A beach ecological restoration groove dam optimization design method based on hydrodynamic simulation
By optimizing the design of channel dams through multi-source data processing and cluster classification, the problem of insufficient hydrodynamic coupling in traditional designs has been solved, achieving high-precision and high-efficiency eco-friendly beach restoration.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 秦皇岛华勘地质工程有限公司
- Filing Date
- 2026-05-08
- Publication Date
- 2026-06-26
AI Technical Summary
Traditional channel dam designs fail to effectively couple multiple hydrodynamic factors, have insufficient calculation accuracy, low optimization efficiency, lack of eco-friendliness, and cannot achieve integrated intelligent design, resulting in poor beach restoration effects.
By collecting multi-source datasets, performing preprocessing and clustering classification, calculating hydraulic reference values and terrain adaptation values for channel dams, optimizing and iterating the scheme, and combining visualization to achieve intelligent design.
It improves the accuracy of hydrological simulation, enhances the adaptability of channel dams, increases the efficiency of ecological restoration, enables real-time feedback, and avoids engineering failure and ecological damage.
Smart Images
Figure CN122287141A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of coastal engineering and ecological restoration technology, and more specifically, to a method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation. Background Technology
[0002] Beaches are vital ecological barriers and protective resources along the coast, serving functions such as shoreline protection, siltation, biological habitat, and scenic recreation. In recent years, affected by wave erosion, tidal currents, storm surges, sand source loss, and human activities, many beaches in my country have experienced problems such as shoreline retreat, beach narrowing, wetland degradation, and ecosystem damage. Channel bar structures are a core engineering measure for beach ecological restoration, aiming to stabilize the shoreline and restore habitats by altering nearshore hydrodynamic conditions and regulating sediment transport and deposition.
[0003] Traditional channel dam design mainly relies on empirical formulas, physical model tests, and manual calculations, which has significant shortcomings: First, it does not couple and simulate multiple hydrodynamic elements such as waves, tides, and storm surges, resulting in insufficient calculation accuracy; second, key parameters such as channel dam elevation, spacing, slope, and layout orientation rely on manual adjustment, leading to low optimization efficiency and poor adaptability; third, it lacks coordination and matching with topography, sand sources, and ecologically sensitive areas, which can easily cause localized erosion, ecological damage, and unsatisfactory restoration results; and fourth, it lacks automated decision-making and feedback mechanisms, making it impossible to evaluate the restoration effect in a timely manner.
[0004] While existing technologies have made some improvements in hydrological simulation or structural design, they are still unable to achieve integrated intelligent design that integrates "multi-source data acquisition, dynamic simulation calculation, scheme clustering and classification, parameter optimization and iteration, and effect analysis and feedback," thus failing to meet the needs of high-precision, high-efficiency, and eco-friendly beach restoration projects.
[0005] In view of this, the present invention proposes an optimization design method for beach ecological restoration trench dams based on hydrodynamic simulation to solve the above problems. Summary of the Invention
[0006] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: including: S1: Collect beach hydrological datasets, topographic datasets, and ecological datasets, and perform preprocessing; the hydrological datasets include wave data, tidal current data, storm surge data, and sediment transport data; the topographic datasets include shoreline slope, beach elevation, underwater topography data, and sediment source storage data; the ecological datasets include tidal flat vegetation distribution, benthic organism density, ecologically sensitive area range, and water environment quality data. S2: Process the hydrological dataset, topographic dataset, and ecological dataset to obtain hydraulic reference values and topographic adaptation values for the channel dam, and perform clustering and classification to obtain the classification results of the channel dam design scheme; S3: Optimize and iterate the classification results of the channel dam design schemes to obtain the optimal channel dam structural parameters and layout decision results; S4: Display the deployment decision results through a visualization display terminal, perform comprehensive analysis of hydrological datasets, topographic datasets, and ecological datasets, and obtain and display the analysis results of the restoration effect.
[0007] Furthermore, the preprocessing methods in S1 include data cleaning, outlier removal, noise removal, spatiotemporal interpolation completion, and dimensional normalization.
[0008] Furthermore, the hydraulic reference value of the S2 channel dam is calculated as follows: H = α・Hw + β・Hc + γ・Hs, where Hw is the wave influence coefficient, Hc is the tidal current influence coefficient, Hs is the storm surge influence coefficient, and α, β, and γ are the corresponding weighting factors.
[0009] Furthermore, the formula for calculating the terrain adaptation value in S2 is: T=δ・Tg+ε・Ts+ζ・Td, where Tg is the shoreline slope coefficient, Ts is the sand source replenishment coefficient, Td is the erosion and deposition intensity coefficient, and δ, ε, and ζ are the corresponding weighting factors.
[0010] Furthermore, the steps for establishing a classification model for channel dam design schemes in S2 include: collecting K sets of historical feature vectors as a sample set, dividing them into a 70% training set, a 15% test set, and a 15% validation set; pre-setting three data clusters: optimal ecological restoration, balanced type, and protection priority type; and using Euclidean distance calculation and K-means iterative clustering until convergence to obtain the classification model for channel dam design schemes.
[0011] Furthermore, the classification rules for the S2 channel dam design scheme are as follows: a preset comprehensive reference value threshold range (M1, M2) is defined; when the comprehensive reference value is less than M1, it is the optimal ecological restoration scheme; when the comprehensive reference value is greater than M1 and less than M2, it is a balanced scheme; when the comprehensive reference value is greater than M2, it is a protection-priority scheme.
[0012] Furthermore, the optimization objectives in S3 are to maximize ecological restoration benefits, optimize hydraulic stability, and minimize engineering costs; the optimization parameters include the elevation, top width, slope, spacing, layout orientation, and permeability of the channel dam.
[0013] Furthermore, the deployment decision results in S3 are divided into three levels: recommended plan, alternative plan, and avoidance plan, which correspond to the priority area for ecological restoration, the area of strong erosion, and the area of ecological sensitivity, respectively.
[0014] Furthermore, the repair effect analysis results in S4 are divided into excellent repair level, qualified repair level, and level requiring re-optimization.
[0015] Furthermore, S4 displays the following information: dam layout plan, hydrodynamic flow field diagram, scour and sedimentation prediction cloud map, and ecological restoration effect curve.
[0016] The technical effects and advantages of the present invention regarding the optimized design method of beach ecological restoration trench dams based on hydrodynamic simulation are as follows: This invention, through coupled processing of multi-source datasets from hydrology, topography, and ecology, obtains hydraulic reference values and topographic adaptation values for trench dams. These values directly reflect the degree of regional dynamic conditions and topographic suitability, significantly reducing the workload of manual calculations and trial-and-error. Clustering and classification enable automatic selection of design schemes, improving their rationality and relevance. Multi-objective optimization iteration yields optimal trench dam parameters, enhancing structural adaptability and ecological restoration efficiency. Visualization and effect analysis provide real-time feedback, preventing engineering failures and ecological damage. Overall, this invention offers significant advantages such as high accuracy in hydrological simulation, strong adaptability to trench dams, high efficiency in ecological restoration, and timely decision feedback. Attached Figure Description
[0017] Figure 1 This is a schematic diagram of an optimized design method for beach ecological restoration trench dams based on hydrodynamic simulation, according to the present invention. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] Please see Figure 1 As shown in this embodiment, a method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation includes: Step S1: Data Acquisition and Preprocessing Collect beach hydrological datasets, topographic datasets, and ecological datasets, and perform preprocessing.
[0020] The hydrological dataset includes: wave significant height, wave period, wave direction, and wave energy; tidal current velocity, direction, tidal level, and tidal range; storm surge increase, extreme water levels, and return period characteristics; and median sediment particle size, sediment concentration, sediment transport rate, and net sediment transport direction.
[0021] The topographic dataset includes: shoreline slope, beach elevation, underwater profile data, nearshore erosion and deposition rates, and sand source reserves and replenishment capacity.
[0022] The ecological dataset includes: tidal flat vegetation type, coverage, suitable growth slope and water depth; benthic organism density, biodiversity index; ecologically sensitive areas, prohibited engineering areas, and water environment quality indicators.
[0023] Preprocessing methods include: data cleaning, outlier removal, noise removal, spatiotemporal interpolation completion, and dimensional normalization.
[0024] Step S2: Data Processing and Solution Classification The hydrological, topographic, and ecological datasets were processed to obtain hydraulic reference values and topographic adaptation values for the channel dam. Clustering and classification were then performed to obtain the classification results for channel dam design schemes. The specific steps are as follows: Q1: The hydraulic reference value of the channel dam is obtained by substituting into the calculation formula: H=α・Hw+β・Hc+γ・Hs, where Hw is the wave influence coefficient, Hc is the tidal current influence coefficient, and Hs is the storm surge influence coefficient; α, β, and γ are the corresponding weighting factors.
[0025] Preset hydraulic threshold range (H1, H2): When the hydraulic reference value of the channel dam is greater than H1 and less than H2, the value is 1; when the hydraulic reference value of the channel dam is less than H1 or greater than H2, the value is 2.
[0026] Q2: The terrain adaptation value is obtained by substituting into the calculation formula: T=δ・Tg+ε・Ts+ζ・Td, where Tg is the shoreline slope coefficient, Ts is the sand source replenishment coefficient, and Td is the erosion and deposition intensity coefficient; δ, ε, and ζ are the corresponding weighting factors.
[0027] Q3: Collect K sets of historical feature vectors as a sample set, and divide the sample set into a 70%K training set, a 15%K test set, and a 15%K validation set; the feature vector is a combination of the hydraulic reference value of the channel dam and the terrain adaptation value.
[0028] Q4: Establish a classification model for dam design schemes based on the sample set, and obtain historical feature vectors in the training set; preset the optimal ecological restoration scheme cluster L1, the balanced scheme cluster L2, and the protection priority scheme cluster L3; randomly select three data points in the training set as the first cluster center, representing the three scheme clusters respectively.
[0029] Q5: The distance between data items is obtained using the Euclidean distance formula: d=√[∑(x -y ) 2 Where x y Let be the value of two data points in the i-th sub-data item, where i is the number of sub-data items. Calculate the distance between each data item in the training set and the three cluster centers, assign the data item to the nearest cluster, and obtain a new cluster set as the second cluster center.
[0030] Q6: Calculate the mean of the three new clusters in the second cluster center, and use them as the new first cluster center to calculate again.
[0031] Q7: Repeat Q5 and Q6 until the preset number of iterations is reached to obtain the classification model of the channel dam design scheme.
[0032] Q8: Input the feature vector of the area to be designed into the classification model, and output the comprehensive reference value of the channel dam design scheme.
[0033] The classification methods include: a preset threshold range (M1, M2); when the comprehensive reference value is less than M1, an optimal ecological restoration scheme signal is generated; when the comprehensive reference value is greater than M1 and less than M2, a balanced scheme signal is generated; when the comprehensive reference value is greater than M2, a protection priority scheme signal is generated.
[0034] By packaging the above signals, we obtain the classification results of the channel dam design scheme.
[0035] Step S3: Solution Optimization and Decision Output The classification results of the channel dam design schemes were optimized and iteratively processed to obtain the optimal channel dam structural parameters and layout decision results. With the goals of maximizing ecological restoration benefits, optimizing hydraulic stability, and minimizing engineering costs, the elevation, crest width, inner and outer slope ratio, spacing, layout orientation, and permeability of the channel dam were iteratively optimized.
[0036] The constraints include: prohibition of deployment in ecologically sensitive areas, minimum scour depth limit, maximum allowable siltation rate, and suitable vegetation growth range.
[0037] After optimization and convergence, the output is a three-level deployment decision: Recommended approach: Applicable to priority ecological restoration areas, offering the highest ecological benefits and best siltation-promoting effect; Alternative solution: Suitable for areas with strong erosion, with strong wave and erosion resistance and high structural stability; Alternative solutions: Applicable to ecologically sensitive areas or areas with severe dynamic conditions, it is recommended to adopt alternative measures such as sand replenishment and vegetation planting.
[0038] Step S4: Visualization and Effect Analysis The optimal layout decision, dam layout diagram, hydrodynamic flow field, and scour and sedimentation prediction cloud map are displayed through a visualization terminal.
[0039] A comprehensive analysis of hydrological, topographic, and ecological datasets is conducted: preset data standard threshold interval groups are used to compare indicators such as waves, tidal currents, sediment, slope, and vegetation into the corresponding threshold intervals to obtain three levels of results: healthy, abnormal, and warning.
[0040] Judgment rules: All indicators are healthy: Excellent recovery level; 1-2 indicators are abnormal, the rest are healthy: qualified repair level; One or more indicators trigger a warning: the solution needs to be optimized again.
[0041] Package the results that are excellent, qualified, or require further optimization, obtain the final repair effect analysis results, and display them.
[0042] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.
[0043] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for users of ordinary technical skills, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.
Claims
1. A method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation, characterized in that, include: S1: Collect beach hydrological datasets, topographic datasets, and ecological datasets, and perform preprocessing; Hydrological datasets include wave data, tidal current data, storm surge data, and sediment transport data; The topographic dataset includes shoreline slope, beach elevation, underwater topographic data, and sand source storage data; the ecological dataset includes tidal flat vegetation distribution, benthic organism density, ecologically sensitive area range, and water environment quality data. S2: Process the hydrological dataset, topographic dataset, and ecological dataset to obtain hydraulic reference values and topographic adaptation values for the channel dam, and perform clustering and classification to obtain the classification results of the channel dam design scheme; S3: Optimize and iterate the classification results of the channel dam design schemes to obtain the optimal channel dam structural parameters and layout decision results; S4: Display the deployment decision results through a visualization display terminal, perform comprehensive analysis of hydrological datasets, topographic datasets, and ecological datasets, and obtain and display the analysis results of the restoration effect.
2. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The preprocessing methods in S1 include data cleaning, outlier removal, noise removal, spatiotemporal interpolation completion, and dimensional normalization.
3. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The formula for calculating the hydraulic reference value of the S2 channel dam is: H = α・Hw + β・Hc + γ・Hs, where Hw is the wave influence coefficient, Hc is the tidal current influence coefficient, Hs is the storm surge influence coefficient, and α, β, and γ are the corresponding weighting factors.
4. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that... The formula for calculating the terrain adaptation value in S2 is: T = δ・Tg + ε・Ts + ζ・Td, where Tg is the shoreline slope coefficient, Ts is the sand source replenishment coefficient, Td is the erosion and deposition intensity coefficient, and δ, ε, and ζ are the corresponding weighting factors.
5. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The steps for establishing a classification model for channel dam design schemes in S2 include: collecting K sets of historical feature vectors as a sample set, dividing them into a 70% training set, a 15% test set, and a 15% validation set; pre-setting three data clusters: optimal ecological restoration, balanced type, and protection priority type; and using Euclidean distance calculation and K-means iterative clustering until convergence to obtain the classification model for channel dam design schemes.
6. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The classification rules for the S2 channel dam design scheme are as follows: a preset comprehensive reference value threshold range (M1, M2) is used; when the comprehensive reference value is less than M1, it is the optimal ecological restoration scheme; when the comprehensive reference value is greater than M1 and less than M2, it is a balanced scheme; when the comprehensive reference value is greater than M2, it is a protection priority scheme.
7. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The optimization objectives in S3 are to maximize ecological restoration benefits, optimize hydraulic stability, and minimize engineering costs; the optimization parameters include the elevation, top width, slope, spacing, orientation, and permeability of the dam.
8. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The deployment decision results in S3 are divided into three levels: recommended plan, alternative plan, and avoidance plan, which correspond to the priority area for ecological restoration, the area of strong erosion, and the area of ecological sensitivity, respectively.
9. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The repair effect analysis results in S4 are divided into excellent repair level, qualified repair level, and level that needs to be re-optimized.
10. The method for optimizing the design of beach ecological restoration trench dams based on hydrodynamic simulation according to claim 1, characterized in that, The content displayed in S4 includes the plan layout of the channel dam, the hydrodynamic flow field map, the scour and sedimentation prediction cloud map, and the ecological restoration effect curve.