A Multi-Objective Performance Evaluation and Parameter Selection Method for Prefabricated Permeable Sand Barrier Dams

Abstract

This invention provides a multi-objective performance evaluation and parameter selection method for prefabricated permeable silt-trapping dams, belonging to the field of disaster prevention and control technology. The method includes: S1. Obtaining interception rate, velocity attenuation rate, and peak flow reduction rate; S2. Establishing a matrix and identifying candidate parameter combinations; S3. Sorting and screening the set of operating conditions that pass sustainable verification; S4. Calculating particle sorting performance indicators; S5. Generating a parameter selection quick reference table. This invention constructs a comprehensive evaluation system covering all dimensions of dam body interception performance, hydrodynamic reduction performance, long-term sustainable operation capability, and particle sorting performance, realizing the systematic quantification of the overall control capability of the dam body; and establishes a multi-index joint quantitative evaluation framework to achieve step-by-step joint evaluation of interception compliance judgment, hydrodynamic effect screening, and long-term operation capability verification.

Description

Technical Field

[0001] This invention relates to the field of disaster prevention and control technology, specifically to a method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt trap dams. Background Technology

[0002] Permeable silt-trapping dams, with their core advantages of intercepting coarse debris and discharging fine debris, slowing down peak flow, and maintaining continuous permeability, are widely used core retaining structures in mountain debris flow disaster prevention projects. Compared with traditional monolithic cast-in-place structures, prefabricated permeable silt-trapping dams can achieve rapid configuration, partial replacement, and upgrading of the dam structure by adjusting core control parameters such as opening type, relative opening degree, number of grid layers, and relative layer spacing, possessing a flexibility and adjustability advantage unmatched by traditional structures.

[0003] However, existing technologies for performance evaluation and parameter selection of permeable silt traps have three prominent industry pain points: Single-index evaluation systems are insufficient to support multi-objective collaborative selection: existing engineering designs rely heavily on single indicators such as interception rate and blockage criticality criteria for parameter design, lacking comprehensive evaluation methods that cover multiple core performance aspects. This can easily lead to performance deviations in dams, failing to meet the engineering requirements of multi-objective collaborative optimization. Many existing projects have rapidly lost their control functions due to improper early parameter selection.

[0004] The lack of quantitative indicators for evaluating the long-term operational capacity of reservoirs: The existing evaluation system only focuses on the instantaneous performance under a single debris flow event, and cannot quantify the reservoir capacity consumption rate and sustainable operation capacity of the dam under multiple disasters. It also fails to effectively distinguish the essential differences between single-layer and multi-layer structures in terms of reservoir capacity sharing mechanism, and cannot reflect the core engineering value of prefabricated multi-layer structures in delaying reservoir capacity decay.

[0005] The lack of a systematic engineering parameter selection process and operation period optimization strategy: the existing parameter design relies heavily on engineering experience and standard recommended values, which is not adapted to the core characteristics of prefabricated structures that are adjustable and replaceable. There is a lack of supporting standardized selection tools and full life cycle operation and maintenance strategies. When the characteristics of debris flow changes or the dam's operating performance deteriorates, it is impossible to provide a systematic diagnostic basis and structural upgrade path, which seriously restricts the realization of the advantages of prefabricated structure engineering. Summary of the Invention

[0006] This invention provides a multi-objective performance evaluation and parameter selection method for prefabricated permeable silt-trapping dams. The objectives include: first, constructing a comprehensive evaluation system covering all dimensions of dam body retention performance, hydrodynamic reduction performance, long-term sustainable operation capability, and particle sorting performance, thereby achieving a systematic quantification of the overall control capability of the dam body; second, establishing a quantitative evaluation framework combining multiple indicators to achieve step-by-step joint evaluation of interception compliance judgment, hydrodynamic effect screening, and long-term operational capability verification; and third, forming a standardized parameter selection process and a full life-cycle operation and maintenance strategy adapted to the adjustable characteristics of prefabricated structures, providing quantitative scientific decision-making basis for the structural parameter optimization design, operational performance evaluation, and full life-cycle operation and maintenance management of prefabricated permeable silt-trapping dams.

[0007] This specification discloses a multi-objective performance evaluation and parameter selection method for prefabricated permeable silt trap dams, including: S1. Obtain the interception rate, velocity attenuation rate and peak flow reduction rate of the prefabricated permeable dam to be evaluated under debris flow. S2. Using the interception rate as the horizontal axis and the speed attenuation rate and the peak flow reduction rate as the vertical axes respectively, establish an interception rate-speed attenuation rate matrix and an interception rate-peak flow reduction rate matrix; using a preset interception compliance line and a preset significant reduction line, divide the performance space of each matrix into four quadrants, and identify the working conditions that fall into the quadrants corresponding to both interception compliance and significant reduction in the two matrices as candidate parameter combination sets that meet the interception criteria and significant reduction. S3. For the working conditions in the candidate parameter combination set, calculate their reservoir capacity retention coefficient. The reservoir capacity retention coefficient is obtained by multiplying the proportion of discharged material derived from the interception rate with the relative opening that characterizes the permeability of the dam body. Sort the working conditions according to the size of the reservoir capacity retention coefficient, retain the top few working conditions with the largest reservoir capacity retention coefficient, or retain the working conditions with the reservoir capacity retention coefficient greater than a preset threshold, to obtain the set of working conditions that pass the sustainable verification. S4. The solid particles of debris flow are divided into coarse particle segment, medium particle segment and fine particle segment according to particle size. Based on the proportion of each segment in the original sample, the mass weighted proportion of the equivalent coarse particle segment and fine particle segment in the whole pool is calculated for each working condition in the set of working conditions. Based on this, the coarse particle blocking efficiency, fine particle discharge efficiency and comprehensive coarse particle blocking and fine particle discharge index are calculated to obtain the particle sorting performance index of each working condition. S5. Following the three-step selection process of performance matrix screening, sustainability verification, and engineering constraint back-inference, based on the candidate parameter combination set, the performance ranking among the working conditions that have passed the sustainability verification, and the particle sorting performance of each working condition, back-infer and determine the recommended parameter window, including opening type, relative opening, number of grid layers, and relative interlayer spacing, and generate a parameter selection quick reference table.

[0008] This instruction manual also includes: S6. Establish a closed-loop strategy for monitoring, diagnosis, and upgrading during operation. The interception rate, velocity attenuation rate, peak flow reduction rate, and reservoir capacity retention coefficient are used as core monitoring parameters. The dam's operating status is diagnosed based on the monitoring data, and corresponding structural adjustment measures are taken based on the adjustable characteristics of the prefabricated structure. After each structural adjustment measure is implemented, S1 to S4 are re-executed to re-evaluate the performance of the adjusted dam. The parameter selection quick reference table generated in S5 is updated based on the re-evaluation results. The cycle is iterated until the core monitoring parameters are restored to the preset target range.

[0009] In this specification, in S2, the interception compliance line is set to an interception rate of 60%, and the significant reduction line is set to a speed attenuation rate of 50% and a peak flow reduction rate of 50%. The four quadrants are specifically: a low interception and high reduction zone with an interception rate of less than 60% and a reduction index of 50% or higher; a high interception and high reduction zone with an interception rate of 60% or higher and a reduction index of 50% or higher; a low interception and low reduction zone with an interception rate of less than 60% and a reduction index of less than 50%; and a high interception and low reduction zone with an interception rate of 60% or higher and a reduction index of less than 50%. The candidate parameter combination set for interception compliance and significant reduction is the set of conditions that simultaneously satisfy the condition of falling into the high interception and high reduction zone in both the interception rate-speed attenuation rate matrix and the interception rate-peak flow reduction rate matrix.

[0010] In this specification, in S3, the reservoir capacity retention coefficient is specifically obtained by multiplying the difference between a certain value and the interception rate by the ratio of the width of the dam opening to the maximum particle size of the debris flow; wherein, the proportion of discharged material derived from the interception rate is characterized by the difference between a certain value and the interception rate, and the difference between a certain value and the interception rate is the inverse index of the reservoir capacity consumption rate; the relative opening is characterized by the ratio of the width of the dam opening to the maximum particle size of the debris flow, and the ratio of the width of the dam opening to the maximum particle size of the debris flow determines the potential for natural discharge of solid material; the sustainable verification also includes: statistically analyzing the proportion of the interception amount of each level of the grid in the multi-layer structure to the total interception amount, screening out the working conditions where the interception ratio of the first layer exceeds 97%, and preferentially retaining the working conditions where the interception ratio of the last layer is not less than 5%.

[0011] In this specification, for prefabricated permeable sand-trapping dams with two or more layers of grid, S3 further includes calculating a modified reservoir capacity retention coefficient. The modified reservoir capacity retention coefficient is calculated jointly by the reservoir capacity retention coefficient, the first-layer interception ratio representing the first-layer load, and the last-stage interception ratio representing the last-stage sharing capacity. Specifically, when the first-layer interception ratio increases, the modified reservoir capacity retention coefficient decreases accordingly; when the last-stage interception ratio increases, the modified reservoir capacity retention coefficient increases accordingly.

[0012] In this specification, in S4, the coarse particle segment refers to particles with a diameter greater than 10 mm, the medium particle segment refers to particles with a diameter between 0.1 mm and 10 mm, and the fine particle segment refers to particles with a diameter less than 0.1 mm. The coarse particle interception efficiency is the ratio of the equivalent coarse particle segment ratio of the entire storage to the original coarse particle segment ratio; a value greater than 1 indicates that coarse particles are enriched in the storage. The fine particle discharge efficiency is 1 minus the ratio of the equivalent fine particle segment ratio of the entire storage to the original fine particle segment ratio; a larger value indicates more complete discharge of fine particles. The comprehensive coarse particle interception and fine particle discharge index is obtained by subtracting the difference between 1 and the fine particle discharge efficiency and the coarse particle interception efficiency; a smaller value indicates better comprehensive coarse particle interception and fine particle discharge performance.

[0013] In this specification, S4 also includes calculating the layered comprehensive coarse and fine discharge index for each layer of the assembled permeable sand-trapping dam with two or more layers. The layered comprehensive coarse and fine discharge index is calculated by the coarse tracing efficiency and fine discharge efficiency of each layer according to the same rules. By comparing the changes in the values ​​of the layered comprehensive coarse and fine discharge index of each layer, when the value of the layered comprehensive coarse and fine discharge index of the last layer is lower than that of the first layer, it is determined that the multi-layer structure has played an effective progressive screening role.

[0014] In this specification, S5, the engineering constraint back-calculation further includes configuring the number of grid layers and the relative interlayer spacing based on the following linkage optimization rules: Define the inter-layer sorting synergy coefficient to characterize whether the value of the comprehensive coarse-blocking and fine-sorting index of each layer decreases as the layer number increases; Define the effective contribution coefficient of the final layer, which is calculated by the interception ratio of the final layer and the sorting efficiency of the final layer. When the interlayer sorting coordination coefficient shows that the comprehensive coarse interception and fine rejection index of each layer does not show a decreasing trend, and the interception ratio of the first layer exceeds the preset threshold, it is judged that the first layer is overloaded and the subsequent layers are ineffective, and adjustment measures such as increasing the relative interlayer spacing or improving the transparency of the first layer are taken. When the effective contribution coefficient of the final stage is lower than the preset threshold, and the difference between the comprehensive coarse-blocking and fine-draining index of the final stage layer and the previous stage layer is less than the preset value, it is determined that the final stage layer is redundant, and adjustment measures such as reducing the number of grid layers or adjusting the opening of the final stage are taken.

[0015] In this specification, the diagnostic rules described in section S6 are as follows: If the interception rate is detected to be lower than the preset interception threshold twice in a row, it is diagnosed as strong or difficult to establish passage. If the rate of siltation growth in the reservoir exceeds the preset threshold or the decrease in the reservoir capacity retention coefficient exceeds 30% within the preset monitoring period, it is diagnosed as excessive flow obstruction leading to siltation concentration. If the concentration of fine particles downstream is continuously higher than the preset threshold, it is diagnosed as excessive final-stage fine particle removal. If local components of the dam are damaged or the impact response amplitude increases abnormally, it is diagnosed as insufficient bearing capacity of the local components.

[0016] In this specification, in section S6, the mapping relationship between the structural adjustment measures and the diagnostic conclusions is as follows: For diagnoses that are difficult to establish due to strong or blocked passage, measures such as increasing the number of grid layers, reducing the relative opening, or replacing with an opening type that has a higher coarsening efficiency can be taken. For diagnosing the problem of excessive flow obstruction leading to siltation, measures such as layered dredging, partial replacement of grating plates to restore opening size, increasing relative opening or optimizing relative interlayer spacing to enhance interlayer sharing effect are adopted. To address the diagnosis of excessive fine exhaust in the final stage, measures such as reducing the relative opening of the final stage grille or adjusting the opening type of the final stage are taken. For diagnoses of insufficient load-bearing capacity in local components, measures such as replacing damaged components or connectors are taken.

[0017] The embodiments described in this specification can achieve at least the following beneficial effects: It addresses the industry pain point that single-index evaluation cannot support multi-objective collaborative selection, and establishes a comprehensive evaluation framework that integrates interception performance, hydrodynamic reduction performance and long-term sustainability. Through dual-matrix joint evaluation, it achieves synchronous control of multiple core performance indicators, effectively avoiding the problem of dam performance deviation caused by single-index optimization.

[0018] It pioneered a reservoir capacity retention coefficient that can quantitatively characterize the long-term operational capacity of a dam, integrating and quantifying the mutually constraining interception performance and permeability discharge capacity. This fills the gap in existing technologies that cannot systematically evaluate the long-term sustainable operational capacity of a dam, and provides a unified and concise quantitative basis for comparing the sustainability of different structural schemes.

[0019] A particle sorting evaluation index system combining full-database and stratified methods was established, which can quantitatively characterize the particle sorting contribution of prefabricated multi-layer structures at different layers, accurately reveal the progressive screening characteristics of multi-layer structures, and provide a scientific evaluation basis for the refined configuration of the number of dam layers and the spacing between layers.

[0020] It has developed a full lifecycle decision-making tool that covers the entire process from design phase selection to dynamic optimization during operation. It has proposed a standardized parameter selection process and supporting engineering quick reference tools, as well as a closed-loop operation and maintenance strategy adapted to the characteristics of prefabricated structures, which can give full play to the core engineering advantages of prefabricated structures, such as adjustability, maintainability, and upgradeability. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the multi-objective performance evaluation and parameter selection method for prefabricated permeable silt trap dams.

[0022] Figure 2 for - A schematic diagram of the quadrant division of the two-dimensional performance matrix.

[0023] Figure 3 for - A schematic diagram of quadrant division of a two-dimensional performance matrix.

[0024] Figure 4 for - A schematic diagram of the working condition screening using the R matrix.

[0025] Figure 5 for - A schematic diagram of matrix operating condition screening.

[0026] Figure 6 for -R and - A schematic diagram of matrix intersection condition screening.

[0027] Figure 7 This is a schematic diagram of the distribution of the storage capacity retention coefficient δ.

[0028] Figure 8 A schematic diagram of the three-step process for parameter selection.

[0029] Figure 9 This is a schematic diagram of the opening type of a prefabricated permeable silt trap dam.

[0030] Figure 10 This is a schematic diagram of the geometric features of openings of types I, II, and III.

[0031] Figure 11 This is a schematic diagram illustrating the calculation process for coarse interception efficiency and fine discharge efficiency.

[0032] Figure 12 This is a schematic diagram comparing the evaluation of the comprehensive coarse-grained and fine-grained index and the stratified index.

[0033] Figure 13 This is a schematic diagram of a closed-loop strategy for monitoring, diagnosis, and upgrade during operation.

[0034] Figure 14 This is a schematic diagram of a multi-layered grid interception structure.

[0035] Figure 15 A schematic diagram illustrating the coding of operating conditions with different parameter combinations. Detailed Implementation

[0036] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0037] like Figure 1As shown in the figure, this embodiment provides a method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt trap dams, including: S1. Obtain the interception rate, velocity attenuation rate and peak flow reduction rate of the prefabricated permeable dam to be evaluated under debris flow. S2. Using the interception rate as the horizontal axis and the speed attenuation rate and the peak flow reduction rate as the vertical axes respectively, establish an interception rate-speed attenuation rate matrix and an interception rate-peak flow reduction rate matrix; using a preset interception compliance line and a preset significant reduction line, divide the performance space of each matrix into four quadrants, and identify the working conditions that fall into the quadrants corresponding to both interception compliance and significant reduction in the two matrices as candidate parameter combination sets that meet the interception criteria and significant reduction. S3. For the working conditions in the candidate parameter combination set, calculate their reservoir capacity retention coefficient. The reservoir capacity retention coefficient is obtained by multiplying the proportion of discharged material derived from the interception rate with the relative opening that characterizes the permeability of the dam body. Sort the working conditions according to the size of the reservoir capacity retention coefficient, retain the top few working conditions with the largest reservoir capacity retention coefficient, or retain the working conditions with the reservoir capacity retention coefficient greater than a preset threshold, to obtain the set of working conditions that pass the sustainable verification. S4. The solid particles of debris flow are divided into coarse particle segment, medium particle segment and fine particle segment according to particle size. Based on the proportion of each segment in the original sample, the mass weighted proportion of the equivalent coarse particle segment and fine particle segment in the whole pool is calculated for each working condition in the set of working conditions. Based on this, the coarse particle blocking efficiency, fine particle discharge efficiency and comprehensive coarse particle blocking and fine particle discharge index are calculated to obtain the particle sorting performance index of each working condition. S5. Following the three-step selection process of performance matrix screening, sustainability verification, and engineering constraint back-inference, based on the candidate parameter combination set, the performance ranking among the working conditions that have passed the sustainability verification, and the particle sorting performance of each working condition, back-infer and determine the recommended parameter window, including opening type, relative opening, number of grid layers, and relative interlayer spacing, and generate a parameter selection quick reference table.

[0038] In some embodiments, it also includes: S6. Establish a closed-loop strategy for monitoring, diagnosis, and upgrading during operation. The interception rate, velocity attenuation rate, peak flow reduction rate, and reservoir capacity retention coefficient are used as core monitoring parameters. The dam's operating status is diagnosed based on the monitoring data, and corresponding structural adjustment measures are taken based on the adjustable characteristics of the prefabricated structure. After each structural adjustment measure is implemented, S1 to S4 are re-executed to re-evaluate the performance of the adjusted dam. The parameter selection quick reference table generated in S5 is updated based on the re-evaluation results. The cycle is iterated until the core monitoring parameters are restored to the preset target range.

[0039] In some embodiments, in S2, the interception target is set to an interception rate of 60%, and the significant reduction target is set to a speed attenuation rate of 50% and a peak flow reduction rate of 50%. The four quadrants are specifically: a low interception and high reduction zone with an interception rate of less than 60% and a reduction index of 50% or higher; a high interception and high reduction zone with an interception rate of 60% or higher and a reduction index of 50% or higher; a low interception and low reduction zone with an interception rate of less than 60% and a reduction index of less than 50%; and a high interception and low reduction zone with an interception rate of 60% or higher and a reduction index of less than 50%. The candidate parameter combination set for interception target achievement and significant reduction is a set of conditions that simultaneously satisfy the condition of falling into the high interception and high reduction zone in both the interception rate-speed attenuation rate matrix and the interception rate-peak flow reduction rate matrix.

[0040] In some embodiments, in S3, the reservoir capacity retention coefficient is specifically obtained by multiplying the difference between a value minus the interception rate and the ratio of the width of the dam opening to the maximum particle size of the debris flow; wherein, the proportion of discharged material derived from the interception rate is characterized by the difference between a value minus the interception rate, and the difference between a value minus the interception rate is the inverse index of the reservoir capacity consumption rate; the relative opening is characterized by the ratio of the width of the dam opening to the maximum particle size of the debris flow, and the ratio of the width of the dam opening to the maximum particle size of the debris flow determines the potential for natural discharge of solid material; the sustainable verification also includes: statistically analyzing the proportion of the interception amount of each level of the grid in the multi-layer structure to the total interception amount, screening out the working conditions where the interception ratio of the first layer exceeds 97%, and preferentially retaining the working conditions where the interception ratio of the last layer is not less than 5%.

[0041] In some embodiments, for prefabricated permeable sand-trapping dams with two or more grid layers, S3 further includes calculating a modified reservoir capacity retention coefficient. The modified reservoir capacity retention coefficient is calculated jointly by the reservoir capacity retention coefficient, the first-layer interception ratio representing the first-layer load, and the last-stage interception ratio representing the last-stage sharing capacity. Wherein, when the first-layer interception ratio increases, the modified reservoir capacity retention coefficient decreases accordingly; when the last-stage interception ratio increases, the modified reservoir capacity retention coefficient increases accordingly.

[0042] In some embodiments, in S4, the coarse particle segment refers to particles with a diameter greater than 10 mm, the medium particle segment refers to particles with a diameter between 0.1 mm and 10 mm, and the fine particle segment refers to particles with a diameter less than 0.1 mm. The coarse particle interception efficiency is the ratio of the equivalent coarse particle segment ratio of the entire storage to the original coarse particle segment ratio; a value greater than 1 indicates that coarse particles are enriched in the storage. The fine particle discharge efficiency is 1 minus the ratio of the equivalent fine particle segment ratio of the entire storage to the original fine particle segment ratio; a larger value indicates that fine particles are discharged more fully. The comprehensive coarse particle interception and fine particle discharge index is obtained by subtracting the difference between 1 and the fine particle discharge efficiency and the coarse particle interception efficiency; a smaller value indicates better comprehensive coarse particle interception and fine particle discharge performance.

[0043] In some embodiments, S4 further includes calculating the layered comprehensive coarse-blocking and fine-discharge index for each layer of the assembled permeable sand-trapping dam with two or more layers. The layered comprehensive coarse-blocking and fine-discharge index is calculated by the coarse-blocking efficiency and fine-discharge efficiency of each layer according to the same rules. By comparing the changes in the values ​​of the layered comprehensive coarse-blocking and fine-discharge index of each layer, when the value of the layered comprehensive coarse-blocking and fine-discharge index of the last layer is lower than that of the first layer, it is determined that the multi-layer structure has played an effective progressive screening role.

[0044] In some embodiments, S5, the engineering constraint back-calculation further includes configuring the number of grid layers and the relative interlayer spacing based on the following linkage optimization rules: Define the inter-layer sorting synergy coefficient to characterize whether the value of the comprehensive coarse-blocking and fine-sorting index of each layer decreases as the layer number increases; Define the effective contribution coefficient of the final layer, which is calculated by the interception ratio of the final layer and the sorting efficiency of the final layer. When the interlayer sorting coordination coefficient shows that the comprehensive coarse interception and fine rejection index of each layer does not show a decreasing trend, and the interception ratio of the first layer exceeds the preset threshold, it is judged that the first layer is overloaded and the subsequent layers are ineffective, and adjustment measures such as increasing the relative interlayer spacing or improving the transparency of the first layer are taken. When the effective contribution coefficient of the final stage is lower than the preset threshold, and the difference between the comprehensive coarse-blocking and fine-draining index of the final stage layer and the previous stage layer is less than the preset value, it is determined that the final stage layer is redundant, and adjustment measures such as reducing the number of grid layers or adjusting the opening of the final stage are taken.

[0045] In some embodiments, in S6, the diagnostic rules are specifically as follows: If the interception rate is detected to be lower than the preset interception threshold twice in a row, it is diagnosed as strong or difficult to establish passage. If the rate of siltation growth in the reservoir exceeds the preset threshold or the decrease in the reservoir capacity retention coefficient exceeds 30% within the preset monitoring period, it is diagnosed as excessive flow obstruction leading to siltation concentration. If the concentration of fine particles downstream is continuously higher than the preset threshold, it is diagnosed as excessive final-stage fine particle removal. If local components of the dam are damaged or the impact response amplitude increases abnormally, it is diagnosed as insufficient bearing capacity of the local components.

[0046] In some embodiments, in S6, the mapping relationship between the structural adjustment measures and the diagnostic conclusions is as follows: For diagnoses that are difficult to establish due to strong or blocked passage, measures such as increasing the number of grid layers, reducing the relative opening, or replacing with an opening type that has a higher coarsening efficiency can be taken. For diagnosing the problem of excessive flow obstruction leading to siltation, measures such as layered dredging, partial replacement of grating plates to restore opening size, increasing relative opening or optimizing relative interlayer spacing to enhance interlayer sharing effect are adopted. To address the diagnosis of excessive fine exhaust in the final stage, measures such as reducing the relative opening of the final stage grille or adjusting the opening type of the final stage are taken. For diagnoses of insufficient load-bearing capacity in local components, measures such as replacing damaged components or connectors are taken.

[0047] In some embodiments, the monitoring-diagnosis-upgrade closed-loop strategy is executed cyclically after each debris flow event or periodically; after each structural adjustment measure is completed, the re-evaluation results are fed back to S5 to update the recommended parameter window for the corresponding working condition of the dam body in the parameter selection quick reference table.

[0048] The technical concept of this invention is as follows: This invention addresses the engineering application needs of prefabricated permeable silt traps by constructing a complete technical solution covering the entire process of design selection, performance evaluation, and operation optimization. The core logic is as follows: First, a basic evaluation index system covering interception performance and hydrodynamic reduction performance is established, clarifying the standardized quantitative characterization method of the dam's core control capability. Second, a two-dimensional performance matrix of interception rate-velocity attenuation rate and interception rate-peak flow reduction rate is constructed. Through performance quadrant division and double matrix intersection screening, high-performance parameter combinations that simultaneously meet interception standards and hydrodynamic reduction requirements are identified. Third, a reservoir capacity retention coefficient is introduced to verify the long-term sustainable operation capability of candidate operating conditions, selecting schemes with excellent reservoir capacity retention capability and significant stratified sharing effect. Subsequently, a granular evaluation system combining full reservoir and stratified performance is established. A performance evaluation system is established to quantify the comprehensive performance of the dam body in terms of both coarse and fine drainage, as well as the progressive screening effect of the multi-layered structure. Based on this, a standardized three-step parameter selection process is established: "performance matrix screening → sustainability verification → engineering constraint back-engineering". Combining engineering constraints such as gully topography, construction conditions, and operation and maintenance requirements, a recommended window for core structural parameters is derived, forming a parameter selection quick reference table suitable for different engineering scenarios. Finally, a closed-loop optimization strategy of "monitoring-diagnosis-upgrade" is established during the operation period, adapting to the modular and adjustable characteristics of prefabricated structures, to achieve dynamic optimization and performance control of the dam body throughout its entire life cycle.

[0049] The specific steps are as follows: S1. Establish an evaluation index system for interception and hydrodynamic performance.

[0050] For the prefabricated permeable silt trap dam to be evaluated, the following three categories of basic performance evaluation indicators are determined: (1) Interception rate Defined as the mass of solid matter (including water mixture) intercepted by the silt-trapping dam within the reservoir. Total mass of debris flow The ratio is calculated using the following formula: ; For multi-layer structures (the number of grid layers is...) (Layer), total interception quality within the database Equal to the sum of the interception mass of each layer of the reservoir: In the formula, For the first Mass of intercepted material in the layered storage area, in kg.

[0051] (2) Velocity decay rate Defined as the ratio of the difference between the velocity of the flow in front of the debris flow dam and the velocity behind the dam to the velocity in front of the dam, the calculation formula is: ; In the formula, For the first Average flow velocity of debris flow in front of the dam ( ), For the first Average flow velocity of debris flow behind the dam ( (The units are all m / s).

[0052] (3) Peak flow reduction rate Defined as the ratio of the difference between the peak flow rates of debris flows before and after the dam crossing to the peak flow rate before the dam crossing, the calculation formula is: ; In the formula, For the first Peak flow rate of debris flow in front of layered grid ( ), For the first Peak flow rate of debris flow after layered grid ( (The units are all m³ / s;) For the first The depth of the debris flow in front of the layered grid. For the first Depth of debris flow behind the layered grid, in meters.

[0053] S2. Establish - and - A two-dimensional performance matrix is ​​used to define the performance quadrants.

[0054] With interception rate The horizontal axis represents the velocity decay rate. (or peak flow reduction rate) ( ) as the vertical axis, with To intercept the compliance judgment line, with or To significantly reduce the discrimination threshold, the performance space is divided into four quadrants: First quadrant (low interception - high reduction zone): and (or ) The reduction is significant but the interception is insufficient; Second Quadrant (High Interception - High Reduction Zone): and (or ) This is the ideal performance zone, meaning that high interception meets the standard and the reduction effect is significant; Third quadrant (low interception - low reduction zone): and (or ) Its overall performance is relatively weak; Fourth Quadrant (High Interception - Low Reduction Zone): and (or ) The interception capability meets the standard, but the reduction capability is insufficient; exist - Matrix and - The matrix is ​​used to define the working conditions of each combination of structural parameters, and the second quadrant (ideal area) of the two types of matrices is cross-filtered to identify the intersection working conditions that simultaneously meet the interception target and the two types of reduction indicators, thus forming a set of candidate high-performance parameter combinations. S3. Calculate the storage capacity retention coefficient To evaluate the long-term sustainable operation capability.

[0055] For the candidate high-performance parameter combinations obtained from S2 screening, a storage capacity retention coefficient is introduced. As a comprehensive indicator for quantifying long-term operational capability, the calculation formula is as follows: ; In the formula, This refers to the width of the silt trap opening, in mm. The maximum particle size in the debris flow particle size distribution curve is expressed in mm. It represents the relative opening (dimensionless).

[0056] Storage capacity retention coefficient The physical meaning is: It reflects the proportion of material discharged from the dam body after a single debris flow event and is an inverse indicator of the reservoir capacity consumption rate. The permeability of the dam body determines its potential for natural discharge of solid materials; the product of these two factors comprehensively characterizes the dam body's ability to maintain permeability and reservoir capacity while achieving a certain interception target. The larger the value, the stronger the storage capacity and the longer the expected service life. Calculate each candidate working condition separately Value, and according to Values ​​are sorted from largest to smallest, and priority is given to retaining them. High operating conditions; S4. Establish a particle sorting performance evaluation index system.

[0057] Using the particle size distribution of the original debris flow solid particles as a reference, the solid particles are divided into three sections according to particle size: coarse particles (particle size distribution). ), medium particle size range (particle size) ) and fine particle segment (particle size) ), respectively calculate the proportion of the three sections in the original sample. , , ; For grid layers of The prefabricated permeable silt-trapping dam with the first layer is designed as follows: The corresponding proportions of the three sections within the layered storage area are as follows: , , ( ), No. The mass of the sediment in the reservoir area is The total interception mass is Then the quality weight of each layer for: ; The proportion of equivalent coarse-grained segments in the entire library and the proportion of fine particles The calculation formulas are as follows: ; ; Based on this, the following three particle sorting performance evaluation indicators are defined: (1) Coarse-blocking efficiency : Reflects the enrichment degree of coarse particles in the reservoir relative to the original sample, and is calculated using the following formula: ; This indicates that coarse particles are enriched in the reservoir, enhancing the coarse-blocking effect; (2) Fine discharge efficiency : Reflects the degree of reduction of fine particles in the reservoir relative to the original sample; the calculation formula is: ; The larger the value, the more fully the fine particles are expelled and the stronger the ability to expel fine particles. (3) Comprehensive coarse interception and fine discharge index Simultaneously characterizing the effects of relative residue of fine particles and relative enrichment of coarse particles within the reservoir, the calculation formula is as follows: ; The smaller the value, the less fine particles remain and the stronger the enrichment of coarse particles, resulting in better overall performance in intercepting coarse particles and removing fine particles. For multi-layer grid structures, the first... Layered coarse index of the storage area 1. Detail the indicators by level and stratified comprehensive index This is used to identify the distribution and progression patterns of sorting contributions across different levels. ; ; ; The calculation process for coarse-blocking efficiency and fine-discharge efficiency is as follows: Figure 11 As shown, the evaluation of the comprehensive coarse-grained and fine-grained index and the stratified index is compared. Figure 12 As shown, S5. Execute the parameter selection process to determine the recommended parameter combination.

[0058] Based on the evaluation results of S2 to S4, the recommended combination of structural parameters is determined according to the following three-step parameter selection process: (1) First step – Performance matrix selection: based on the established S2 - and - The performance matrix uses the second quadrant (high interception - high reduction region) as the filtering area to identify... at the same time and The candidate working conditions with intersection are used to form a candidate parameter set; if there are no intersecting working conditions, the constraints are relaxed step by step: first, ensure that (Prioritize interception of qualified targets), and then proceed according to... and Comprehensive ranking; (2) Second step – sustainability verification: In the candidate parameter set, the reservoir capacity retention coefficient calculated based on S3 is used. The various operating conditions are sorted, and the proportion of subsequent layers of interception in a multi-layered structure for each condition is calculated (layered interception ratio), with priority given to retaining them. The value is relatively high and the burden is significantly shared in subsequent layers (the proportion of interception at the final layer). The combination of structural parameters is eliminated. Value too low ( Or the load on the first layer is too concentrated (first-layer interception rate) (The working conditions of) (3) Third step – Engineering constraint back-deduction: Taking into account engineering constraints such as ditch topography, construction organization capabilities and operation and maintenance convenience, the recommended parameter combination obtained from the first two steps is verified for engineering feasibility, and the opening type and relative opening are back-deduced. Number of grid layers and relative interlayer spacing The recommended parameter window generates a parameter selection quick reference table; among which... This refers to the interlayer spacing, in meters (m).

[0059] S6. Establish a closed-loop strategy of "monitoring-diagnosis-upgrade" during operation.

[0060] like Figure 13 To address the dynamic performance changes of prefabricated permeable silt traps during operation, a closed-loop optimization strategy was established, including a monitoring index system, condition diagnosis rules, and upgrade and adjustment measures, as detailed below: (1) Monitoring: based on interception rate Velocity decay rate Peak flow reduction rate and storage capacity retention coefficient The core monitoring quantity is supplemented by observation indicators such as changes in the effective flow cross-section of the opening, the siltation height in the reservoir, and the morphology of the downstream accumulation fan, and the dam's operational status is assessed regularly. (2) Diagnosis: Based on the monitoring data, the dam's operational status is classified and diagnosed: if the monitoring shows Drop to below The diagnosis is either strong permeability or unstable blockage; if the sedimentation and growth within the reservoir accelerates, A rapid decrease in flow rate is diagnosed as excessive flow obstruction leading to sediment accumulation; if the discharge intensity is too high or the risk of downstream refinement increases, it is diagnosed as excessive flow capacity in the final stage; if the impact pressure increases significantly or local components are damaged, it is diagnosed as insufficient impact resistance of the components. (3) Upgrade: For different diagnostic conclusions, take corresponding prefabricated structural adjustment measures: against Downward Diagnosis: Increase the number of grid layers Or reduce the relative opening. Alternatively, the opening type could be replaced with one that has stronger interception capabilities to increase the probability of particle bridging and blockage at the opening. against Rapid descent diagnosis: Prioritize layered dredging, replace the first layer of grating to restore the opening size, or appropriately increase its size. To improve permeability and excretion capacity, and simultaneously optimize To enhance the inter-layer sharing effect; Diagnostic for excessively strong exhaust: Adjust the opening type of the final stage grille or reduce the size of the final stage grille. Enhance the final stage particle screening and interception capabilities; For component damage diagnosis: replace damaged grating plates or connectors, and quickly restore structural function by utilizing the prefabricated and replaceable features; (4) Iteration: The above "monitoring-diagnosis-upgrade" strategy is executed periodically. After each upgrade and adjustment, S1 to S4 are re-executed to re-evaluate the performance, verify the adjustment effect, and update the parameter selection scheme accordingly.

[0061] The technical effects of this invention are as follows: (1) This invention solves the problem that single-indicator evaluation cannot support multi-objective collaborative selection. It establishes a three-dimensional integrated comprehensive evaluation framework covering interception, reduction, and sustainability. - and - A two-dimensional performance matrix enables simultaneous visualization and evaluation of multiple indicators. An intersection condition screening method is proposed to identify high-performance zones where all three indicators—interception rate, speed attenuation rate, and peak flow reduction rate—meet the standards. This effectively overcomes the performance bias caused by single-indicator optimization in existing technologies.

[0062] (2) The reservoir capacity retention coefficient, which is used to quantitatively characterize long-term operational capacity, was proposed for the first time. Storage capacity retention coefficient By integrating two mutually constraining parameters, interception rate and permeability, a comprehensive quantitative assessment of the dam's reservoir capacity consumption rate and permeability maintenance potential is achieved under the premise of meeting interception standards. This fills the gap in existing technologies where evaluation systems cannot quantify long-term sustainable operation capabilities, and provides a unified and concise quantitative basis for comparing the sustainability of different dam structures.

[0063] (3) A stratified particle sorting evaluation index system was established, revealing the progressive sieving characteristics of the multi-layer structure. The coarse-blocking efficiency proposed in this invention... , fine discharge efficiency and comprehensive coarse and fine index and corresponding stratification indicators , , It can quantitatively characterize the particle sorting contribution of prefabricated multilayer structures at each layer, providing a refined evaluation basis for optimizing the interlayer spacing and layer configuration.

[0064] (4) It provides a complete closed-loop decision-making tool from design to operation. The three-step selection process and parameter quick reference table of “performance matrix screening → sustainability verification → engineering constraint back-inference” proposed in this invention, as well as the closed-loop strategy of “monitoring-diagnosis-upgrade” during operation, directly transform the multi-objective evaluation conclusions into an operable engineering decision-making tool, which effectively supports the full play of the engineering advantages of prefabricated permeable silt traps that are adjustable, maintainable and upgradeable.

[0065] Example 1: Parameter selection and evaluation of a single-layer grid assembled permeable sand-trapping dam.

[0066] This embodiment uses a Class II opening (opening aspect ratio) ,in The height of the opening. (Opening width), debris flow density Based on the basic working conditions, this paper explains the specific application of the method described in this invention in the selection of parameters for a single-layer grid structure.

[0067] S1: Relative opening Five working conditions (1.25, 1.375, 1.5, 1.625, and 1.75) were selected for water tank model experiments. The maximum particle size of the experimental material was determined. Record the velocity of the inflow in front of the dam under various working conditions. dam downstream speed Peak flow rate of debris flow and and the amount of interception within the database With total input Calculate the values ​​for each working condition according to the formula described in S1. , and The values ​​yielded the following results (example data), as shown in Table 1: Table 1. Operating Conditions , and Value table

[0069] S2: As Figure 2 , Figure 3 As shown, the performance quadrants are divided with interception rate on the horizontal axis and reduction index on the vertical axis, and each operating condition is positioned within a quadrant. To intercept the standard judgment line, and To reduce the significance of the discrimination line, in - In the matrix: The three operating conditions of 1.375 and 1.5 all fall into the second quadrant (the ideal zone for high interception-high reduction). 1.75 falls into the first quadrant (low interception - high reduction zone). - In the matrix, 1.375 and 1.5 also fall into the second quadrant. Take... - and - The intersection of the ideal regions of the two types of matrices is confirmed. 1.375 and 1.5 are candidate high-performance operating conditions. For example... Figure 4 , Figure 5 and Figure 6 As shown, high-performance candidate operating conditions are obtained through the intersection of two matrices.

[0070] S3: As Figure 7 As shown, the reservoir capacity retention coefficient can intuitively reflect the long-term operating capacity under different working conditions. The three candidate working conditions are calculated using the formula... The calculations and results are shown in Table 2: Table 2. Candidate Operating Condition Storage Capacity Retention Coefficient Table

[0071] according to Value sorting, correspond The highest value (58.72) indicates the strongest capacity maintenance capability at a similar interception rate level, followed by [other value]. ( ).

[0072] S4: Take sieving tests on the accumulated samples in the reservoir for each candidate working condition to obtain the proportion of each particle size range, based on the proportion of the coarse particle segment of the original sample. The proportion of fine particles As a reference standard, Taking the working condition as an example, calculate the sorting index: assuming the proportion of coarse particles in the bin. The proportion of fine particles ,but: ; ; ; This indicates that the working condition has good overall performance in both coarse and fine material removal.

[0073] S5: Based on the evaluation results of the above three steps, following the three-step selection process of "performance matrix screening → sustainability verification → engineering constraint back-calculation": Step 1 confirms the candidate operating condition set as follows: 1.375, 1.5; Step 2 Sort selection To optimize operating conditions ( (Highest); the third step, combining the actual flow characteristics of the channel and construction organization conditions, ultimately recommends Class II openings; A single-layer grid assembled permeable sand-trapping dam, and the parameter combination is included in the quick reference table.

[0074] S6: Based on the above recommended scheme, establish the following operational strategy: Set the monitoring indicator threshold as follows. , When monitoring data shows Two consecutive times lower At that time, the diagnosis was strong, and the upgraded measures were to... Adjusted from 1.5 to 1.375; when The value has decreased continuously for more than At that time, the diagnosis was concentrated siltation, and the upgraded measures were to implement first-layer dredging and add a double-layer screen. This introduces an inter-layer load-sharing mechanism into the runtime configuration.

[0075] Example 2: Comprehensive performance evaluation of a three-layer grid assembled permeable sand-trapping dam.

[0076] This embodiment uses a Class III opening (opening aspect ratio) ), relative opening Number of grid layers Debris flow density Based on the basic working conditions, this paper explains the specific application of the present invention in the comprehensive evaluation and interlayer sorting analysis of multi-layer three-dimensional grid structures.

[0077] S1 to S2: Relative interlayer spacing Experiments were conducted under four working conditions: 2.5, 5.0, 7.5, and 10.0, and the parameters for each working condition were calculated. , and Value, in - and - Quadrant positioning is performed within the matrix. Taking the working condition as an example: , , All three indicators meet the threshold requirements. , , ),fall into - and - The ideal region of matrix intersection represents candidate high-performance operating conditions.

[0078] S3: Calculation Storage capacity retention factor under operating conditions: ;calculate Operating conditions: This represents the highest value under operating conditions, indicating the strongest capacity maintenance capability. A tiered interception percentage was calculated, with the tiered interception percentage set as follows: , First-layer interception percentage under working conditions for Second layer for The third layer for Final interception percentage The requirements for hierarchical sharing are met, and the verification is passed. For example... Figure 7 As shown, a three-layer structure significantly improves the storage capacity retention coefficient compared to single-layer or double-layer structures. Figure 14 As shown, the multi-layered grid achieves a reasonable allocation of storage capacity through layered distribution.

[0079] S4: Yes Layered particle size analysis was performed under the operating conditions, with the proportion of coarse particles in the first layer of the reservoir area set. Second layer The third layer Fine-grained segments correspond to , , Combine the quality weights of each layer Calculate the overall coarse-to-fine index of the entire reservoir according to the formula described in S4. And calculate the stratification index. , , ,like This indicates that the sorting effect increases progressively with each layer, and the final layer makes the most significant contribution to improving the overall performance of coarse bar separation and fine bar removal, thus verifying the engineering rationale of increasing the number of grid layers to three.

[0080] S5: Based on the overall evaluation results, a Class III opening is recommended. , , To optimize the parameter combination, a quick reference table is generated to recommend entries: This parameter combination is in Under debris flow conditions, it is possible to achieve , , With an overall performance score of 74.14, it is suitable for engineering scenarios where the proportion of fine material in the incoming flow is high, and where both permeable drainage and long-term sustainable operation are required. For example... Figure 15 As shown, different parameter combinations correspond to unique operating condition codes, facilitating rapid selection in engineering projects.

[0081] S6: For the above-mentioned recommended three-layer grid scheme, establish a "monitoring-diagnosis-upgrade" strategy: if multiple debris flows are detected... Continue to decline to The diagnosis is high permeability of the opening; the prefabricated upgrade measure is to add a third layer of grille. The value was reduced from 2.0 to 1.75, allowing for local parameter adjustments without dismantling the basic framework using adjustable opening modules; if the sedimentation rate in the final layer increases sharply (exceeding the total interception capacity)... The diagnosis was that the final stage was already carrying too much interception load, and the upgrade measure was to implement single-layer dredging of the final stage and simultaneously increase the capacity. To enhance the interlayer velocity recovery and re-sorting effect.

[0082] Example 3: Application of parameter selection quick reference table in different target engineering scenarios.

[0083] This embodiment illustrates the application method of the parameter selection quick reference table proposed in this invention in five typical engineering target scenarios.

[0084] like Figure 8 As shown, a parameter quick reference table is generated following the three-step process of "performance screening → sustainable verification → engineering back-calculation". Based on the engineering constraint back-calculation method described in S5, the following parameter selection quick reference table (simplified illustration) is formed, as shown in Table 3: Table 3. Quick Reference Table for Parameter Selection

[0085] in, The width of the downstream accumulation fan is used to characterize the degree of lateral diffusion of debris flow after it passes over the dam.

[0086] The specific recommended parameter values ​​for each engineering scenario should be calculated by substituting the measured physical parameters of debris flow in the target gully (density, gradation, peak flow, etc.) into S1 to S4, and finally determined after performing the complete selection process with the quick reference table as a reference framework.

[0087] In some embodiments, the three control effect discrimination thresholds set by the present invention—interception rate Flow rate attenuation Peak flow rate attenuation rate The criteria for determining — are as follows: (1) Interception rate threshold This threshold originates from the nonlinear jump in interception rate observed in the experimental data. Experimental results (see Example 1 or Table 4) show that when the relative opening of the grille... When the value increased from 1.5 to 1.625, the interception rate plummeted from 60.86% to 20.00%, a drop of over 40 percentage points. The interception rate changes gradually within a certain range. This abrupt change corresponds to the critical phase transition of particle bridging and blocking behavior at the grid opening: It is the natural dividing line between the two operating modes of effective closure and free passage.

[0088] Table 4. Interception Rate Threshold Table

[0089] In addition, Setting the threshold to 60% rather than a higher value also takes into account the need to avoid rapid saturation of the reservoir capacity. Engineering surveys in the background of this invention show that the current silt trap dam has a full capacity rate as high as 42.73%, partly due to the excessively high designed interception rate. It is a reasonable lower limit that balances effective interception with the sustainability of storage capacity.

[0090] (2) Threshold for flow rate decay This threshold is based on the physical relationship between debris flow kinetic energy and impact force with flow velocity. The impact force of a debris flow is proportional to the square of the flow velocity (see the impact force calculation formula in DZ / T 0239-2004 "Design Code for Debris Flow Disaster Prevention and Control Engineering").

[0091] mudstone kinetic energy In the formula For debris flow quality, For flow rate; Debris flow impact force In the formula For impact force, The impact force coefficient, The area under stress.

[0092] When the flow velocity decreases by 50%, the kinetic energy and impact force of the debris flow both decrease to 25% of their original values, a reduction of 75%, which is sufficient to downgrade a high-hazard debris flow to a low-to-medium hazard level. This threshold also considers the engineering feasibility of permeable structures: excessively high flow velocity reduction requirements (such as...) This would subject the dam to excessive loads, which is inconsistent with the design principles of permeable structures.

[0093] (3) Peak flow rate attenuation threshold This threshold draws on the evaluation concept of peak reduction rate in flood control projects. The peak flow rate of debris flows directly determines its maximum impact force and maximum affected area. Reducing the peak flow rate by 50% significantly reduces the instantaneous maximum impact load downstream, providing a greater safety margin for early warning and avoidance. Similarly, It is a balanced choice that avoids imposing excessively high regulation requirements on the permeable structure while ensuring the effectiveness of peak reduction.

[0094] In some embodiments, the sand interception rate and the percentage of layered interception are calculated as follows: Prefabricated permeable silt-trapping dams improve the interception rate of debris flow mass. Defined as the mass of solid matter (including water mixture) intercepted in the reservoir by a prefabricated permeable silt trap dam. Total mass of debris flow The ratio can be calculated using the following formula: ; Let the first Layer interception quality is Total interception mass Layered interception percentage Defined as the first The proportion of sand-trapping capacity of the layered grid to the total sand-trapping capacity, i.e. .

[0095] when When, i.e., in the case of a single-layer structure: ; when When it is a two-layer structure: ; ; ; when When it is a three-layer structure: ; ; ; ; In the formula, The mass of solid material in the warehouse before the first layer of grating; The mass of the solid material between the first and second layers; The mass of the solid material between the second and third layers; , , These represent the interception percentages of the first, second, and third layers, indicating the proportion of sand-trapping rate of each layer of the grid to the total sand-trapping rate. For example... Figure 14 As shown, the multi-layered structure allows each reservoir layer to independently intercept debris flow solid materials, with each layer bearing the load.

[0096] "Percentage of interceptions at the final layer" The threshold for "" is determined based on the following: Statistical analysis of layered interception data under different combinations of grid layers and relative interlayer spacing in the series of experiments of this invention shows that when the interception ratio of the final layer is... At that time, the storage capacity retention coefficient of the multi-layer structure Compared to a single-layer structure with the same parameters, this represents a significant improvement, with the layered distribution effect operating effectively; and when At that time, over 95% of the interception quality was concentrated in the first layer, with subsequent layers failing to play a substantial role in sharing the load, effectively degenerating the multi-layered structure into a single-layer operation mode. Therefore, This is an engineering threshold used to determine whether a multi-layered load-sharing mechanism has been effectively activated. Additionally, if the first-layer interception accounts for a certain percentage... This indicates that the dam's operation mode has become equivalent to a compact structure, thus losing the core engineering value of a prefabricated, multi-layered, and adjustable structure, and should be eliminated from the selection process.

[0097] In some embodiments, such as Figure 9 , Figure 10 As shown, the grid openings are classified into categories I, II, and III according to their height-to-width ratio to suit different debris flow conditions. The opening type of the prefabricated permeable silt trap described in this invention is based on the opening height-to-width ratio. They are divided into the following four categories: Class I openings ( ): The vertical scale of the opening is significantly larger than the horizontal scale, the horizontal constraint is significantly stronger than the vertical constraint, and the particles are easy to form bridging and blockage in the horizontal direction. It is suitable for debris flow conditions with high coarse particle content and strong interception capacity. Class II opening ( ): The horizontal dimension of the opening is significantly larger than the vertical dimension, the vertical constraint is significantly stronger than the horizontal constraint, and it has a large flow capacity before the blockage is established. It is suitable for working conditions where it is necessary to maintain permeability in the initial stage while taking into account drainage and sand discharge. Class III openings ( ): The opening height-to-width ratio is close to 1, the lateral and vertical constraints are comparable, there is no obvious dominant direction in the blocking process, and it is suitable for general working conditions where both interception and transparency are required. Type IV openings: The dam body contains two or more of the above three opening types, which can achieve differentiated constraints and are suitable for engineering scenarios with complex debris flow components.

[0098] This classification method uses geometric features as a unified scale, enabling comparable characterization of the opening constraint features of different dam types without relying on specific engineering names.

[0099] In some embodiments, the present invention does not allow continuous optimization that compensates for different metrics, but rather first establishes a strongly constrained feasible region for safe compliance, and then performs hierarchical ranking within the feasible region. That is, high... or high Uncompensable low ,high It also cannot compensate for substandard interception or peak shaving performance.

[0100] definition: (1) First feasible region: ; (2) Second feasible region: ; (3) Strongly constrained intersection domain: ; In the formula, The threshold for achieving the interception rate (benchmark value) ); To significantly reduce the threshold (benchmark value) for the rate of rate decay. ); Significantly reduce the peak flow reduction rate threshold (benchmark value) ).

[0101] Only by entering the intersection region Only after the parameter combinations are determined will the next step of sorting proceed. For the operating conditions within the intersection domain, the "intersection safety margin" will be defined. ; The dual-matrix intersection filtering method does not involve a weighted summation or Pareto front optimization of the interception rate, speed attenuation rate, and peak traffic reduction rate; instead, it constructs separate matrices for each. - Feasible domain and - The feasible region is determined, and the intersection of the two is taken to form a strongly constrained candidate set. Then, the candidate set is sorted in layers according to the safety margin of the intersection, storage capacity retention capacity and particle sorting performance, so as to avoid unreasonable compensation between different performance indicators.

[0102] Conventional Pareto front methods treat all objectives as continuous variables that can be traded off, allowing improvements in one indicator to compensate for the degradation of another. Therefore, the Pareto front may retain solutions with "extremely low interception rates but extremely high reduction rates," which is unacceptable in engineering safety assessments. Weighted summation methods synthesize indicators with different physical dimensions into a single scalar; however, the selection of weights is subjective and masks information about whether each indicator has met its target.

[0103] The dual-matrix intersection filtering described in this invention adopts a hierarchical decision-making logic of "item-specific achievement → intersection admission → domain-specific ranking": firstly, in... - plane and - Establish rigid compliance boundaries in the plane ( , , This forms two independent feasible regions. and Cases where the interception rate does not meet the standard are not included in the candidate set regardless of how high the reduction performance is (i.e., high reduction does not compensate for low interception); then the intersection of the two feasible regions is taken. As a strongly constrained candidate set; finally, only in the intersection domain... Internally, based on intersection safety margin With storage capacity retention coefficient Perform a joint sort. When two operating conditions... When values ​​are close (difference) ), preferred Higher operating conditions.

[0104] In some embodiments, for multi-layer grid structures ( To reflect the impact of the stratified sharing effect on the sustainability of storage capacity, a modified storage capacity retention coefficient is introduced. .

[0105] Bundle The revised storage capacity retention coefficient, which takes into account the stratified sharing effect, is as follows: ; in, ; This represents the percentage of first-layer interception. This represents the percentage of interceptions at the final layer. , This is an empirical coefficient, calibrated by model experiments or prototype monitoring. When only single-layer experiments are available or stratified data is lacking, it can be set as follows: The recommended initial calibration value is... , (Based on regression analysis of experimental data from a series of three-layer grids of this invention, applicable to debris flow density) (Scope), in engineering applications, it can be recalibrated based on the measured layered interception data of the target channel. Note that in the same... and Under these conditions, if the first floor is overloaded and subsequent floors do not share the load, then It will decrease; if the lowest level participates in effective burden sharing, then It will rise.

[0106] Then, establish a semi-empirical equation for the evolution of remaining effective storage capacity with the event sequence: ; In the formula, For the first The remaining effective reservoir capacity (m³) after the debris flow event. For the first Total mass of incoming flow (kg); The equivalent density of the sediment (kg / m³). , For volume conversion and natural displacement correction factors; This is the corrected reservoir capacity retention coefficient calculated after the k-th debris flow event.

[0107] Redefining the full inventory criterion: ; In the formula, To design an effective storage capacity (m³). For the safety factor of residual storage capacity, it is recommended to take... (That is, the remaining storage capacity is reduced to less than 10% of the design capacity), which can be increased to [a higher percentage] under severe engineering conditions. The corresponding number of full-database events is obtained. Or full warehouse time If the reservoir capacity of the dam is deemed to be exhausted, dredging or structural upgrades should be initiated. Based on the reservoir capacity retention coefficient, a recursive update equation for the remaining effective reservoir capacity should be established to quantitatively predict the time to full reservoir capacity, the remaining operational life, and the timing of dredging.

[0108] In some embodiments, in a single debris flow event, the control volume is defined as the area from the dam front to the end of the stable sediment deposition, and the initial total mechanical energy of the debris flow is assumed to be... The following energy conservation framework can be established: ; In the formula, This represents the initial kinetic energy of the debris flow. This represents the initial potential energy of the debris flow. The velocity in front of the dam; It is the acceleration due to gravity; The potential energy height in front of the dam; Total mass of debris flow.

[0109] When a debris flow passes through a dam, its initial total mechanical energy is not entirely transported downstream through the dam, but is converted into the following components: In the formula, The remaining transport energy corresponding to the discharge through or across the dam; The potential energy generated by the dam's climbing and backfilling; This refers to the dissipated energy caused by collisions, friction, and local turbulence between particles and between particles and structures. The structural energy consumption corresponding to siltation, bridging blockage, and coarse particle retention.

[0110] For the interception process, what truly determines whether the debris flow continues to flow downwards is the remaining transportable energy after the action of each layer of grid. Let the debris flow pass through... After the first layer of grid, the second layer The effective dissipation rate of the layered grid for the residual energy of the incoming flow is ,but: ; ; thereby: ; The total effective energy dissipation rate of the dam body against debris flow can be expressed as: ; For experiments conducted under the same slope, source composition, and scale, the degree to which the silt-trapping dam reduces the energy transported by debris flows shows a strong correlation with the final proportion of retained sediment in the reservoir. To facilitate the establishment of engineering prediction models, the interception rate is used. With total effective energy dissipation rate Approximate correspondence, that is: ; This indicates that the interception effect of prefabricated permeable dams is essentially a progressive dissipation process of the remaining transport energy of debris flows through multiple layers of grids.

[0111] Furthermore, the first Effective energy dissipation rate of layered grid It is not a fixed value, but is determined by the characteristics of the debris flow and the structural parameters of the dam. It can generally be written as: ; In the formula, Debris flow density; For the slope of the water tank; This is the opening shape coefficient. Indicates the type of opening.

[0112] Considering that the experimental conditions in this study were mostly based on a constant debris flow density and flume slope ( , ) conditions, therefore and The influence of the flow rate is incorporated into the constant term to establish a sub-model of the silt-trapping dam structural parameters and interception rate under fixed inflow conditions. Definition: ; ; Introducing dimensionless energy dissipation potential Characterizing the opening type as The number of layers is The overall reduction capacity of the dam body against the transport energy of debris flows is the interception rate. It can be written as: ; In the formula, The larger the dam, the stronger its ability to dissipate the energy transported by debris flows, and the higher its interception rate.

[0113] Based on experimental patterns, Further expressed as the product of the basic energy consumption term and the interlayer correction term: ; ; ; In the formula, Opening type Basic energy consumption coefficient; This is the relative opening sensitivity coefficient; This is the layer enhancement factor; , , , This is a relative interlayer spacing correction parameter used to characterize two-layer and three-layer structures. The nonlinear impact on the interception rate.

[0114] Based on the experimental data, a nonlinear least squares method was used to fit the data, resulting in the following expression for the interception rate: Class I openings: ; in ; ; ; In the formula, Class I opening, The relative interlayer spacing correction function when the layers are in layers.

[0115] Class II openings: ; in ; ; ; Class III openings: ; in ; ; ; In the above formulas, The coefficients for determining the goodness of fit are denoted as .

[0116] In some embodiments, the inter-layer sorting coordination coefficient is first defined: The larger this quantity, the more progressively stronger the sorting capacity of each layer.

[0117] Redefine the effective contribution coefficient of the final level: ;in This represents the percentage of interceptions at the final layer.

[0118] Based on these two quantities, a "layer number-layer spacing linkage optimization rule" can be established: (1) When Low and If the value is too high, it indicates that the first floor is overloaded and the subsequent floors are failing; the value should be increased. Or improve the transparency of the first floor; (2) When Too low and When this occurs, it indicates redundancy in the final level layer, and the number of layers should be reduced. Or adjust the opening of the final stage; (3) When Although low If the pressure is too high, it indicates that the final stage of fine extrusion is too strong, and the pressure of the final stage should be reduced. Or change the final stage opening type; (4) Only when and Only when the target value is reached is it considered... and The configuration is optimal for collaboration.

[0119] In some embodiments, The operating conditions at that time are shown in Table 5: Table 5. Table of parameter values

[0120] The adaptive adjustment method is based on the following approach: Define threshold vector Further written as: ; in, The baseline threshold vector (i.e.) , , , , ), The threshold for the storage capacity retention coefficient, This represents the threshold for the percentage of interceptions at the final layer. The interception rate benchmark threshold, The speed decay rate is the baseline threshold. The peak flow reduction rate is the baseline threshold. This serves as the baseline threshold for the storage capacity retention coefficient. This serves as the baseline threshold for the percentage of interceptions at the final layer. This is the threshold adjustment amount; The operating condition feature vector includes at least one or more of the following: inflow density, coarse particle ratio, peak flow rate, channel slope, downstream sensitivity level, and maintenance difficulty.

[0121] For example: (1) Safety-first scenario: improve and ; (2) Sustainable priority scenarios: Improve and ; (3) Transparency-first scenarios: Appropriately reduce But increase the Or the constraints of downstream risk refinement; (4) Downstream sensitive scenarios: Improve Requirements for controlling the discharge of fine materials.

[0122] ,but: ; for The adjustment amount, for The adjustment amount, for The adjustment amount, for The adjustment amount, for The adjustment amount, ={Security Priority, Sustainability Priority, Transparency Priority, Downstream Sensitivity} is a predefined set of scenarios; Let X be the membership degree (weight) of X to scene s, satisfying... It can be calculated based on the characteristics in X using fuzzy membership functions (such as trapezoidal or triangular functions); The standard adjustment vector corresponding to scene s is calibrated empirically or experimentally, for example: Safety First: (Right now Increase by 10%, Increase by 10%, (Reduce by 10, everything else remains the same) Sustainability First: ; Downstream sensitive: At the same time, an upper limit constraint on the discharge of fine particles is added.

[0123] If there is no overlap between multiple scenarios, the method corresponding to a single scenario can be used directly. The adjustment values ​​for each scenario can be determined based on engineering experience or by reverse calibration using prototype monitoring data.

Claims

1. A method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams, characterized in that, include: S1. Obtain the interception rate, velocity attenuation rate and peak flow reduction rate of the prefabricated permeable dam to be evaluated under debris flow. S2. With the interception rate on the horizontal axis and the speed attenuation rate and the peak flow reduction rate on the vertical axes respectively, establish an interception rate-speed attenuation rate matrix and an interception rate-peak flow reduction rate matrix; The performance space of each matrix is ​​divided into four quadrants based on the preset interception threshold and the preset significant reduction threshold. The working conditions that fall into the quadrant corresponding to both interception and significant reduction in the two matrices are identified as the candidate parameter combination set that meets both interception and significant reduction. S3. For the working conditions in the candidate parameter combination set, calculate their reservoir capacity retention coefficient. The reservoir capacity retention coefficient is obtained by multiplying the proportion of discharged material derived from the interception rate with the relative opening that characterizes the permeability of the dam body. Sort the working conditions according to the size of the reservoir capacity retention coefficient, retain the top few working conditions with the largest reservoir capacity retention coefficient, or retain the working conditions with the reservoir capacity retention coefficient greater than a preset threshold, to obtain the set of working conditions that pass the sustainable verification. S4. The solid particles of debris flow are divided into coarse particle segment, medium particle segment and fine particle segment according to particle size. Based on the proportion of each segment in the original sample, the mass weighted proportion of the equivalent coarse particle segment and fine particle segment in the whole pool is calculated for each working condition in the set of working conditions. Based on this, the coarse particle blocking efficiency, fine particle discharge efficiency and comprehensive coarse particle blocking and fine particle discharge index are calculated to obtain the particle sorting performance index of each working condition. S5. Following the three-step selection process of performance matrix screening, sustainability verification, and engineering constraint back-inference, based on the candidate parameter combination set, the performance ranking among the working conditions that have passed the sustainability verification, and the particle sorting performance of each working condition, back-infer and determine the recommended parameter window, including opening type, relative opening, number of grid layers, and relative interlayer spacing, and generate a parameter selection quick reference table.

2. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 1, characterized in that, Also includes: S6. Establish a closed-loop strategy for monitoring, diagnosis, and upgrading during operation. The interception rate, velocity attenuation rate, peak flow reduction rate, and reservoir capacity retention coefficient are used as core monitoring parameters. The dam's operating status is diagnosed based on the monitoring data, and corresponding structural adjustment measures are taken based on the adjustable characteristics of the prefabricated structure. After each structural adjustment measure is implemented, S1 to S4 are re-executed to re-evaluate the performance of the adjusted dam. The parameter selection quick reference table generated in S5 is updated based on the re-evaluation results. The cycle is iterated until the core monitoring parameters are restored to the preset target range.

3. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 1, characterized in that, In S2, the interception target is set to an interception rate of 60%, and the significant reduction target is set to a speed attenuation rate of 50% and a peak flow reduction rate of 50%. The four quadrants are specifically: a low interception and high reduction zone with an interception rate of less than 60% and a reduction index of 50% or higher; a high interception and high reduction zone with an interception rate of 60% or higher and a reduction index of 50% or higher; a low interception and low reduction zone with an interception rate of less than 60% and a reduction index of less than 50%; and a high interception and low reduction zone with an interception rate of 60% or higher and a reduction index of less than 50%. The candidate parameter combination set for interception target achievement and significant reduction is the set of conditions that simultaneously satisfy the condition of falling into the high interception and high reduction zone in both the interception rate-speed attenuation rate matrix and the interception rate-peak flow reduction rate matrix.

4. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 1, characterized in that, In S3, the reservoir capacity retention coefficient is specifically obtained by multiplying the difference between a certain value and the interception rate by the ratio of the width of the dam opening to the maximum particle size of the debris flow; wherein, the proportion of discharged material derived from the interception rate is characterized by the difference between a certain value and the interception rate, and the difference between a certain value and the interception rate is the inverse index of the reservoir capacity consumption rate; the relative opening is characterized by the ratio of the width of the dam opening to the maximum particle size of the debris flow, and the ratio of the width of the dam opening to the maximum particle size of the debris flow determines the potential for natural discharge of solid material; the sustainable verification also includes: statistically analyzing the proportion of the interception amount of each level of the grid in the multi-layer structure to the total interception amount, screening out the working conditions where the interception ratio of the first layer exceeds 97%, and preferentially retaining the working conditions where the interception ratio of the last layer is not less than 5%.

5. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 4, characterized in that, For prefabricated permeable sand-trapping dams with two or more layers of grid, S3 further includes calculating a modified reservoir capacity retention coefficient. The modified reservoir capacity retention coefficient is calculated by the reservoir capacity retention coefficient, the first-layer interception ratio representing the first-layer load, and the last-stage interception ratio representing the last-stage sharing capacity. Specifically, when the first-layer interception ratio increases, the modified reservoir capacity retention coefficient decreases accordingly; when the last-stage interception ratio increases, the modified reservoir capacity retention coefficient increases accordingly.

6. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 1, characterized in that, In S4, the coarse particle segment refers to particles with a diameter greater than 10 mm, the medium particle segment refers to particles with a diameter between 0.1 mm and 10 mm, and the fine particle segment refers to particles with a diameter less than 0.1 mm. The coarse particle interception efficiency is the ratio of the equivalent coarse particle segment ratio of the entire storage to the original coarse particle segment ratio; a value greater than 1 indicates that coarse particles are enriched in the storage. The fine particle discharge efficiency is 1 minus the ratio of the equivalent fine particle segment ratio of the entire storage to the original fine particle segment ratio; a larger value indicates that fine particles are discharged more fully. The comprehensive coarse particle interception and fine particle discharge index is obtained by subtracting the difference between 1 and the fine particle discharge efficiency and the coarse particle interception efficiency; a smaller value indicates better comprehensive coarse particle interception and fine particle discharge performance.

7. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 6, characterized in that, S4 also includes calculating the layered comprehensive coarse and fine discharge index for prefabricated permeable sand-trapping dams with two or more layers. The layered comprehensive coarse and fine discharge index is calculated by the coarse-trapping efficiency and fine-discharge efficiency of each layer according to the same rules. By comparing the changes in the values ​​of the layered comprehensive coarse and fine discharge index of each layer, when the value of the layered comprehensive coarse and fine discharge index of the last layer is lower than that of the first layer, it is determined that the multi-layer structure has played an effective progressive screening role.

8. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 7, characterized in that, In S5, the engineering constraint back-calculation also includes configuring the number of grid layers and the relative interlayer spacing based on the following linkage optimization rules: Define the inter-layer sorting synergy coefficient to characterize whether the value of the comprehensive coarse-blocking and fine-sorting index of each layer decreases as the layer number increases; Define the effective contribution coefficient of the final layer, which is calculated by the interception ratio of the final layer and the sorting efficiency of the final layer. When the interlayer sorting coordination coefficient shows that the comprehensive coarse interception and fine rejection index of each layer does not show a decreasing trend, and the interception ratio of the first layer exceeds the preset threshold, it is judged that the first layer is overloaded and the subsequent layers are ineffective, and adjustment measures such as increasing the relative interlayer spacing or improving the transparency of the first layer are taken. When the effective contribution coefficient of the final stage is lower than the preset threshold, and the difference between the comprehensive coarse-blocking and fine-draining index of the final stage layer and the previous stage layer is less than the preset value, it is determined that the final stage layer is redundant, and adjustment measures such as reducing the number of grid layers or adjusting the opening of the final stage are taken.

9. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 2, characterized in that, In S6, the specific rules for diagnosis are as follows: If the interception rate is detected to be lower than the preset interception threshold twice in a row, it is diagnosed as strong or difficult to establish passage. If the rate of increase in siltation in the reservoir exceeds the preset threshold or the decrease in the reservoir capacity retention coefficient exceeds 30% within the preset monitoring period, it is diagnosed as excessive flow obstruction leading to siltation concentration. If the concentration of fine particles downstream is continuously higher than the preset threshold, it is diagnosed as excessive final-stage fine particle removal. If local components of the dam are damaged or the impact response amplitude increases abnormally, it is diagnosed as insufficient bearing capacity of the local components.

10. The method for multi-objective performance evaluation and parameter selection of prefabricated permeable silt-trapping dams according to claim 9, characterized in that, In S6, the mapping relationship between the structural adjustment measures and the diagnostic conclusions is as follows: For diagnoses that are difficult to establish due to strong or blocked passage, measures such as increasing the number of grid layers, reducing the relative opening, or replacing with an opening type that has a higher coarsening efficiency can be taken. For diagnosing the problem of excessive flow obstruction leading to siltation, measures such as layered dredging, partial replacement of grating plates to restore opening size, increasing relative opening or optimizing relative interlayer spacing to enhance interlayer sharing effect are adopted. To address the diagnosis of excessive fine exhaust in the final stage, measures such as reducing the relative opening of the final stage grille or adjusting the opening type of the final stage are taken. For diagnoses of insufficient load-bearing capacity in local components, measures such as replacing damaged components or connectors are taken.

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