimensional visual hydropower station underground powerhouse hole seepage monitoring method and system |
| CN116522818A (en) * | 2023-05-09 | 2023-08-01 | 中国水利水电科学研究院 | Method for simulating water level in arid region under condition of high-gradient terrain |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112129681A (en) * | 2020-09-02 | 2020-12-25 | 中铁第一勘察设计院集团有限公司 | Method for acquiring change rule of water content of water-rich soft plastic loess tunnel under seepage effect |
-
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Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112129681A (en) * | 2020-09-02 | 2020-12-25 | 中铁第一勘察设计院集团有限公司 | Method for acquiring change rule of water content of water-rich soft plastic loess tunnel under seepage effect |
Non-Patent Citations (4)
| Title |
|---|
| 周洪波 等: "弹性和弹塑性有限元在溪洛渡水电站坝区地应力反演中的应用", 《长江科学院院报》, pages 63 - 67 * |
| 康婷 等: "黄土潜水层深井降水三维有限元模拟研究", 《西北农林科技大学学报(自然科学版)》, no. 04, pages 139 - 142 * |
| 张晓宇;: "董志塬地区富水黄土隧道渗流分析研究", 《铁道建筑技术》, pages 38 - 43 * |
| 王峰 等: "三维基坑开挖阶段地下水渗流分析", 《低温建筑技术》, no. 05, pages 96 - 98 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113866066A (en) * | 2021-10-26 | 2021-12-31 | 贵州乌江水电开发有限责任公司东风发电厂 | Three-dimensional visual hydropower station underground powerhouse hole seepage monitoring method and system |
| CN113866066B (en) * | 2021-10-26 | 2023-11-03 | 贵州乌江水电开发有限责任公司东风发电厂 | Three-dimensional visual hydropower station underground powerhouse chamber water seepage monitoring method and system |
| CN116522818A (en) * | 2023-05-09 | 2023-08-01 | 中国水利水电科学研究院 | Method for simulating water level in arid region under condition of high-gradient terrain |
| CN116522818B (en) * | 2023-05-09 | 2023-12-19 | 中国水利水电科学研究院 | Method for simulating water level in arid region under condition of high-gradient terrain |
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