Method and device for analyzing performance of cemented rubble protection structure, equipment and medium

Abstract

This invention proposes a performance analysis method, apparatus, equipment, and medium for cemented riprap protective structures, relating to the field of performance testing technology for cemented riprap protective structures. Addressing the shortcomings of existing technologies in studying gridded cemented riprap, such as the disconnect between macroscopic scour morphology and material performance evolution, and the inability of short-term test results to reflect performance degradation over decades of service, which prevents the establishment of a quantitative relationship between material degradation and structural failure and hinders long-term protective performance prediction, this invention obtains scour pit volume evolution data through flue model tests, establishes a strength attenuation model by combining it with material erosion tests, equates scour damage under wave-current loading to material erosion time, and corrects material strength in real time based on the equivalent damage age, ultimately constructing a scour pit development rate model to predict long-term protective performance.

Description

Technical Field

[0001] This invention relates to the field of performance testing technology for cemented riprap protective structures, and in particular to a performance analysis method, apparatus, equipment, and medium for cemented riprap protective structures. Background Technology

[0002] Offshore wind power, as a crucial component of clean energy, hinges on the long-term safety and stability of its foundation structure. Grid-bonded riprap is a relatively new erosion control technology that involves laying stone units bonded with a specific cementing material around the foundation to form a holistic protective layer with a grid-like structure. This technology combines the flexibility and adaptability of traditional riprap with the overall stability of concrete structures. However, current research on this technology is still in its early stages and exhibits significant limitations.

[0003] Most existing studies verify the instantaneous stability under extreme wave and current conditions through short-term flume tests. However, these methods have two major drawbacks:

[0004] The macroscopic and microscopic aspects are disconnected: either only macroscopic morphology such as the size of scour pits is measured, or only the initial mechanical properties of materials are tested, failing to establish a quantitative connection between the two, and making it impossible to infer structural failure from material degradation.

[0005] Disconnect between short-term and long-term: Short-term test results cannot reflect the performance degradation of a structure over a decades-long service life due to material fatigue, corrosion, etc., making it difficult to make effective long-term stability predictions.

[0006] These issues constrain the optimal design and safety assessment of gridded cemented riprap, necessitating a new method that can correlate macroscopic and microscopic performance and predict its long-term service behavior. Summary of the Invention

[0007] To address the shortcomings of existing research on gridded cemented riprap, such as the disconnect between macroscopic scour morphology and material property evolution, and the inability of short-term test results to reflect performance degradation over decades of service, which prevents the establishment of a quantitative relationship between material degradation and structural failure and hinders long-term protective performance prediction, this invention proposes a performance analysis method for cemented riprap protective structures, including:

[0008] The scour evolution data of the cemented riprap protective structure under wave load obtained from the water tank model test is obtained. The scour evolution data includes the time series of scour pit volume.

[0009] To obtain the initial mechanical data of cemented paved stone materials and the mechanical property data of cemented paved stone samples at different erosion ages obtained from material tests;

[0010] Based on the initial mechanical data and the mechanical property data, a strength reduction factor model is constructed to characterize the strength degradation of cemented paved stone materials with erosion time.

[0011] The equivalent damage age of the cemented riprap protective structure under wave scouring is calculated based on the scouring evolution data and the corresponding wave load data.

[0012] The real-time equivalent strength of the cemented riprap material is determined based on the equivalent damage age and the strength reduction coefficient model.

[0013] Based on the real-time equivalent strength, a scour pit development rate model is constructed to predict the scour pit development process and protection cycle of the cemented riprap protection structure under long-term wave and current action.

[0014] Furthermore, the initial mechanical data includes the initial strength of the cemented riprap material, and the mechanical property data includes the post-erosion strength of the cemented riprap material at different erosion ages. The construction of a strength reduction coefficient model characterizing the strength degradation of the cemented riprap material over erosion time based on the initial mechanical data and the mechanical property data includes:

[0015] The strength reduction factor for each age is calculated based on the formula: λ(t) = Q(t) / Q(0), where λ(t) is the strength reduction factor, Q(0) is the initial strength, and Q(t) is the strength after erosion.

[0016] A nonlinear regression method was used to fit multiple intensity reduction coefficients to obtain a functional relationship model between the intensity reduction coefficients and the equivalent erosion time: λ(t)=A×exp(-B×t)+C, where A is the magnitude of intensity decay, B is the rate of intensity decay, C is the lower limit of intensity decay, and t is the erosion time.

[0017] Furthermore, the wave-current load data includes wave height and flow velocity time series data. The calculation of the equivalent damage age of the cemented riprap protective structure under wave-current scouring based on the scour evolution data and the corresponding wave-current load data includes:

[0018] The bed shear stress within each time step is calculated based on wave height and flow velocity time series data.

[0019] The equivalent damage increment for each time step is calculated based on the formula ΔTs=k1×(τ-τ0)×Δt, where ΔTs is the equivalent damage increment, τ0 is the stress threshold, τ is the bed shear stress within the time step, k1 is the damage equivalence coefficient, and Δt is the time step. The damage equivalence coefficient is determined based on scour evolution data.

[0020] The equivalent damage increments are accumulated to obtain the cumulative equivalent damage age T=ΣΔTs at any scouring time.

[0021] Furthermore, the damage equivalence coefficient is determined based on scour evolution data, including:

[0022] The observed scour rate was calculated based on the time series of the scour pit volume.

[0023] Construct a prediction model for the scour rate: dV1 / dt=k×(τ-τ0) / λ(t), where dV1 / dt is the predicted scour rate, k is the scour rate coefficient, and λ(t) is the intensity reduction coefficient;

[0024] With the goal of minimizing the error between the predicted scour rate and the observed scour rate, an optimization algorithm is used to simultaneously adjust k1 and k to obtain the calibrated damage equivalence coefficient k1.

[0025] Furthermore, the optimization algorithm employs the least squares method or a genetic algorithm.

[0026] Furthermore, the construction of the scour pit development rate model based on the real-time equivalent intensity includes:

[0027] Construct a real-time equivalent intensity scour pit development rate model:

[0028] , where dV2 / dt is the equivalent strength scour pit volume development rate, S(t) is the real-time equivalent strength, k2 is the scour strength coefficient, and N is the strength influence index.

[0029] Furthermore, the method also includes:

[0030] Compare the predicted protection period with the target lifespan;

[0031] If the predicted protection period does not meet the target lifespan, the parameters of the cemented paved stone material in the protection structure are adjusted, and the steps of obtaining the initial mechanical data of the cemented paved stone material and the mechanical property data of the cemented paved stone samples at different erosion ages obtained from material tests are re-executed to construct a scour pit development rate model based on the real-time equivalent strength. Iterative optimization is carried out until a set of cemented paved stone material parameters that meets the protection lifespan requirements and has the best cost is found.

[0032] A performance analysis device for cemented riprap protective structures, the device employing the performance analysis device for cemented riprap protective structures as described in any of the preceding claims, specifically comprising the following modules:

[0033] The first acquisition module is used to acquire the scour evolution data of the cemented riprap protective structure under wave load obtained from the water tank model test. The scour evolution data includes the time series of scour pit volume.

[0034] The second acquisition module is used to acquire the initial mechanical data of cemented paved stone materials and the mechanical property data of cemented paved stone samples at different erosion ages obtained from material tests.

[0035] The first construction module, connected to the second acquisition module, is used to construct a strength reduction coefficient model characterizing the strength degradation of cemented paved material with erosion time based on the initial mechanical data and the mechanical performance data.

[0036] The calculation module, connected to the first acquisition module, is used to calculate the equivalent damage age of the cemented riprap protective structure under wave scouring based on the scouring evolution data and the corresponding wave load data.

[0037] A determination module, connected to the first construction module and the calculation module, is used to determine the real-time equivalent strength of the cemented riprap material based on the equivalent damage age and the strength reduction coefficient model.

[0038] The second construction module, connected to the determining module, is used to construct a scour pit development rate model based on the real-time equivalent intensity, so as to predict the scour pit development process and protection cycle of the cemented riprap protection structure under long-term wave current action.

[0039] An electronic device includes a processor and a memory, wherein the processor is coupled to the memory;

[0040] The processor is used to execute a computer program stored in the memory, so that the electronic device performs a performance analysis method for a cemented riprap protective structure as described in any of the preceding claims.

[0041] A computer-readable storage medium includes a computer program or instructions that, when executed on a computer, cause the computer to perform a performance analysis method for a cemented riprap protective structure as described above.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0043] Data on the volume evolution of scour pits were obtained through flume model tests. A strength attenuation model was established by combining material erosion tests. Scour damage under wave load was equivalent to material erosion time. Material strength was corrected in real time based on the equivalent damage age. A scour pit development rate model was constructed. The long-term protective performance of cemented riprap protective structures was predicted by the scour pit development rate model. Attached Figure Description

[0044] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0045] Figure 1 This is a flowchart illustrating the performance analysis method of a cemented riprap protective structure in Example 1;

[0046] Figure 2 This is a structural block diagram of a performance analysis device for a cemented riprap protective structure as shown in Example 2;

[0047] Figure 3 This is a structural block diagram illustrating an electronic device in Example 3. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0049] The specific embodiments of the present invention are described below. Addressing the long-term stability issues caused by wave and current erosion in offshore wind power foundation protection structures, gridded cemented riprap, as an emerging protection technology, has seen research primarily focused on short-term flue tests to verify immediate stability. Existing methods suffer from drawbacks such as a disconnect between macroscopic erosion morphology and material performance evolution, and the inability of short-term test results to reflect performance degradation over decades of service. This makes it impossible to establish a quantitative relationship between material degradation and structural failure, hindering long-term protection performance prediction. The present invention obtains erosion pit volume evolution data through flue model tests, establishes a strength attenuation model by combining it with material erosion tests, equates erosion damage under wave and current loads to material erosion time, and corrects material strength in real-time based on the equivalent damage age. Finally, a erosion pit development rate model is constructed to predict the long-term protection performance of the cemented riprap structure.

[0050] Example 1

[0051] like Figure 1 As shown, this invention proposes a performance analysis method for cemented riprap protective structures, which specifically includes the following steps:

[0052] Step S1: Obtain the scour evolution data of the cemented riprap protective structure under wave and current load obtained from the water tank model test. The scour evolution data includes the time series of scour pit volume.

[0053] In this embodiment, the scour evolution data was obtained through a large-scale wave flume model test. The test equipment included a large wave flume with dimensions of 456m×5m×12m, equipped with a computer-controlled wave generation system and a circulation flow generation system to simulate regular waves, irregular waves, and wave-current coupling conditions.

[0054] A cemented riprap protective structure model was set up in a large wave flume, and a scouring test was conducted under the action of wave current. A three-dimensional laser scanner was used to scan the scouring terrain to obtain the sequential data of the scouring pit volume changing over time, i.e., scouring evolution data. At the same time, the flow velocity and wave height were monitored in real time using an acoustic Doppler point velocity meter and a capacitive wave height meter to form wave current load time series data.

[0055] The wave-generating system includes a wave generator, which can be a motor servo-driven push-plate absorption wave generator that can produce regular and irregular waves. Both ends of the large wave tank are equipped with wave-damping devices, and the two ends of the tank are connected by pipes to keep the water level on both sides of the model constant during the test.

[0056] Irregular waves are simulated using a spectrum, with the JONSWAP spectrum used as the analytical expression:

[0057] ;

[0058] In the formula: ;

[0059] ;

[0060] ;

[0061] in, In this embodiment, the peak factor is used as the spectral peak factor. The value is 3.3; It refers to the peak frequency, specifically the period of the spectral peak frequency. The reciprocal of; Spectral density; For significant wave height; For frequency, For the average period, For frequency coefficients, The peak coefficient is used to input the given effective wave height and period into the computer for wave spectrum simulation. After correction, the spectral density, peak frequency, spectral energy, and effective wave height near the peak frequency meet the requirements of the "Wave Model Test Procedure" (JTJ / T234-2001).

[0062] That is: (1) the allowable deviation of the total energy of the wave spectrum is ±10%; (2) the allowable deviation of the peak frequency simulation value is ±5%; (3) the allowable deviation of the spectral density distribution is ±15% within the range where the spectral density is greater than or equal to 0.5 times the peak value of the spectral density; (4) the allowable deviation of the effective wave height, effective wave period or spectral peak period is ±5%; (5) the allowable deviation of the 1% cumulative frequency wave height and the ratio of effective wave height to average wave height in the simulated wave train is ±15%.

[0063] Multiple operating condition tests: Extreme events: Simulate extreme storm surge conditions in the target sea area once every 50 years and once every 100 years: Simulate typical and frequently encountered wave and current conditions over several years or even decades, and conduct long-term cyclic loading to observe the cumulative damage effect.

[0064] Table 1 shows the experimental parameters for different events.

[0065] Table 1

[0066]

[0067] In this embodiment, an array-type wave height meter and an acoustic Doppler current meter are used to synchronously collect time series data of wave height and current velocity around the model pile at a frequency of not less than 10Hz. Before the test, after extreme events, and at multiple key intervals of long-term cyclic loading, such as after 1 year, 5 years, and 10 years of equivalent simulation, a high-precision three-dimensional laser scanner is used to perform full-section scanning of the terrain around the pile. The terrain models at different time points are compared using point cloud data processing software to quantify the time-varying development of the scour pit. Key indicators include: total volume of the scour pit, maximum scour depth, and planar distribution morphology of the scour pit.

[0068] Step S2: Obtain the initial mechanical data of the cemented paved stone material and the mechanical property data of the cemented paved stone samples at different erosion ages obtained from material tests.

[0069] In this embodiment, uniaxial and triaxial compression tests were performed on the original cemented riprap protective structure specimen to obtain the initial uniaxial compressive strength, i.e., the initial mechanical data.

[0070] To accelerate the simulation of seawater chemical erosion and physical dissolution, cemented riprap protective structure samples were immersed in a high-concentration NH4NO3 solution, with multiple erosion ages set, such as 0h, 6h, 12h, 24h, and 48h. At the end of each age, the cemented riprap protective structure samples were removed, the surfaces were wiped dry, and uniaxial compression tests were immediately conducted to test their residual uniaxial compressive strength, i.e., mechanical property data.

[0071] Step S3: Based on the initial mechanical data and the mechanical property data, construct a strength reduction coefficient model to characterize the strength degradation of cemented paved stone material over erosion time.

[0072] Step S3 specifically includes: calculating the intensity reduction coefficient for each age based on the formula: λ(t) = Q(t) / Q(0), where λ(t) is the intensity reduction coefficient, Q(0) is the initial intensity, and Q(t) is the intensity after erosion; fitting multiple intensity reduction coefficients using a nonlinear regression method to obtain the functional relationship model between the intensity reduction coefficient and the equivalent erosion time: λ(t) = A × exp(-B × t) + C, where A is the magnitude of intensity decay, B is the rate of intensity decay, C is the lower limit of intensity decay, and t is the erosion time.

[0073] In this embodiment, the strength reduction coefficient at the corresponding time point is obtained by calculating the ratio of the uniaxial compressive strength at different erosion ages to the initial strength. For example, the strength of the cemented paved concrete protective structure sample with an erosion time of 30 days is measured to be 75% of the initial strength, and the corresponding λ(30) = 0.75. Then, the reduction coefficient data at each time point is imported into the nonlinear regression model. By minimizing the sum of squared residuals between the predicted value and the measured value, the parameters A, B, and C in the exponential function are determined. The strength reduction coefficient model characterizes the degradation law of the cemented paved concrete material strength as it first rapidly decays and then tends to stabilize with the erosion time. Among them, the exponential term exp(-B×t) describes the strength loss of the material in the early stage due to the dissolution effect, and the constant term C represents the proportion of the residual strength when the material reaches a stable state.

[0074] Among them, A, B, and C can be determined in the following way: Prepare a set of identical cemented riprap protective structure specimens, place the cemented riprap protective structure specimens in an accelerated testing device that simulates the field erosion environment, such as acidic water, salt water immersion, wet-dry cycle, etc., and erode them for different times t, such as 0 days, 30 days, 60 days, 90 days, and 180 days, where t=0 is the initial state, and conduct uniaxial compressive strength tests on each set of cemented riprap protective structure specimens that have reached the predetermined erosion time to obtain multiple strength values ​​Q(t).

[0075] For each erosion age, the intensity reduction factor is calculated: λ(t) = Q(t) / Q(0), thus obtaining multiple sets of time intensity data (t1, λ1), (t2, λ2), ..., (tn, λn). The data (t1, λ1), (t2, λ2), ..., (tn, λn) are input into the corresponding analysis software for nonlinear regression analysis. The model to be fitted is specified as: λ(t) = A × exp(-B × t) + C. An iterative algorithm, such as the least squares method, is used to find the optimal values ​​of A, B, and C, so that the sum of errors between the curve of the functional relationship model of intensity reduction factor and equivalent erosion time and all experimental data points is minimized. When fitting, the constraint condition A + C = 1 can be added to ensure the accuracy of the functional relationship model of intensity reduction factor and equivalent erosion time in a physical sense. There is no reduction in the initial state.

[0076] Step S4: Calculate the equivalent damage age of the cemented riprap protective structure under wave scouring based on the scouring evolution data and the corresponding wave load data.

[0077] Step S4 specifically includes: calculating the bed shear stress within each time step based on wave height and flow velocity time series data; calculating the equivalent damage increment for each time step based on the formula ΔTs=k1×(τ-τ0)×Δt, where ΔTs is the equivalent damage increment, τ0 is the stress threshold, τ is the bed shear stress within the time step, k1 is the damage equivalence coefficient, and Δt is the time step, the damage equivalence coefficient being determined based on scour evolution data; and accumulating the equivalent damage increments to obtain the cumulative equivalent damage age T(t)=ΣΔTs at any scour moment.

[0078] The bed shear stress is the tangential stress acting on the surface of the cemented riprap protective structure under the combined action of water flow and waves. It can be calculated using fluid dynamics formulas combined with measured wave height and flow velocity data. For example, the formula τ=ρu² can be used, where ρ is the fluid density, u is the near-bottom flow velocity, and τ is used to quantify the direct mechanical action of wave load on the protective structure. The equivalent damage increment is the transformation of the damage caused to the material by wave loads of different intensities into the equivalent time dimension of damage. It can be quantified by multiplying the difference between the instantaneous shear stress and the threshold stress by the time step. For example, when the measured shear stress exceeds the threshold, the damage increment is positively correlated with the over-limit amplitude and duration. The equivalent damage increment realizes the correlation mapping between dynamic load and material damage. The damage equivalence coefficient is a correlation factor characterizing the material damage rate and the change of mechanical parameters. It can be determined by joint calibration of scour test data and material performance data. For example, in the experiment, the volume change of the scour pit and the material strength data are collected simultaneously, and the damage equivalence coefficient value is determined by the inverse optimization algorithm. The damage equivalence coefficient ensures the physical authenticity of the damage accumulation model.

[0079] In this embodiment, the wave load is first converted into a quantifiable shear stress parameter through fluid dynamics calculations. Then, a mathematical relationship is established between the shear stress exceeding the limit and the equivalent damage increment, converting the dynamic wave load into a damage accumulation in the time dimension. Finally, the damage increment at the discrete time step is converted into a continuous damage age parameter through integral calculation. For example, under high wave and high load conditions during typhoon season, when the bed shear stress continuously exceeds the threshold, the accumulation rate of the equivalent damage age is significantly accelerated, thus reflecting the accelerated damage effect of extreme loads on the protective structure.

[0080] The damage equivalence coefficient is determined based on scour evolution data, including: calculating the observed scour rate based on the scour pit volume time series; constructing a predicted scour rate model: dV1 / dt=k×(τ-τ0) / λ(t), where dV1 / dt is the predicted scour rate, k is the scour rate coefficient, and λ(t) is the intensity reduction coefficient; with the goal of minimizing the error between the predicted scour rate and the observed scour rate, an optimization algorithm is used to simultaneously adjust k1 and k to obtain the calibrated damage equivalence coefficient k1. The optimization algorithm adopts the least squares method or a genetic algorithm.

[0081] The damage equivalence coefficient is a conversion parameter that transforms the actual physical scouring effect generated by wave current load into an equivalent material damage time. It can be achieved by backfitting the scouring rate prediction model with the measured scouring pit volume change data. The damage equivalence coefficient is used to quantify the accelerating effect of wave current load on material performance degradation. The scouring rate coefficient is a proportional parameter that reflects the relationship between bed shear stress and scouring rate. It can be determined by establishing a linear regression model of the difference between scouring rate and shear stress. The scouring rate coefficient is used to characterize the contribution of unit shear stress increment to scouring rate.

[0082] In this embodiment, the time series of scour pit volume is obtained through three-dimensional scanning or volume measurement devices in a water tank test. For example, a laser rangefinder is used to record the scour pit morphology data at fixed intervals. The scour rate is calculated by dividing the volume difference between adjacent time points by the time step. In the scour rate prediction model, the shear stress threshold τ0 can be determined by a critical start-up test. For example, the flow velocity is gradually increased under still water conditions until the stone is displaced. The strength reduction coefficient λ(t) is calculated by substituting the equivalent damage age T into the strength reduction coefficient model. During the optimization process, k1 and k are adjusted synchronously as undetermined parameters. For example, the parameter value range is set in the genetic algorithm and an initial population is generated. The root mean square error between the predicted scour rate and the measured value is evaluated by the fitness function. After multiple generations of evolution, the optimal parameter combination is selected.

[0083] Among them, the least squares method is a method to solve for the optimal parameters by minimizing the sum of the squared differences between the predicted and observed values. It can be achieved by constructing an error function matrix and solving for its extreme points. The genetic algorithm is a global optimization algorithm that simulates the biological evolution process. It uses operations such as selection, crossover, and mutation to search for the optimal solution in the parameter space. The above two algorithms play the roles of local precise optimization and global search, respectively, in the parameter calibration process. They can effectively solve the complex nonlinear matching problem between the scour rate prediction model and the measured data.

[0084] In this embodiment, during the process of synchronously adjusting the damage equivalence coefficient k1 and the scour rate coefficient k, when the least squares method is used, the sum of squared residuals between the scour rate prediction model and the measured data is constructed as the objective function, and the parameters are iteratively updated until convergence is achieved through the gradient descent method. When the genetic algorithm is used, the parameter combination is encoded as a chromosome population, and after evaluation by the fitness function, a new generation of population is generated through genetic operations. The process is iterated until the optimal parameter set that meets the error threshold is obtained.

[0085] Step S5: Determine the real-time equivalent strength of the cemented paving stone material based on the equivalent damage age and the strength reduction coefficient model.

[0086] In this embodiment, T(t) is substituted into λ(t) = A × exp(-B × t) + C to obtain the real-time equivalent strength S(t) = λ(T(t)) × S(0) of the cemented paving material at the current moment, where S(0) is the initial strength of the material.

[0087] Step S6: Construct a scour pit development rate model based on the real-time equivalent strength to predict the scour pit development process and protection cycle of the cemented riprap protection structure under long-term wave and current action.

[0088] Step S6 specifically includes: constructing a real-time equivalent intensity scour pit development rate model: First calculate S(t) raised to the power of N, then calculate K2 divided by... Where dV2 / dt is the equivalent strength scour pit volume development rate, S(t) is the real-time equivalent strength, k2 is the scour strength coefficient, and N is the strength influence index.

[0089] Among them, the real-time equivalent strength is the actual erosion resistance of cemented riprap material after being eroded and damaged during wave scouring; the scouring strength coefficient is a proportional parameter related to the scouring performance of the material, which can be determined by minimizing the error between the flue test data and the model prediction value. The scouring strength coefficient characterizes the scouring resistance of a specific material under unit strength; the strength influence index is a parameter indicating the sensitivity of the scouring rate to the change in material strength. It can be expressed in the form of a power function to express the nonlinear influence of strength decay on scouring development. The strength influence index can be determined by comparative scouring tests of specimens with different strength grades.

[0090] In this embodiment, after obtaining the time series of real-time equivalent strength, a negative correlation model between scour rate and real-time strength is established to dynamically reflect the accelerating effect of material strength decay on scour development. For example, when the material strength decreases to 50% of the initial value due to chemical erosion, the scour rate increases to twice the initial state. The determination of parameters k2 and N in the real-time equivalent strength scour pit development rate model is combined with the scour pit volume development data observed in the flue model test, and a nonlinear regression method is used for joint inversion to ensure the consistency between the scour pit development rate model prediction results and the measured data.

[0091] In this embodiment, the development rate of the scour pit volume at each time point is calculated by constructing a scour pit development rate model using real-time equivalent intensity. Starting from time zero, the instantaneous scour rate at each time point is accumulated to obtain a complete curve of the scour pit volume changing with time. This curve describes the entire historical process from nothing to something, and from slow to fast development speed.

[0092] The protection period is the effective service life of the cemented riprap protection structure. When the volume of the scour pit reaches the critical scour volume, the cemented riprap protection structure is considered to have failed. Critical scour volume: When the volume of the scour pit reaches a preset value, the structure is considered to have failed. The time point corresponding to the critical scour volume on the curve is determined, and the determined time point is the predicted protection period. The critical scour volume is set in advance.

[0093] This embodiment also includes: comparing the predicted protection period with the target life; if the predicted protection period does not meet the target life, adjusting the cemented paving material parameters of the protective structure, and re-executing the steps of obtaining the initial mechanical data of the cemented paving material and the mechanical property data of the cemented paving sample at different erosion ages obtained from material tests to construct a scour pit development rate model based on the real-time equivalent strength, performing iterative optimization until a cemented paving material parameter set that meets the protection life requirements and has the best cost is found.

[0094] Among them, the target life refers to the pre-set service life requirement of the protective structure, which can be determined by engineering design requirements or standard specifications, such as 20 years or 30 years. Adjusting the cemented rubble material parameters of the protective structure refers to modifying variables that affect the material strength, such as the cementitious material ratio, aggregate particle size, or curing process. Orthogonal experimental methods or numerical simulation methods can be used to screen parameter combinations. Changing the material ratio directly affects the strength decay rate and erosion resistance. Iterative optimization refers to gradually approaching the optimal solution that meets the life and cost constraints by iteratively executing steps S2 to S6. Gradient descent algorithm or multi-objective optimization algorithm can be used to achieve this. A balance between performance and cost can be achieved through multiple parameter adjustments and model verification.

[0095] In this embodiment, after predicting the development process of the scour pit, the calculated results are compared with the preset target life. If the predicted life is insufficient, the material parameters need to be adjusted in reverse. For example, the amount of cementitious material can be increased to enhance erosion resistance, or the aggregate gradation can be optimized to reduce the scour rate. The adjusted parameters need to be re-entered into the material testing process to obtain new mechanical data, and the strength reduction factor model and the scour pit development rate model can be updated. The life prediction is then performed again. This process is repeated until a parameter combination that meets the target life and has the lowest material cost is selected. For example, when the initial predicted life is 15 years, which is lower than the target of 20 years, the proportion of cementitious material can be gradually increased until the predicted life meets the target. At the same time, the material cost under different ratios is recorded, and finally, the ratio scheme with the lowest cost under the condition of meeting the life is selected.

[0096] Example 2

[0097] like Figure 2 As shown, the present invention also proposes a performance analysis device based on a cemented riprap protective structure, using a performance analysis method for a cemented riprap protective structure as described in any one of Examples 1, comprising the following modules:

[0098] The first acquisition module is used to acquire the scour evolution data of the cemented riprap protective structure under wave load obtained from the water tank model test. The scour evolution data includes the time series of scour pit volume.

[0099] The second acquisition module is used to acquire the initial mechanical data of cemented paved stone materials and the mechanical property data of cemented paved stone samples at different erosion ages obtained from material tests.

[0100] The first construction module, connected to the second acquisition module, is used to construct a strength reduction coefficient model characterizing the strength degradation of cemented paved material with erosion time based on the initial mechanical data and the mechanical performance data.

[0101] The calculation module, connected to the first acquisition module, is used to calculate the equivalent damage age of the cemented riprap protective structure under wave scouring based on the scouring evolution data and the corresponding wave load data.

[0102] A determination module, connected to the first construction module and the calculation module, is used to determine the real-time equivalent strength of the cemented riprap material based on the equivalent damage age and the strength reduction coefficient model.

[0103] The second construction module, connected to the determining module, is used to construct a scour pit development rate model based on the real-time equivalent intensity, so as to predict the scour pit development process and protection cycle of the cemented riprap protection structure under long-term wave current action.

[0104] This invention addresses the stability issues faced by existing offshore wind power foundation protection structures due to long-term wave and current erosion. While gridded cemented riprap is an emerging protection technology, research on it has largely focused on short-term flue tests to verify immediate stability. However, existing methods suffer from a disconnect between macroscopic erosion morphology and material performance evolution, and short-term test results cannot reflect performance degradation over decades of service. This makes it impossible to establish a quantitative relationship between material degradation and structural failure, hindering long-term protection performance prediction. This invention obtains erosion pit volume evolution data through flue model tests, combines this with material erosion tests to establish a strength attenuation model, equates erosion damage under wave and current loads to material erosion time, and corrects material strength in real-time based on the equivalent damage age. Finally, it constructs an erosion pit development rate model to predict the long-term protection performance of cemented riprap structures.

[0105] Example 3

[0106] Figure 3 This is a structural block diagram of an electronic device 300 provided in an embodiment of this application. (See diagram below.) Figure 3 As shown, the electronic device 300 includes a memory 301, a processor 302, and a communication bus 303; the memory 301 and the processor 302 are connected via the communication bus 303. The memory 301 stores a performance analysis method for a cemented riprap protective structure, as provided in the above embodiment, which can be loaded and executed by the processor 302.

[0107] The memory 301 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 301 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing a performance analysis method for a cemented riprap protective structure provided in the above embodiments, etc. The data storage area may store data involved in the performance analysis method for a cemented riprap protective structure provided in the above embodiments, etc.

[0108] Processor 302 may include one or more processing cores. Processor 302 executes instructions, programs, code sets, or instruction sets stored in memory 301, and calls data stored in memory 301 to perform various functions and process data as described in this application. Processor 302 may be at least one of the following: Application-Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), Central Processing Unit (CPU), controller, microcontroller, and microprocessor. It is understood that, for different devices, the electronic devices used to implement the functions of processor 302 may also be other types, and this application embodiment does not specifically limit the specific implementation.

[0109] The communication bus 303 may include a path for transmitting information between the aforementioned components. The communication bus 303 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 303 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The symbol is represented by a single double arrow, but this does not mean that there is only one bus or one type of bus.

[0110] Example 4

[0111] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as described in the above embodiments, a performance analysis method for a cemented riprap protective structure.

[0112] In this embodiment, the computer-readable storage medium can be a tangible device that holds and stores instructions used by an instruction execution device. The computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, the computer-readable storage medium can be a portable computer disk, a hard disk, a USB flash drive, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), lectern random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory stick, floppy disk, optical disk, magnetic disk, mechanical encoding device, or any combination thereof.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A performance analysis method for a cemented riprap protective structure, characterized in that, include: The scour evolution data of the cemented riprap protective structure under wave load obtained from the water tank model test is obtained. The scour evolution data includes the time series of scour pit volume. To obtain the initial mechanical data of cemented paved stone materials and the mechanical property data of cemented paved stone samples at different erosion ages obtained from material tests; Based on the initial mechanical data and the mechanical property data, a strength reduction factor model is constructed to characterize the strength degradation of cemented paved stone materials with erosion time. The equivalent damage age of the cemented riprap protective structure under wave scouring is calculated based on the scouring evolution data and the corresponding wave load data. The real-time equivalent strength of the cemented riprap material is determined based on the equivalent damage age and the strength reduction coefficient model. Based on the real-time equivalent strength, a scour pit development rate model is constructed to predict the scour pit development process and protection cycle of the cemented riprap protection structure under long-term wave and current action. The initial mechanical data includes the initial strength of the cemented riprap material, and the mechanical property data includes the post-erosion strength of the cemented riprap material at different erosion ages. The construction of a strength reduction coefficient model characterizing the strength degradation of the cemented riprap material over erosion time based on the initial mechanical data and the mechanical property data includes: The strength reduction factor for each age is calculated based on the formula: λ(t) = Q(t) / Q(0), where λ(t) is the strength reduction factor, Q(0) is the initial strength, and Q(t) is the strength after erosion. The nonlinear regression method was used to fit multiple intensity reduction coefficients to obtain the functional relationship model between the intensity reduction coefficients and the equivalent erosion time: λ(t)=A×exp(-B×t)+C, where A is the magnitude of intensity decay, B is the rate of intensity decay, C is the lower limit of intensity decay, and t is the erosion time. Substituting the equivalent damage age into λ(t) = A × exp(-B × t) + C, the real-time equivalent intensity is obtained; The method of constructing the scour pit development rate model based on the real-time equivalent intensity includes: Construct a real-time equivalent intensity scour pit development rate model: , where dV2 / dt is the equivalent strength scour pit volume development rate, S(t) is the real-time equivalent strength, k2 is the scour strength coefficient, and N is the strength influence index.

2. The performance analysis method for a cemented riprap protective structure according to claim 1, characterized in that, The wave load data includes wave height and velocity time series data. The calculation of the equivalent damage age of the cemented riprap protective structure under wave scouring based on the scour evolution data and the corresponding wave load data includes: The bed shear stress within each time step is calculated based on wave height and flow velocity time series data. The equivalent damage increment for each time step is calculated based on the formula ΔTs=k1×(τ-τ0)×Δt, where ΔTs is the equivalent damage increment, τ0 is the stress threshold, τ is the bed shear stress within the time step, k1 is the damage equivalence coefficient, and Δt is the time step. The damage equivalence coefficient is determined based on scour evolution data. The equivalent damage increments are accumulated to obtain the cumulative equivalent damage age T=ΣΔTs at any scouring time.

3. The performance analysis method for a cemented riprap protective structure according to claim 2, characterized in that, The damage equivalence coefficient is determined based on scour evolution data, including: The observed scour rate was calculated based on the time series of the scour pit volume. Construct a prediction model for the scour rate: dV1 / dt=k×(τ-τ0) / λ(t), where dV1 / dt is the predicted scour rate, k is the scour rate coefficient, and λ(t) is the intensity reduction coefficient; With the goal of minimizing the error between the predicted scour rate and the observed scour rate, an optimization algorithm is used to simultaneously adjust k1 and k to obtain the calibrated damage equivalence coefficient k1.

4. The performance analysis method for a cemented riprap protective structure according to claim 3, characterized in that, The optimization algorithm employs either the least squares method or a genetic algorithm.

5. The performance analysis method for a cemented riprap protective structure according to claim 1, characterized in that, The method further includes: Compare the predicted protection period with the target lifespan; If the predicted protection period does not meet the target lifespan, the parameters of the cemented paved stone material in the protection structure are adjusted, and the steps of obtaining the initial mechanical data of the cemented paved stone material and the mechanical property data of the cemented paved stone samples at different erosion ages obtained from material tests are re-executed to construct a scour pit development rate model based on the real-time equivalent strength. Iterative optimization is carried out until a set of cemented paved stone material parameters that meets the protection lifespan requirements and has the best cost is found.

6. A performance analysis device for a cemented riprap protective structure, characterized in that, The device employs a performance analysis method for a cemented riprap protective structure as described in any one of claims 1 to 5, specifically comprising the following modules: The first acquisition module is used to acquire the scour evolution data of the cemented riprap protective structure under wave load obtained from the water tank model test. The scour evolution data includes the time series of scour pit volume. The second acquisition module is used to acquire the initial mechanical data of cemented paved stone materials and the mechanical property data of cemented paved stone samples at different erosion ages obtained from material tests. The first construction module, connected to the second acquisition module, is used to construct a strength reduction coefficient model characterizing the strength degradation of cemented paved material with erosion time based on the initial mechanical data and the mechanical performance data. The calculation module, connected to the first acquisition module, is used to calculate the equivalent damage age of the cemented riprap protective structure under wave scouring based on the scouring evolution data and the corresponding wave load data. A determination module, connected to the first construction module and the calculation module, is used to determine the real-time equivalent strength of the cemented riprap material based on the equivalent damage age and the strength reduction coefficient model. The second construction module, connected to the determining module, is used to construct a scour pit development rate model based on the real-time equivalent intensity, so as to predict the scour pit development process and protection cycle of the cemented riprap protection structure under long-term wave current action. The initial mechanical data includes the initial strength of the cemented riprap material, and the mechanical property data includes the post-erosion strength of the cemented riprap material at different erosion ages. The construction of a strength reduction coefficient model characterizing the strength degradation of the cemented riprap material over erosion time based on the initial mechanical data and the mechanical property data includes: The strength reduction factor for each age is calculated based on the formula: λ(t) = Q(t) / Q(0), where λ(t) is the strength reduction factor, Q(0) is the initial strength, and Q(t) is the strength after erosion. The nonlinear regression method was used to fit multiple intensity reduction coefficients to obtain the functional relationship model between the intensity reduction coefficients and the equivalent erosion time: λ(t)=A×exp(-B×t)+C, where A is the magnitude of intensity decay, B is the rate of intensity decay, C is the lower limit of intensity decay, and t is the erosion time. Substituting the equivalent damage age into λ(t) = A × exp(-B × t) + C, the real-time equivalent intensity is obtained; The method of constructing the scour pit development rate model based on the real-time equivalent intensity includes: Construct a real-time equivalent intensity scour pit development rate model: Where dV2 / dt is the equivalent strength scour pit volume development rate, S(t) is the real-time equivalent strength, k2 is the scour strength coefficient, and N is the strength influence index.

7. An electronic device, characterized in that, It includes a processor and a memory, wherein the processor is coupled to the memory; The processor is used to execute a computer program stored in the memory, so that the electronic device performs a performance analysis method for a cemented riprap protective structure as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Includes a computer program or instructions that, when executed on a computer, cause the computer to perform a performance analysis method for a cemented riprap protective structure as described in any one of claims 1 to 5.

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