Anti-sliding stability control method under working condition of sudden two-way water level drop of plain reservoir partition dam

Abstract

The invention relates to the technical field of reservoir structure safety control in water conservancy projects, in particular to an anti-sliding stability control method under the working condition of two-way sudden water level drop of a plain reservoir partition dam, which comprises the following steps: S1, working condition initialization and boundary condition definition; s2, carrying out seepage-stress coupling analysis; s3, solving an anti-sliding stability coefficient; s4, performing multi-objective optimization on the structural parameters; s5, verifying the efficiency of the waterproof and drainage system; s6, construction parameter simulation: fitting a soil material dry density-water content relationship through compaction test data, and determining an optimal construction water content and compaction degree parameter; and S7, performing dynamic early warning in an operation period. The anti-slip stability coefficient is accurately solved by constructing the seepage-stress bidirectional coupling analysis model and combining the strip division method, the internal mechanical response and potential slip crack surface characteristics of the dam body under the working condition of bidirectional sudden water level drop can be accurately captured, the anti-slip stability evaluation error is reduced, and a reliable quantitative basis is provided for safety management and control of the partition dam.

Description

Anti-sliding stability control method for sudden bidirectional water level drop in plain reservoir dam Technical Field

[0001] This invention relates to the field of reservoir structure safety control technology in water conservancy projects, and in particular to the anti-sliding stability control method under the condition of sudden drop in water level in both directions of the dam of a plain reservoir. Background Technology

[0002] In large-scale water conservancy projects such as the South-to-North Water Diversion Project, plain reservoirs often expand to enhance their storage capacity. In this case, it is necessary to convert part of the original reservoir dam into a partition dam to separate the new and old reservoir areas, so as to meet the needs of independent operation or joint scheduling of the two reservoir areas.

[0003] Unlike conventional reservoir dams, this type of diversion dam needs to withstand bidirectional water-retaining loads for a long time. In actual operation, it may face extreme conditions where one side of the reservoir maintains a high water level while the other side experiences a sudden drop in water level. For example, when the diversion dam needs to maintain a high design water level on the side of the old reservoir in the first phase while the water level on the side of the new reservoir in the second phase drops from a high level to a low level, the water pressure difference on both sides of the diversion dam changes drastically under this condition, which can easily lead to insufficient anti-sliding stability coefficient of the newly added dam slope, directly threatening the safety of the dam body.

[0004] Traditional design methods for diversion dams in plain reservoirs often refer to the unidirectional water-retaining conditions or bidirectional water level difference stability conditions of conventional cofferdams for parameter setting. On the one hand, the dam body cross-sectional parameters (such as dam crest width and dam slope) adopt a uniform standard design, without considering the weakening effect of the dam slope anti-sliding force caused by the change in the seepage field on the side of sudden water level drop. On the other hand, the dam crest drainage system is simple in design, often using conventional slope ratio drainage, which makes the diversion dam prone to having an anti-sliding stability coefficient lower than the standard requirements when the bidirectional water level drops sharply (SL274-2001 "Design Code for Rolled Earth-Rock Dams" requires that the anti-sliding stability safety factor of a Class 3 dam be no less than 1.25).

[0005] For example, patent document CN201810404375.2 discloses a method for assessing the anti-sliding stability of a dam slope at a bend in a reservoir dam. This method mainly involves evaluating the slope using a spatial volume cut at a unit angle, calculating the moment balance of soil strips at a unit angle using slice division, thereby deriving the anti-sliding stability safety factor at the bend, and assessing the anti-sliding stability of the inner and outer slopes at the dam bend. This method simplifies the three-dimensional spatial problem into an axisymmetric two-dimensional planar problem.

[0006] As can be seen from the above description, it has the following drawbacks in practical applications:

[0007] First, the aforementioned patents target the conventional stable working conditions at the bend of the reservoir dam, and only solve the problem of anti-sliding assessment of the local bend section of the dam. They have poor adaptability to working conditions and cannot cope with the problem of dam body stress imbalance caused by rapid changes in water level between the two reservoirs.

[0008] Second, when the water level of the dam drops sharply in both directions, the seepage field and stress field inside the dam body are distributed in three dimensions (such as increased lateral seepage on the side of the dam body where the water level drops sharply and stress concentration in the dam foundation). The method of the above patent is prone to causing the evaluation results to deviate significantly from the actual working conditions, and cannot provide a basis for targeted parameter design for the anti-sliding stability control of the dam.

[0009] Therefore, it is necessary to design a method to achieve precise and stable anti-sliding control for sudden drops in water level in both directions of a dam in a plain reservoir. Summary of the Invention

[0010] To solve one of the aforementioned technical problems, the present invention employs the following technical solution: a method for anti-sliding stability control under the condition of sudden bidirectional water level drop in a plain reservoir dam, comprising the following steps:

[0011] S1. Initialization of operating conditions and definition of boundary conditions: Establish a mathematical model to quantify the asymmetric boundary between the constant water level of the old reservoir and the dynamic sudden drop of the new reservoir, and output the water level-time history curve and key operating condition parameters.

[0012] S2. Seepage-stress coupling analysis: Based on finite element theory and Biot's consolidation equation, calculate the pore water pressure and effective stress distribution in the dam body, and output the pore water pressure field, stress field and potential slip surface location.

[0013] S3. Solution of anti-sliding stability coefficient: The most dangerous slip surface is searched by the slice method, and the anti-sliding stability coefficient is calculated by combining the soil strip stress analysis. The coefficient value and slip surface characteristics are output.

[0014] S4. Multi-objective optimization of structural parameters: Construct a safety-cost dual-objective optimization model to solve for the optimal dam crest width, dam slope gradient, and reinforcement parameters that satisfy stability constraints;

[0015] S5. Verification of Drainage and Waterproofing System Effectiveness: Calculate drainage capacity based on Darcy's Law, verify the synergistic effectiveness of drainage and waterproofing structures by comparing seepage flow, and output the infiltration line and seepage flow analysis results;

[0016] S6. Construction parameter simulation: By fitting the dry density-moisture content relationship of soil through compaction test data, the optimal construction moisture content and compaction degree parameters are determined;

[0017] S7. Dynamic early warning during operation: Integrate dam settlement and displacement monitoring data, calculate early warning index and dynamically adjust the rate of water level drop, and output early warning and adjustment suggestions.

[0018] Based on any of the above technical solutions, the following optimization is made: In step S1, the process of sudden drop in water level in the new reservoir area is modeled by a piecewise function, and formula (1) is as follows: ;

[0019] Where H(t) is the new reservoir water level at time t, H0 is the initial water level, and H t Let v be the target water level, v be the rate of drop (m / d), and T be the duration of the drop; the parameter values ​​should satisfy 0.3≤v≤0.7.

[0020] Based on any of the above technical solutions, the following optimization is made: In step S2, the seepage-stress coupling analysis adopts Biot's consolidation theory, and its two-dimensional core control formulas (2) and (3) are as follows: ; ;

[0021] Where u is the pore water pressure, k ij Let ε be the permeability tensor. v Let {δ} be the volumetric strain rate, [K] and [C] be the stiffness matrix and damping matrix, respectively, {δ} be the displacement vector, {Fu} be the equivalent nodal force of pore water pressure, and {R} be the external load vector.

[0022] Based on any of the above technical solutions, the following optimization is made: In step S3, the anti-skid stability coefficient is calculated using the slice method, and its formula (4) is as follows: ;

[0023] Where n is the number of soil strips, W j Let be the self-weight of the j-th soil strip, α be the dip angle of the sliding surface, and u be the self-weight of the j-th soil strip. j φ represents the pore water pressure corresponding to the soil strip, b represents the width of the soil strip, and φ′ and c′ represent the effective shear strength parameters of the soil.

[0024] Based on any of the above technical solutions, the further optimization is as follows: In step S4, the structural parameter optimization is transformed into a constrained nonlinear programming problem, as shown in formula (5) below: ;

[0025] Where X = [B, β, n] are the optimization variables (dam crest width B, dam slope angle β, number of reinforcement layers n), C 体积 C 加筋 These are the dam embankment cost and reinforcement material cost functions, respectively, where λ is the safety factor weighting factor, and F... s This is the anti-skid stability coefficient.

[0026] Based on any of the above technical solutions, the following optimization is made: In step S5, the flow rate of a single drain pipe is calculated using Darcy's law, as shown in formula (6) below: ;

[0027] Where q is the flow rate of a single pipe, k is the permeability coefficient of the drainage pipe, i is the hydraulic gradient, and A is the effective water passage area of ​​the drainage pipe.

[0028] Based on any of the above technical solutions, the following optimization is made: In step S6, the relationship between the dry density and moisture content of the soil is fitted by a quadratic curve, and the formula (7) is as follows: ;

[0029] Where, p d denoted as dry density, w as moisture content (%), and a, b, and c as fitting coefficients;

[0030] optimum moisture content .

[0031] Based on any of the above technical solutions, the following optimization is made: In step S7, the early warning index I during the operation period adopts a weighted maximum value model, and the formula (8) is as follows: ;

[0032] Where Δs and Δh are the measured settlement and horizontal displacement increments, respectively, Δ Sallow Δ hallow To standardize the allowed values, w s w h The weighting coefficient (values ​​0.6 and 0.4) is used; an early warning is triggered when I > 1.0.

[0033] Based on any of the above technical solutions, a further optimization is made: the permeability coefficient tensor in step S2 is valued according to the soil anisotropy theory: horizontal permeability coefficient k xx =k yy =k0, vertical permeability coefficient k zz =0.3k0, where k0 is taken from the typical permeability coefficient value of the corresponding soil type in the SL274-2001 standard.

[0034] Based on any of the above technical solutions, the following further optimization is made: the constraint range of the optimization variables in step S4 is: dam crest width 4m≤B≤10m, dam slope angle 20°≤β≤30°, and number of reinforcement layers 2≤n≤5.

[0035] Based on any of the above technical solutions, the following optimization is made: the formula (9) for adjusting the rate of water level drop after the early warning in step S7 is as follows: ;

[0036] Among them, V old For the original rate of sudden drop, V new The adjusted rate must satisfy V. new ≥0.1m / d.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0038] 1. This invention, by constructing a two-way coupled analysis model of seepage and stress and combining it with the slice method to accurately solve the anti-sliding stability coefficient, breaks through the limitation of traditional single-field analysis that ignores the interaction between pore water pressure and stress. It can accurately capture the internal mechanical response and potential slip surface characteristics of the dam body under the condition of sudden drop in water level in both directions, reduce the error of anti-sliding stability assessment, and provide a reliable quantitative basis for the safety management of the dam.

[0039] 2. This invention establishes a dual-objective optimization model of safety and cost and correlates it with construction parameter simulation. By optimizing core parameters such as dam crest width, dam slope angle and number of reinforcement layers, and determining the optimal moisture content and compaction degree based on quadratic curve fitting, it avoids the problems of excessive reinforcement leading to soaring costs or simplified design causing safety hazards in traditional design, and improves the construction quality of the dam body, achieving synergistic optimization of economy and safety.

[0040] 3. This invention constructs a closed-loop management and control mechanism for the entire life cycle of design, construction, and operation. During the operation period, the traditional passive risk management is transformed into proactive and precise control through a settlement-displacement dual-index weighted early warning model and a dynamic adjustment algorithm for the rate of sudden drop in water level. Rate optimization can be completed within 12 hours after the early warning, effectively reducing the risk of slippage caused by sudden drop in water level. At the same time, the modular design is adaptable to different soil types and reservoir sizes, and its versatility is greatly improved compared to the traditional single-condition method. Attached Figure Description

[0041] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or components are generally identified by similar reference numerals. In the drawings, the elements or components are not necessarily drawn to scale.

[0042] Figure 1 is a water level time curve generated in step S1 of the present invention.

[0043] Figure 2 is a pore water pressure cloud map generated in step S2 of the present invention.

[0044] Figure 3 is an effective stress distribution diagram generated in step S2 of the present invention.

[0045] Figure 4 is a diagram of the most dangerous slip surface in step S3 of the present invention.

[0046] Figure 5 is an optimized convergence curve in step S4 of the present invention.

[0047] Figure 6 is a comparison chart of drainage efficiency generated in step S5 of the present invention.

[0048] Figure 7 is a compaction test curve in step S6 of the present invention.

[0049] Figure 8 is a graph showing the change of the early warning index during the operation period in step S7 of the present invention.

[0050] Figure 9 is a diagram showing the dynamic adjustment of the water level drop rate in step S7 of the present invention. Detailed Implementation

[0051] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of the present invention and are therefore merely examples, not intended to limit the scope of protection of the present invention. Related figures and diagrams of the present invention are shown in Figures 1-9.

[0052] Example 1: A method for anti-sliding stability control under the condition of sudden drop in water level in both directions of a dam in a plain reservoir, including the following steps:

[0053] S1. Initialization of operating conditions and definition of boundary conditions: Establish a mathematical model to quantify the asymmetric boundary between the constant water level of the old reservoir and the dynamic sudden drop of the new reservoir, and output the water level-time history curve and key operating condition parameters.

[0054] S2. Seepage-stress coupling analysis: Based on finite element theory and Biot's consolidation equation, calculate the pore water pressure and effective stress distribution in the dam body, and output the pore water pressure field, stress field and potential slip surface location.

[0055] S3. Solution of anti-sliding stability coefficient: The most dangerous slip surface is searched by the slice method, and the anti-sliding stability coefficient is calculated by combining the soil strip stress analysis. The coefficient value and slip surface characteristics are output.

[0056] S4. Multi-objective optimization of structural parameters: Construct a safety-cost dual-objective optimization model to solve for the optimal dam crest width, dam slope gradient, and reinforcement parameters that satisfy stability constraints;

[0057] S5. Verification of Drainage and Waterproofing System Effectiveness: Calculate drainage capacity based on Darcy's Law, verify the synergistic effectiveness of drainage and waterproofing structures by comparing seepage flow, and output the infiltration line and seepage flow analysis results;

[0058] S6. Construction parameter simulation: By fitting the dry density-moisture content relationship of soil through compaction test data, the optimal construction moisture content and compaction degree parameters are determined;

[0059] S7. Dynamic early warning during operation: Integrate dam settlement and displacement monitoring data, calculate early warning index and dynamically adjust the rate of water level drop, and output early warning and adjustment suggestions.

[0060] It needs to be explained that: ① Multiphysics coupling specifically refers to the bidirectional coupling of the seepage field and the stress field. The coupling mechanism is based on Biot's consolidation theory and is implemented through finite element software (such as ANSYS, COMSOL) or numerical calculation methods (such as the pdepe function); ② The execution logic of the modular steps is "the output of the preceding step is used as the input of the following step". The quantitative results of each step include specific parameter dimensions (such as the time interval of 0.1d for the water level-time curve and the mesh density of the stress field of 50×30); ③ The specific form of the visualization analysis results (such as pore water pressure cloud map and stability coefficient convergence curve) has been clarified in the subsequent technical solutions. Technical personnel in the relevant technical field can implement it through conventional numerical calculation tools (such as MATLAB, Python).

[0061] It should be noted that this method first clarifies the asymmetric water level boundary (constant old reservoir + sudden drop in new reservoir) through operational condition initialization, solving the problem of traditional methods ignoring the two-way water level difference; then, it obtains the internal mechanical response of the dam body through seepage-stress coupling analysis, providing accurate input for the calculation of the stability coefficient; subsequently, it balances safety and cost through multi-objective optimization, avoiding over-design or insufficient safety caused by single-objective optimization; finally, it achieves dynamic control through operational early warning, adapting to the real-time risks during the sudden drop in water level.

[0062] Compared with existing technologies, its advantages are: modular design can flexibly adapt to the size and soil properties of different plain reservoir dams, and has strong versatility; multi-physics coupling improves the accuracy of mechanical response calculation and avoids the error of single-field analysis; dynamic feedback mechanism realizes anti-sliding stability control throughout the entire life cycle of design-construction-operation, covering the dynamic adjustment link during operation that is not covered by traditional methods.

[0063] It is also worth highlighting that this optimization scheme breaks through the limitations of traditional single-water-level conditions. By using asymmetric boundary quantization, it achieves accurate simulation of bidirectional water level drops, solving the problem of stability calculation distortion caused by water level differences on both sides of the dam in plain reservoirs. The independent output characteristics of modular steps support cross-platform adaptation and can be directly connected to engineering design software and numerical simulation tools to achieve seamless integration of design-simulation-construction. The multi-objective optimization model introduces a weighted balancing mechanism of cost function and safety factor, avoiding the extremes of traditional optimization that prioritize safety over cost or vice versa, and achieving synergistic optimization of engineering economy and safety. The linkage mechanism of dynamic early warning and rate adjustment during operation transforms passive protection into active control, which can reduce the risk of anti-sliding stability in real time without affecting the normal operation of the reservoir, breaking through the rigid constraints of traditional fixed rate drops.

[0064] Based on any of the above technical solutions, the following optimization is made: In step S1, the process of sudden drop in water level in the new reservoir area is modeled by a piecewise function, and formula (1) is as follows: ;

[0065] Where H(t) is the new reservoir water level at time t, H0 is the initial water level, and H t Let v be the target water level, v be the rate of drop (m / d), and T be the duration of the drop; the parameter values ​​should satisfy 0.3≤v≤0.7.

[0066] It should be explained that the calculation logic for the sudden drop duration T in this scheme is as follows: To ensure the continuity and rationality of the piecewise function, those skilled in the art can directly calculate based on the actual water level difference and the selected rate; parameters H0, H t The value is determined based on the design water level of the plain reservoir (such as the normal storage water level and the dead water level) and combined with the engineering survey data. The example value range is 10-30m (which conforms to the common water level range of plain reservoirs); ③ The specific source of the rate constraint 0.3≤v≤0.7 is the SL274-2001 standard to ensure the standardization and feasibility of the parameter values.

[0067] It should be noted that the working principle of this optimization scheme is to accurately characterize the three stages of a sudden drop in water level using a piecewise function: ① Before the sudden drop (t < 0): the water level remains at the initial value H0, simulating the stable operation of the reservoir; ② During the sudden drop (0 ≤ t ≤ T): the water level drops linearly, and the rate v meets the specified limits, simulating the water level change caused by actual drainage or precipitation; ③ After the sudden drop (t > T): the water level stabilizes at the target value H0. t This simulates a new stable state for the reservoir.

[0068] Compared to the traditional linear drop model, its advantages are: segmented modeling closely matches the phased characteristics of actual water level changes, avoiding the shortcomings of a single model in distinguishing the stable state before and after a sudden drop; standardized constraints on the rate parameter ensure the engineering applicability of the model, avoiding stability calculation deviations caused by improper rate values; and the function form is concise and can be directly implemented through programming software (such as MATLAB and Excel), lowering the threshold for engineering applications.

[0069] Its core function is to provide accurate boundary conditions for subsequent seepage-stress coupling analysis, ensuring the accuracy of subsequent mechanical response calculations.

[0070] It is also worth highlighting that the nonlinear characterization capability of the piecewise function in this optimization scheme breaks through the limitations of traditional linear models. It can accurately adapt to the complex water level change process of stabilization before a sudden drop, linearity during the drop, and stabilization after the drop, thus improving the simulation accuracy of boundary conditions. The interval constraint design of the rate parameter not only meets the specifications but also reserves space for dynamic adjustment during the subsequent operation period, realizing the linkage between design-stage pre-setting and operation-stage optimization. The engineering definition of the function parameters ensures that all variables correspond to clear physical meanings and engineering parameters, and can be directly calibrated using reservoir monitoring data, avoiding the problem of the disconnect between pure theoretical models and actual engineering. The cross-scenario adaptability is achieved by adjusting H0, H...t The parameters such as v can be adapted to dams in plain reservoirs of different sizes and geological conditions, overcoming the limitations of traditional models that require a single model for each reservoir.

[0071] Based on any of the above technical solutions, the following optimization is made: In step S2, the seepage-stress coupling analysis adopts Biot's consolidation theory, and its two-dimensional core control formulas (2) and (3) are as follows: ; ;

[0072] Where u is the pore water pressure, k ij Let ε be the permeability tensor. v Let {δ} be the volumetric strain rate, [K] and [C] be the stiffness matrix and damping matrix, respectively, {δ} be the displacement vector, {Fu} be the equivalent nodal force of pore water pressure, and {R} be the external load vector.

[0073] It needs to be explained that the boundary conditions for solving the governing equations are as follows: the seepage boundary is the water level on the new reservoir side changing according to a piecewise function of step S1, the water level on the old reservoir side is constant, and the dam bottom is an impermeable boundary; the stress boundary is the free boundary at the dam crest, the fixed constraint at the dam bottom, and the horizontal constraints on both sides; the permeability tensor k... ij Specific methods for determining the values: Horizontal and vertical permeability coefficients are taken from typical values ​​for the corresponding soil types in the SL274-2001 standard; Methods for constructing matrix parameters: The stiffness matrix [K] is obtained through finite element integration based on soil constitutive relations (such as the Mohr-Coulomb model), and the damping matrix [C] uses Rayleigh damping. The external load vector {R} includes the soil's self-weight, water pressure, etc.

[0074] It should be noted that this optimization scheme is based on Biot consolidation theory to realize the bidirectional coupling of seepage field and stress field: the seepage field formula (2) describes the spatiotemporal distribution law of pore water pressure. Considering the anisotropic permeability characteristics of soil, the change of pore water pressure will be fed back to the stress field through volumetric strain rate; formula (3) describes the stress-displacement response of dam body. Pore water pressure participates in stress balance through equivalent nodal force. The stress change will lead to the change of soil permeability coefficient, forming a coupling closed loop.

[0075] Compared to traditional methods that calculate seepage and stress fields separately, this approach offers several advantages: Two-way coupling accurately reflects the intrinsic relationship between pore water pressure dissipation, effective stress increase, and dam deformation during a sudden drop in water level, avoiding stress calculation errors caused by single-field analysis; the introduction of a permeability tensor considers soil anisotropy, aligning with the actual mechanical properties of dam materials in plain reservoirs (horizontal permeability is typically greater than vertical permeability); and the mature finite element method for solving the governing equations allows for rapid implementation using existing engineering software, balancing accuracy and efficiency. This provides precise pore water pressure and stress distribution data for calculating the anti-sliding stability coefficient in step S3, offering a reliable basis for subsequent optimization design.

[0076] It is also worth highlighting that the two-way coupling mechanism of this optimization scheme breaks through the limitations of the traditional one-way coupling (only seepage affects stress, without considering the effect of stress on seepage). It can accurately capture the hysteresis effect of the mechanical response inside the dam body during a sudden drop in water level, improving the accuracy of stability coefficient calculation. The anisotropic design of the permeability coefficient tensor solves the problem that the traditional isotropic assumption does not match the actual soil properties, avoiding the distortion of pore water pressure distribution caused by the simplification of permeability characteristics. The modular solution logic of the control formula can independently adjust seepage or stress parameters, adapting to dams of different soil types (such as loam and sandy loam), enhancing the versatility of the scheme. The introduction of equivalent nodal forces quantifies the influence of pore water pressure on structural stress as nodal loads, simplifying the solution difficulty of the coupling formula while ensuring calculation accuracy, breaking through the bottleneck of the complexity of solving traditional coupling equations and the difficulty in engineering applications.

[0077] Example 2: Compared with Example 1, this example also includes the following technical features:

[0078] Based on any of the above technical solutions, the following optimization is made: In step S3, the anti-skid stability coefficient is calculated using the slice method, and its formula (4) is as follows: ;

[0079] Where n is the number of soil strips, W j Let be the self-weight of the j-th soil strip, α be the dip angle of the sliding surface, and u be the self-weight of the j-th soil strip. j φ represents the pore water pressure corresponding to the soil strip, b represents the width of the soil strip, and φ′ and c′ represent the effective shear strength parameters of the soil.

[0080] It should be explained that the value of the number of soil strips n is determined based on the horizontal length L of the dam body, with n=20-50 (soil strip width b=L / n), preferably 2-5m, to ensure a balance between calculation accuracy and efficiency; the self-weight W of the soil strips... j The calculation logic: ( Unit weight of soil, in kN / m³; (where is the average height of the j-th soil strip, in meters; 1 is the calculation depth, in meters). Linear distribution based on location according to the cross-sectional shape of the dam body (e.g., trapezoidal); pore water pressure u j The values ​​of the soil surface are determined by taking the pore water pressure value at the midpoint of the soil strip from the seepage field calculation results in step S2. If the seepage field is a discrete grid, linear interpolation is used. The effective shear strength parameters φ′ and c′ are determined by indoor triaxial shear tests. If no test data is available, the typical values ​​for the corresponding soil type in the SL274-2001 standard are referenced. The search method for the most dangerous slip surface is a traversal search method. The slip surface inclination angle α ranges from 5° to 30°, with a step size of 1°. The values ​​corresponding to each inclination angle are calculated. The minimum value of α corresponds to the dip angle of the most dangerous slip surface.

[0081] It should be noted that this optimization scheme is based on the slice method of the simplified Bishop method. By dividing the dam body into several soil strips along the slip surface, the anti-sliding force and sliding force of each soil strip are calculated separately, and the anti-sliding stability coefficient is obtained by summing and comparing the values. The anti-sliding force consists of two parts: the frictional force generated by the effective normal force (the normal component of the soil strip's self-weight minus the pore water pressure), and the cohesive anti-sliding force generated by the soil cohesion. The sliding force is the tangential component of the soil strip's self-weight, directed downwards along the slip surface. When the stability coefficient is greater than 1.25, it meets the requirements of the specification (SL274-2001). If it is less than this value, it needs to be optimized and adjusted through step S4.

[0082] Compared with the traditional slice method, its advantages are: the introduction of quantitative calculation of pore water pressure avoids the overestimation of anti-slip force caused by the traditional method ignoring pore water pressure; the calculation of cohesion anti-slip force takes into account the length of the slip surface, which is close to the tilt characteristics of the actual slip surface and improves the calculation accuracy; the traversal search method of the most dangerous slip surface ensures that the global minimum stability coefficient is found and avoids the safety hazards caused by local optimal solutions.

[0083] Its core function is to quantify the anti-sliding stability of the dam under the condition of a sudden drop in water level, so as to provide a basis for judgment for subsequent structural optimization.

[0084] It is also worth highlighting that this optimization scheme precisely couples pore water pressure with soil strip stress, breaking through the limitations of the traditional slice method's assumption of average pore water pressure, and realizing differentiated calculation of pore water pressure for each soil strip, thereby improving the accuracy of stability coefficient calculation; the traversal search mechanism for slip surface inclination angle solves the problem of omission of the most dangerous slip surface caused by the traditional fixed slip surface inclination angle calculation, ensuring the comprehensiveness of stability assessment; the linear distribution method of soil strip height is adapted to the trapezoidal cross-sectional shape of plain reservoir dams, avoiding the problem of discrepancies between the traditional assumption of equal-height soil strips and the actual cross-section.

[0085] Based on any of the above technical solutions, the further optimization is as follows: In step S4, the structural parameter optimization is transformed into a constrained nonlinear programming problem, as shown in formula (5) below: ;

[0086] Where X = [B, β, n] are the optimization variables (dam crest width B, dam slope angle β, number of reinforcement layers n), C 体积 C 加筋 These are the dam embankment cost and reinforcement material cost functions, respectively, where λ is the safety factor weighting factor, and F... s This is the anti-skid stability coefficient.

[0087] It needs to be explained what the specific form of the cost function is: ; Unit weight of compacted soil, in kN / m³; The volume of the dam is in m³. The price is the unit price for excavation and transportation of earthwork, expressed in yuan / kN.

[0088] ; The height of the dam is in meters (m). The length of the dam is in meters (m). ; The price per unit area for reinforcement materials is RMB / m².

[0089] The weighting factor λ is determined based on the following criteria: λ = 100-200, adjusted according to the safety level of the project (200 for Class I dams, 150 for Class II dams, and 100 for Class III dams), to ensure that the weight of the safety factor in the objective function is appropriate to the importance of the project.

[0090] Algorithm selection: Interior point method (fmincon function) is used. Initial value X0 = [6, 25, 3], iteration precision 10. -6 The maximum number of iterations is 15,000; the constraint range is determined based on the dam crest width of 4m < B < 10m (to meet the needs of flood control vehicle passage) and the dam slope angle of 20°. <30° (balancing stability and floor space), number of reinforcement layers 2 < n < 5 (matching the tensile strength limit of the reinforcement material).

[0091] It should be noted that this optimization scheme constructs a safety-cost dual-objective optimization model, and achieves the optimal configuration of structural parameters through nonlinear programming: minimizing the total cost and maximizing the safety factor. The priority of the two is balanced by weighting factors to avoid the extremes of single-objective optimization. The constraints ensure that the optimization results meet the safety requirements of the specifications and the actual feasibility of the project. The optimization variables selected are the dam crest width, dam slope angle, and number of reinforcement layers, which cover the core design parameters of the dam structure and can significantly affect the anti-sliding stability and project cost.

[0092] Compared to traditional optimization methods, its advantages are: dual-objective coupled optimization, breaking through the traditional sequential design mode of prioritizing safety before considering cost, and achieving synergistic optimization of both; quantitative modeling of the cost function, based on engineering unit price and volume / area calculation, avoiding cost estimation bias caused by traditional qualitative analysis; and high solution efficiency of the interior point method, capable of handling constrained nonlinear problems, ensuring the global optimality of the optimization results. Under the premise of meeting anti-sliding stability requirements, it minimizes engineering costs and improves the economic efficiency of dam design.

[0093] It is also worth highlighting that the dynamic adjustment mechanism of the weight factors in this optimization scheme is adapted to plain reservoir dams of different safety levels, achieving a personalized balance between safety and cost; through the reasonable configuration of reinforcement materials, the amount of dam fill is reduced (cost reduction) while ensuring stability and safety, achieving the dual benefits of material optimization and structural optimization; all parameter ranges are based on actual engineering needs (such as flood control and passage, land area), avoiding the problem that purely theoretical optimization results cannot be implemented; the seamless connection between the optimization model and the calculation of the preceding stability coefficient, with the quantitative results of the preceding steps directly used as the input of the optimization model, ensures the continuity and accuracy of the optimization process, breaking through the bottleneck of the traditional design-optimization-verification disconnect.

[0094] Based on any of the above technical solutions, the following optimization is made: In step S5, the flow rate of a single drain pipe is calculated using Darcy's law, as shown in formula (6) below: ;

[0095] Where q is the flow rate of a single pipe, k is the permeability coefficient of the drainage pipe, i is the hydraulic gradient, and A is the effective water passage area of ​​the drainage pipe.

[0096] It should be explained that the value of the drainage pipe permeability coefficient k is based on the typical permeability coefficient of plastic drainage boards or permeable hoses, k=10. -4 -10 -3 m / s (compliant with the "Technical Specification for Application of Geosynthetics"); Calculation method of hydraulic gradient: i=(H 上 -H 下 ) / L 排水 H 上 H represents the water level at the inlet of the drainage pipe. 下 L is the water level on the outlet side. 排水The effective length of the drainage pipe is taken as 1 / 2 of the horizontal length of the dam. The calculation logic for the effective water passage area A is: A=πd² / 4 (d is the inner diameter of the drainage pipe), and d=50~100mm is recommended (common engineering specifications). The calculation method for the total seepage flow is: Q=Nq (N is the number of drainage pipes, which are evenly distributed according to the length of the dam, with a spacing of 2-5m). The comparison logic for effectiveness verification is: calculate the total seepage flow of the system without drainage (only the dam body itself seeps) and the system with drainage (dam body + drainage pipes) respectively, and verify the drainage effectiveness by the change in the burial depth of the phreatic line (an increase in the burial depth of the phreatic line ≥0.5m is considered effective).

[0097] It should be noted that this optimization scheme is based on Darcy's law to quantify the drainage capacity of the drainage pipe. By comparing the seepage effect with and without the drainage system, the synergistic effectiveness of the drainage and waterproofing structure is verified: Darcy's law applies to laminar infiltration of porous media, and the flow calculation of the drainage pipe, as an artificial infiltration channel, conforms to this law; the calculation of the hydraulic gradient takes into account the actual layout length of the drainage pipe and the difference between the inlet and outlet water levels, which is consistent with the actual project; the logic of the effectiveness verification is that the drainage system reduces pore water pressure and raises the phreatic line, thereby improving the anti-sliding stability of the dam body (reduced pore water pressure can increase effective stress and improve shear strength).

[0098] Compared with traditional drainage performance verification methods, its advantages are: combining quantitative calculation with visual comparison to intuitively reflect the effect of the drainage system; parameter values ​​are based on commonly used engineering specifications and requirements to ensure the engineering applicability of the verification results; and the drainage system design can be optimized by adjusting parameters such as the number of drainage pipes, pipe diameter, and spacing to avoid problems of over-drainage or under-drainage.

[0099] Based on any of the above technical solutions, the following optimization is made: In step S6, the relationship between the dry density and moisture content of the soil is fitted by a quadratic curve, and the formula (7) is as follows: ;

[0100] Where, p d denoted as dry density, w as moisture content (%), and a, b, and c as fitting coefficients;

[0101] optimum moisture content .

[0102] It needs to be explained that the method for obtaining compaction test data is as follows: Heavy compaction tests were conducted according to the "Standard for Geotechnical Testing Methods" GB / T50123. Five groups of soil samples with different moisture contents were selected (recommended moisture content range 10%-18%). Each group of soil samples underwent three parallel tests, and the average dry density was taken as the test data. The method for determining the fitting coefficients a, b, and c was to use the least squares method to fit the test data, achieving a goodness of fit ≥0.9.5 (to ensure the reliability of the fitted curve). The method for verifying the optimum moisture content was as follows: [The text abruptly ends here, likely due to an incomplete sentence or missing information.] Three groups of moisture content were selected nearby ( -1% , A supplementary compaction test was conducted (+1%), and the moisture content corresponding to the maximum dry density was taken as the final optimum moisture content; determination of compaction parameters: ;in, The specification requires that the maximum dry density corresponds to the optimum moisture content. .

[0103] It should be noted that this optimization scheme is based on quadratic curve fitting of compaction test data to establish a quantitative relationship between soil dry density and moisture content, thereby determining the optimal construction parameters: the dry density of the soil changes with moisture content according to a quadratic curve (when the moisture content is below the optimal value, the dry density increases with increasing moisture content; when it is above the optimal value, the dry density decreases with increasing moisture content); the optimal moisture content... Let x be the x-coordinate of the vertex of the conic section, which can be obtained by differentiation. It can be quickly determined without trial and error.

[0104] Based on any of the above technical solutions, the following optimization is made: In step S7, the early warning index I during the operation period adopts a weighted maximum value model, and the formula (8) is as follows: ;

[0105] Where Δs and Δh are the measured settlement and horizontal displacement increments, respectively, Δ Sallow Δ hallow To standardize the allowed values, w s w h The weighting coefficient (values ​​0.6 and 0.4) is used; an early warning is triggered when I > 1.0.

[0106] It needs to be explained that the method for obtaining the measured increment is as follows: settlement gauges (such as fiber optic grating settlement gauges) are used to monitor the dam crest settlement, and displacement gauges (such as inclinometers) are used to monitor the horizontal displacement of the dam body. The monitoring frequency is once per day; it is the difference between the monitoring values ​​of the current day and the previous day; the basis for determining the allowable value according to the standard is: Δ Sallow =5mm / d, Δ hallow =3mm / d (refer to the "Technical Specification for Safety Monitoring of Earth-Rock Dams"). Reason for the weighting coefficient: The settlement increment has a greater impact on the stability of the dam (excessive settlement may lead to cracking of the dam body). =0.6, horizontal displacement increment weight =0.4, balancing the effects of both on stability.

[0107] The handling logic after the warning is as follows: When I > 1.0, adjust the rate of water level drop and increase the monitoring frequency to 4 times / day; when I ≤ 1.0, maintain the original rate of drop and monitoring frequency.

[0108] Based on any of the above technical solutions, a further optimization is made: the permeability coefficient tensor in step S2 is valued according to the soil anisotropy theory: horizontal permeability coefficient k xx =k yy =k0, vertical permeability coefficient k zz =0.3k0, where k0 is taken from the typical permeability coefficient value of the corresponding soil type in the SL274-2001 standard.

[0109] It needs to be explained that, according to the SL274-2001 standard, typical permeability coefficients are selected for different soil types. The application logic of the permeability coefficient tensor is as follows: In two-dimensional seepage-stress coupling analysis, only the permeability difference in the horizontal (x, y directions) and vertical (z direction) directions is considered, while the permeability coefficient in the shear direction (such as the xy direction) is ignored. This conforms to the actual permeability characteristics of the soil material for the dam of a plain reservoir (mainly manifested as the difference in the horizontal and vertical directions). If there is indoor permeability test data, it can be determined through experiments; if there is no test data, the typical value in the standard is directly adopted.

[0110] It should be noted that the soil material for the dam of a plain reservoir is usually compacted in layers, and the permeability coefficient in the horizontal direction is greater than that in the vertical direction (compaction causes soil particles to be arranged in the horizontal direction, resulting in better pore connectivity), which is consistent with the anisotropy theory.

[0111] Compared with the traditional isotropic permeability coefficient values, its advantages are: it conforms to the actual permeability characteristics of the soil, improves the calculation accuracy of pore water pressure distribution, and thus optimizes the subsequent stability coefficient calculation results; it standardizes the direct application of typical values, avoids the difficulty of obtaining values ​​when there is no experimental data, and enhances the versatility of the scheme.

[0112] Based on any of the above technical solutions, the following further optimization is made: the constraint range of the optimization variables in step S4 is: dam crest width 4m≤B≤10m, dam slope angle 20°≤β≤30°, and number of reinforcement layers 2≤n≤5.

[0113] It needs to be explained that the basis for the dam crest width constraint is as follows: B≥4 is to meet the passage requirements of flood control vehicles (the minimum passage width for flood control vehicles is 3.5m, with a 0.5m safety distance reserved); 4m≤B≤10m is to control the dam volume and project cost (excessive width leads to a surge in fill volume and a decrease in economic efficiency), while also avoiding increased construction difficulty due to an excessively wide dam crest.

[0114] The basis for dam slope angle constraints is as follows: β > 20° is to control the land area occupied by the dam (too small a slope angle will result in an excessively wide dam base, occupying too much land resources); β ≤ 30° is to ensure the stability of the dam slope (too large a slope angle will easily lead to dam slope sliding, and even with reinforcement materials, the slope angle should not exceed 30°, in accordance with the requirements of SL274-2001).

[0115] The basis for the constraint on the number of reinforcement layers is as follows: n≥2 is to ensure the reinforcement effect (the tensile strength of a single layer of reinforcement is limited and it is difficult to effectively improve the anti-slip stability); n≤5 is to control the reinforcement cost (too many layers lead to a surge in material costs and the marginal reduction of the synergistic effect between reinforcement layers), while avoiding the complexity of construction procedures caused by too many layers (reinforcement layers need to be compacted in layers with soil, and too many layers affect construction efficiency).

[0116] Based on any of the above technical solutions, the following optimization is made: the formula (9) for adjusting the rate of water level drop after the early warning in step S7 is as follows: ;

[0117] Among them, V old For the original rate of sudden drop, V new The adjusted rate must satisfy V. new ≥0.1m / d.

[0118] It needs to be explained that the logic behind adjusting the formula is as follows: the larger the warning index I, the higher the stability risk, and the greater the need to reduce the rate of sudden drop. Therefore, an inverse proportional relationship is used to achieve a dynamic match between risk and rate. Upper limit constraint. The basis for ≤0.3m / d: The SL274-2001 standard stipulates that the minimum allowable rate of sudden drop in water level in earth-rock dams is 0.3m / d (to avoid stability risks caused by excessively rapid drops). Even if I is small (lower risk), the adjusted rate should not exceed this limit; ③ Lower limit constraint The basis for ≥0.1m / d is to balance the efficiency of reservoir operation and avoid excessively long drainage cycles caused by excessively slow rates (such as drainage of plain reservoirs, which usually needs to be completed within 10-20 days). At the same time, a rate of 0.1m / d can effectively control stability risks. Based on the dynamic rate adjustment of the early warning index, the higher the risk, the greater the rate reduction, thus achieving precise control, improving the pertinence of risk response, and realizing closed-loop control of risk and rate.

[0119] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention. For those skilled in the art, any alternative improvements or transformations made to the implementation of the present invention fall within the protection scope of the present invention.

[0120] Any aspects of this invention not described in detail are well-known to those skilled in the art.

Claims

1. A method for anti-sliding stability control under the condition of sudden drop in water level in both directions of a dam in a plain reservoir, characterized in that, Includes the following steps: S1. Initialization of operating conditions and definition of boundary conditions: Establish a mathematical model to quantify the asymmetric boundary between the constant water level of the old reservoir and the dynamic sudden drop of the new reservoir, and output the water level-time history curve and key operating condition parameters. S2. Seepage-stress coupling analysis: Based on finite element theory and Biot's consolidation equation, calculate the pore water pressure and effective stress distribution of the dam body, and output the pore water pressure field, stress field and potential slip surface location; S3. Anti-sliding stability coefficient solution: Use the slice method to search for the most dangerous slip surface, and combine the soil strip stress analysis to calculate the anti-sliding stability coefficient, and output the coefficient value and slip surface characteristics. S4. Multi-objective optimization of structural parameters: Construct a safety-cost dual-objective optimization model to solve for the optimal dam crest width, dam slope, and reinforcement parameters that satisfy stability constraints; S5. Verification of drainage system effectiveness: Calculate drainage capacity based on Darcy's law, verify the synergistic effectiveness of drainage and drainage structures by comparing seepage flow, and output the phreatic line and seepage flow analysis results; S6. Simulation of construction parameters: Fit the dry density-moisture content relationship of soil material through compaction test data to determine the optimal construction moisture content and compaction parameters; S7. Dynamic early warning during operation: Integrate dam settlement and displacement monitoring data, calculate the early warning index, dynamically adjust the rate of water level drop, and output early warning and adjustment suggestions.

2. The anti-sliding stability control method for a plain reservoir under the condition of sudden drop in water level in both directions under the condition of bidirectional water level drop, as described in claim 1, is characterized in that, In step S1, the process of sudden drop in water level in the new reservoir area is modeled using a piecewise function, as shown in formula (1): Where H(t) is the new reservoir water level at time t, H0 is the initial water level, and H... t Let v be the target water level, v be the rate of drop (m / d), and T be the duration of the drop; the parameter values ​​should satisfy 0.3≤v≤0.

7.

3. The anti-sliding stability control method for a plain reservoir under the condition of sudden drop in water level in both directions under the condition of bidirectional water level drop, as described in claim 2, is characterized in that... In step S2, the seepage-stress coupling analysis adopts Biot's consolidation theory, and its two-dimensional core control formulas (2) and (3) are as follows: ； Where u is the pore water pressure, and k ij Let ε be the permeability tensor. v Let {δ} be the volumetric strain rate, [K] and [C] be the stiffness matrix and damping matrix, respectively, {δ} be the displacement vector, {Fu} be the equivalent nodal force of pore water pressure, and {R} be the external load vector.

4. The anti-sliding stability control method for a plain reservoir dam under the condition of sudden drop in water level in both directions, as described in claim 3, is characterized in that... In step S3, the anti-skid stability coefficient is calculated using the slice method, and its formula (4) is as follows: Where n is the number of soil strips, W j Let be the self-weight of the j-th soil strip, α be the dip angle of the sliding surface, and u be the self-weight of the j-th soil strip. j φ represents the pore water pressure corresponding to the soil strip, b represents the width of the soil strip, and φ′ and c′ represent the effective shear strength parameters of the soil.

5. The anti-sliding stability control method for a plain reservoir dam under the condition of sudden drop in water level in both directions, as described in claim 4, is characterized in that... In step S4, the structural parameter optimization is transformed into a constrained nonlinear programming problem, as shown in equation (5): Where X = [B, β, n] are the optimization variables (dam crest width B, dam slope angle β, number of reinforcement layers n), C 体积 C 加筋 These are the dam embankment cost and reinforcement material cost functions, respectively, where λ is the safety factor weighting factor, and F... s This is the anti-skid stability coefficient.

6. The anti-sliding stability control method for a plain reservoir under the condition of sudden drop in water level in both directions under the condition of bidirectional water level drop, as described in claim 5, is characterized in that... In step S5, the flow rate of a single drain pipe is calculated using Darcy's law, as shown in formula (6): Where q is the flow rate of a single pipe, k is the permeability coefficient of the drainage pipe, i is the hydraulic gradient, and A is the effective water passage area of ​​the drainage pipe.

7. The anti-sliding stability control method for a plain reservoir under the condition of sudden drop in water level in both directions under the condition of bidirectional water level drop, as described in claim 6, is characterized in that... In step S6, the relationship between the dry density and moisture content of the soil is fitted by a quadratic curve, and formula (7) is as follows: ; where p d Let be the dry density, w be the moisture content (%), and a, b, and c be the fitting coefficients; the optimum moisture content is... 。 8. The anti-sliding stability control method for a plain reservoir under the condition of sudden drop in water level in both directions under the condition of bidirectional water level drop, as described in claim 7, is characterized in that... In step S7, the early warning index I during the operation period adopts the weighted maximum value model, and the formula (8) is as follows: Where Δs and Δh are the measured settlement and horizontal displacement increments, respectively, Δ Sallow Δ hallow To standardize the allowed values, w s w h The weighting coefficient (values ​​0.6 and 0.4) is used; an early warning is triggered when I > 1.0.

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