Failure evaluation method of suction bucket structure based on destroy envelope surface theory

Abstract

The invention relates to a failure evaluation method for a suction bucket structure based on a destroy envelope surface theory, and the method is characterized in that the method comprises the following steps: collecting wave height, wave period and wind speed data in a research sea area for continuous years; the optimal edge distribution of the wave height, the wave period and the wind speed is selected; selecting the optimal joint distribution of the wave height, the wave period and the wind speed data; generating random sample data of wave height, wave period and wind speed; according to the generated random data of the wave height, the wave period and the wind speed, the wind load and the wave load borne by the suction bucket foundation of the offshore wind turbine in each group of samples are calculated; taking a damaged enveloping surface formula of the offshore wind turbine suction bucket foundation as a foundation failure judgment condition, if the obtained load is stable in the damaged enveloping surface, otherwise, the foundation fails; counting the number of the failure samples and the total samples, calculating the failure probability of each sampling, and obtaining the average failure probability after multiple times of cyclic sampling.

Description

Technical Field

[0001] The present invention relates to the field of marine engineering, and in particular to a failure evaluation method for a suction bucket structure based on a failure envelope theory. Background Art

[0002] Currently, offshore wind power has become a rapidly developing renewable energy source. As a new type of offshore wind turbine foundation, the suction bucket foundation offers advantages such as ease of construction and high cost-effectiveness. In recent years, it has been widely used in soft-soil sea areas. The uncompartmented suction bucket foundation was first used in actual engineering projects. Later, a four-compartment design was developed by adding a cross-shaped internal baffle to prevent shear failure of the soil plug within the bucket foundation, thereby improving the foundation's bearing capacity. Due to the complex interaction between the foundation and the subgrade, the ultimate bearing capacity of the wind turbine foundation is difficult to monitor. Furthermore, the marine environment in which the wind turbine foundation is located is extremely complex and harsh, and it is subject to the combined effects of wind and wave loads during its service life. Therefore, the failure probability of the offshore wind turbine suction bucket foundation under the combined effects of wind and waves must be considered during the design process. Existing methods often use a safety factor method, which cannot accurately determine the specific failure probability of the offshore wind turbine suction bucket foundation and does not consider the correlation between wave height, wave period, and wind speed. Using a larger safety factor will increase costs, while using a smaller one will increase risks. To overcome this problem, this paper proposes a highly efficient method for calculating the failure probability of offshore wind turbine suction bucket foundations under the combined effects of wind and waves, using the Copula theory to consider the correlation between wind and waves and the suction bucket foundation failure envelope as the failure criterion. Furthermore, a corresponding relationship between the failure probability of the suction bucket foundation and the traditional safety factor is provided for designers' reference. This method can provide a scientific basis for the design and optimization of offshore wind turbine suction bucket foundations, enabling more economical, safe, and efficient offshore wind farm construction. Summary of the Invention

[0003] The purpose of this invention is to provide a method that can quickly and accurately calculate the failure probability of offshore wind turbine suction bucket foundations while taking into account wind-wave correlation. To achieve this, the present invention proposes a failure assessment method for suction bucket structures based on the failure envelope theory. The technical solution employed by the present invention includes the following steps:

[0004] A failure evaluation method for a suction bucket structure based on a failure envelope theory is characterized by comprising the following steps:

[0005] (1) Collect wave height, wave period and wind speed data in the study area for many consecutive years;

[0006] (2) Using several different distributions to fit the wave height, wave period and wind speed data, the fitting parameters are obtained, and the goodness of fit test is performed. Then, the optimal marginal distribution of wave height, wave period and wind speed is selected;

[0007] (3) Several Archimedean Copula functions are used to establish the joint distribution of wave height, wave period and wind speed data and calculate the correlation coefficient θ. The goodness of fit test is then performed and the optimal joint distribution is selected.

[0008] (4) Generate random variables of the Archimedean Copula function based on the selected optimal joint distribution, and then generate random sample data of wave height, wave period and wind speed through Laplace transform;

[0009] (5) Calculate the wind load and wave load on the suction bucket foundation of the offshore wind turbine in each sample group based on the generated random data of wave height, wave period and wind speed;

[0010] (6) The damage envelope formula of the offshore wind turbine suction bucket foundation is used as the foundation failure judgment condition. If the required load is within the damage envelope, the foundation is stable; otherwise, the foundation fails. The method is:

[0011] 1) Assume that the horizontal force and moment of the foundation calculated in step (5) are H and M respectively, and the horizontal ultimate bearing capacity and moment ultimate bearing capacity under a certain vertical load are H respectively. ult_V and M ult_V , determine the failure envelope formula of the offshore wind turbine suction bucket foundation:

[0012]

[0013] Where ζ and ξ are parameters;

[0014] 2) If If it is not less than 1, the foundation will fail, otherwise the foundation will be stable;

[0015] (7) Calculate the failure probability of each sampling by counting the number of failed samples and the total number of samples, and obtain the average failure probability after multiple cycles of sampling;

[0016] (8) Different multi-year return load values ​​are used as design loads, and the corresponding relationship curves between the average failure probability and safety factor of the offshore wind turbine suction bucket foundation under different design loads are established.

[0017] Furthermore, the data collected in step (1) are wind and wave observation data from the Lianyungang Ocean Station in Jiangsu, China. In step (2), the optimal marginal distributions of wave height, wave period, and wind speed are selected as follows: Lognormal distribution for wave height, Gamma distribution for wave period, and Lognormal distribution for wind speed.

[0018] Furthermore, in step (2), four distributions, Gumebl, Weibull, Gamma and Lognormal, were used to fit the wave height, wave period and wind speed data respectively and obtain the fitting parameters. The goodness of fit was tested using three methods, namely KS hypothesis test, root mean square error method and Akaike information criterion.

[0019] Furthermore, in step (3), four Archimedean Copula functions, namely Clayton, Frank, Gumbel-Hougaard and Ali-Mikhail-Haq, are used to establish the joint distribution of the three and calculate the correlation coefficient θ, and the goodness of fit test is performed using the root mean square error method and the Akaike information criterion.

[0020] Furthermore, in step (3), the Gumbel-Hougaard Copula function is selected as the optimal joint distribution:

[0021]

[0022] u, v, and w are the marginal distributions of wave height, wave period, and wind speed, respectively.

[0023] Furthermore, in step (4), for the Gumbel-Hougaard Copula function, Y follows the stable distribution Y~Stable(α, β, γ, δ), α=1 / θ, β=1, γ=1, δ=0.

[0024] Furthermore, the method of step (4) is as follows:

[0025] 1) Generate independent uniform random variables v for wave height, wave period and wind speed i , i=1,2,3;

[0026] 2) Select the random variable Y corresponding to the Archimedean Copula function according to the optimal joint distribution;

[0027] 3) Generate marginal distributions u, v, w of wave height, wave period and wind speed, and generate random sample data by sampling according to the generated marginal distributions.

[0028] Furthermore, in step (4), let the intermediate variable s i =-lnv i / Y;

[0029] pass Generate marginal distributions u, v, w of wave height, wave period and wind speed, and generate random sample data by sampling according to the generated marginal distributions, where:

[0030] u iCalculate as follows:

[0031]

[0032] Where, Generating function for the Gumbel-Hougaard Copula The inverse function of .

[0033] Furthermore, in step (5), the calculation of the wind load and wave load on the suction bucket foundation of the offshore wind turbine adopts the maximum static load method; the calculation method of the wind load includes calculating the wind turbine force through the wind turbine thrust coefficient method and calculating the tower force through the piecewise integration method; the calculation method of the wave load is to calculate the tower force through the Morrison equation of linear wave theory.

[0034] Furthermore, in step (6), the parameters required to solve the failure envelope formula of the offshore wind turbine suction bucket foundation include: the mass m of the structural system, the suction bucket foundation type, the foundation diameter D, the foundation depth-to-diameter ratio d / D, and the soil shear strength s at the mud surface in the soil condition. um and the rate of change of soil shear strength with depth k.

[0035] The present invention has the following advantages:

[0036] (1) The method of the present invention achieves reasonable consideration of the correlation between wave height, wave period, and wind speed in the calculation of the failure probability of the suction bucket foundation of an offshore wind turbine. Four different distributions and four copula functions are used to fit the data. The optimal marginal distribution and joint distribution are selected through the goodness of fit test, so that the generated random sample data of wave height, wave period, and wind speed are more consistent with the actual situation.

[0037] (2) The method of the present invention can efficiently calculate the failure probability of the suction bucket foundation of an offshore wind turbine under the combined action of wind and waves. The failure envelope of the suction bucket foundation on a soft foundation is used as the foundation failure judgment condition to quickly determine whether the foundation has failed and then calculate the failure probability. The calculation speed is fast and the calculation results are stable.

[0038] (3) The method of the present invention is easy for designers to use. Using the multi-year return wave value as the load design value, a corresponding relationship between the failure probability and safety factor of the offshore wind turbine suction bucket foundation under different design loads is established. Designers can quickly determine the corresponding safety factor based on the requirements of the allowable failure probability. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Flowchart for calculating the failure probability of an offshore wind turbine suction bucket foundation under combined wind and wave action

[0040] Figure 2 Generate random samples of wave height, wave period, and wind speed

[0041] Figure 3 Wave force calculation diagram

[0042] Figure 4 η specified in the specification max Value

[0043] Figure 5 Average probability of failure as a function of cycle number

[0044] Figure 6 Homogeneous soil u Failure probability of NSBF and SBFICS at different times (a)s u =5kPa; (b)s u =10kPa; (c)s u =15kPa; (d)s u =20kPa; (e)s u =25kPa; (f)s u =30kPa

[0045] Figure 7 In heterogeneous soil um =10kPa and k is different NSBF and SBFICS failure probability (a)s um =10kPa, k = 1kPa / m; (b)s um =10kPa, k=2kPa / m; (c)s um =10kPa, k=3kPa / m; (d)s um =10kPa, k=4kPa / m; (e)s um =10kPa, k=5kPa / m; (f)s um =10kPa,k=6kPa / m

[0046] Figure 8 In heterogeneous soil, k = 2kPa / m and s um Failure probability of NSBF and SBFICS at different times (a)k=2kPa,s um =5kPa; (b)k=2kPa,s um =10kPa; (c)k=2kPa,s um =15kPa; (d)k=2kPa,s um =20kPa; (e)k=2kPa,s um =25kPa; (f)k=2kPa,s um =30kPa

[0047] Figure 9 Homogeneous soil (s uRelationship between the failure envelope of NSBF and SBFICS and the normalized 100-year load position (a)s u =15kPa,D=15m;(b)s u =15kPa,D=16m;(c)s u =20kPa,D=15m;(d)s u =20kPa,D=16m

[0048] Figure 10 Relationship between the failure envelopes of NSBF and SBFICS and the normalized 100-year load position in heterogeneous soils (different k) (a) um =10kPa, k=3kPa / m, D=14m; (b)s um =10kPa, k=3kPa / m, D=15m; (c)s um =10kPa, k=6kPa / m, D=14m; (d)s um =10kPa, k=6kPa / m, D=15m

[0049] Figure 11 Heterogeneous soil (s um Relationship between the failure envelope of NSBF and SBFICS and the normalized 100-year load position (a) k = 2 kPa / m, s um =5kPa, D=17m; (b)k=2kPa / m, s um =5kPa, D=18m; (c)k=2kPa / m, s um =10kPa, D=17m; (d)k=2kPa / m, s um =10kPa, D=18m Figure 12 Relationship curve between safety factor and average failure probability under different design loads DETAILED DESCRIPTION

[0050] The present invention is described in detail below with reference to specific embodiments:

[0051] Example

[0052] The present invention provides a failure evaluation method for a suction bucket structure based on the failure envelope theory, and its flow chart is as follows: Figure 1 As shown, it mainly includes the following steps:

[0053] S1. Collect wave height, wave period and wind speed data of a certain sea area for many consecutive years;

[0054] The present invention takes the wind and wave observation data of the Lianyungang Ocean Station in Jiangsu Province, China as an example (https: / / mds.nmdis.org.cn / ), selects the wave height, wave period and wind speed data of 8 consecutive years from 2016 to 2023, and adopts the annual N maximum value method (N=5) to ensure the fitting accuracy, that is, the extreme values ​​of the first 5 months of each year are selected as the fitting data, as shown in Table 1.

[0055] Table 1 Wave height, wave period and wind speed data

[0056]

[0057] S2, using four distributions to fit wave height, wave period and wind speed data respectively and selecting the optimal marginal distribution;

[0058] Four distributions, Gumebl, Weibull, Gamma and Lognormal, were used to fit the wave height, wave period and wind speed data respectively and the fitting parameters were obtained by the maximum likelihood method, as shown in Tables 2 and 3. The goodness of fit was tested by the KS hypothesis test, root mean square error (RMSE) and Akaike information criterion (AIC). The value of the KS test was less than This indicates that the data fits the distribution. Smaller RMSE and AIC values ​​indicate better fitting. Based on the above goodness-of-fit evaluation criteria, the optimal marginal distributions of wave height, wave period, and wind speed are selected. The calculation results are shown in Table 3.

[0059] The calculation formulas for KS test, RMSE and AIC are as follows:

[0060] (1) KS test:

[0061] It is known that the cumulative distribution function of a random variable X is F(x) and its theoretical distribution is F0(x). Let the null hypothesis H0: F(x) = F0(x) and the alternative hypothesis H1: F(x) ≠ F0(x). Select the statistic make

[0062]

[0063] Then the statistic D n Observed values Taking the significance level as 0.05, for different sample sizes n, the critical value D of the KS test can be obtained by looking up the table. n (0.05). If Then accept the null hypothesis H0, that is, the sample conforms to the theoretical distribution; otherwise reject the null hypothesis, the sample does not conform to the theoretical distribution.

[0064] (2) Root mean square error (RMSE)

[0065] RMSE can represent the error between predicted data and actual data, and its calculation formula is as follows:

[0066]

[0067] Where n is the number of samples; P c (i) is the theoretical frequency value; P0(i) is the empirical frequency value, P0(i) = m i / (n+1),m i Is x≤x i The number of .

[0068] (3) Akaike Information Criterion (AIC)

[0069] AIC is based on the concept of entropy and is used to evaluate the goodness of fit. Its calculation formula is as follows:

[0070]

[0071] Where m is the number of parameters of the marginal distribution function.

[0072] Table 2 Probability density functions and cumulative distribution functions of four distribution types

[0073]

[0074] Table 3 Fitting parameters, fitting tests and goodness of fit evaluation of the four distributions of wave height, period and wind speed

[0075]

[0076] The wave height is selected from the Lognormal distribution: The wave period is selected as Gamma distribution:

[0077] The wind speed is selected as Lognormal distribution:

[0078] S3, using four Copula functions to establish the joint distribution of the three and select the optimal joint distribution;

[0079] The four Archimedean Copula functions, Clayton, Frank, Gumbel-Hougaard, and Ali-Mikhail-Haq, are used to establish the joint distribution of the three and calculate the correlation coefficient θ. The calculation steps of the correlation coefficient θ are as follows:

[0080] (1) Map the cumulative distribution function of the original data into u i , v i , w i ∈(0,1), for each sample point (ui ,v i ,w i ), the statistic is not greater than its number, and then divided by the total number of samples n to obtain the empirical distribution value C empirical (u i ,v i ,w i );

[0081] (2) Calculate the theoretical distribution value C according to the Copula function expression provided in Table 4 θ (u i ,v i ,w i );

[0082] (3) Finally, the objective function is constructed by the Cramer-von Mises distance method The correlation coefficient θ is calculated by solving the minimum value of the objective function as follows:

[0083]

[0084] Where C θ (u i ,v i ,w i ) is the theoretical distribution value of the Copula function, C empirical (u i ,v i ,w i ) is the empirical distribution value of the Copula function, and the estimated value of the correlation coefficient θ is calculated by solving the minimum value of the distance between the two.

[0085] Goodness-of-fit tests were performed using the root mean square error (RMSE) and the Akaike Information Criterion (AIC). Smaller RMSE and AIC values ​​indicate a better fit. Based on these goodness-of-fit evaluation criteria, the optimal joint distribution was selected, and the calculation results are shown in Table 5.

[0086] Table 4 Four Archimedean Copula functions

[0087]

[0088] Table 5 Goodness of fit test of four Archimedean Copula functions

[0089]

[0090] Select the Gumbel-Hougaard Copula function as the optimal joint distribution:

[0091]

[0092] S4, generating random sample data of wave height, wave period and wind speed;

[0093] (1) Generate independent uniform random variables v for wave height, wave period, and wind speed i , i=1,2,3;

[0094] (2) Generate a random variable Y. For the Gumbel-Hougaard Copula function, Y follows the stable distribution Y~Stable(α, β, γ, δ), α = 1 / θ, β = 1, γ = 1, δ = 0;

[0095]

[0096] (3) Assume that the intermediate variable s i =-lnv i / Y, i=1, 2, 3;

[0097] (4) Through u i Generate the marginal distributions u, v, and w of wave height, wave period, and wind speed, and generate random sample data by sampling according to the generated marginal distributions, such as Figure 2 As shown. i Calculate as follows:

[0098]

[0099] Where, Generating function for the Gumbel-Hougaard Copula in Table 4 The inverse function of .

[0100] S5. Calculate the wind load and wave load on the suction bucket foundation of the offshore wind turbine in each sample group;

[0101] Calculate wind loads as follows:

[0102] Calculate wind speed at different heights (Code for Loads on Building Structures GB50009-2012):

[0103]

[0104] Where V ref is the reference wind speed; z ref is the reference height, which is generally 10m above sea level; ψ is the ground roughness index, which belongs to Class A in coastal areas and is taken as 0.12.

[0105] The wind turbine thrust is calculated using the thrust coefficient method (Frohboese and Schmuck, 2010; Arany, 2017; Ma, 2020; Ma et al., 2021).

[0106] When the wind speed at the hub V hub At the cut-in wind speed (V in ) and cut-out wind speed (V out ) between:

[0107]

[0108] Where, F Th is the fan thrust; ρ a is the air density, take 1.225kg / m 3 ; C T is the horizontal thrust coefficient; A R is the blade swept area; V hub is the wind speed at hub height; V in is the cut-in wind speed; V r is the rated wind speed; V out To cut out wind speed.

[0109] When the wind speed at the hub V hub Less than the cut-in wind speed (V in ) or greater than the cut-out wind speed (V out )hour:

[0110]

[0111] Where A B is the projected area of ​​all fan blades.

[0112] The tower force is calculated by the segmented integration method. The tower at sea level is divided into several small sections, and the height of each section is Δz. Then the force on each section of the tower is:

[0113]

[0114] Where C s is the tower resistance coefficient, which can be 0.5 for a cylindrical shape; A tower is the projected area of ​​each tower section; V zi is the wind speed on each tower section.

[0115] The maximum horizontal force on the foundation under wind action is:

[0116]

[0117] The maximum moment of the foundation under wind action is:

[0118]

[0119] Calculate wave loads (Hydrological Code for Ports and Waterways JTS145-2015).

[0120] The wave force P on a vertical pile per unit length is derived from the drag force P D and inertial force P I It consists of two parts. Maximum drag force P Dmax and inertial force P Imax and the torque M it generates Dmax and M Imax They are:

[0121]

[0122] Where, P Dmax is the maximum drag force acting on the entire column height; P Imax is the maximum inertia force; M Dmax and M Imax P Dmax and P Imax Moment about the foundation; ρ w is the density of seawater, take 1025kg / m 3 ; C D is the resistance coefficient, take 1.2; C M is the inertia coefficient, which is taken as 2.0; D is the cylinder diameter; H is the wave height; L is the wavelength; K1, K2, K3, and K4 are coefficients. The calculation formula is as follows:

[0123]

[0124] Where d is the water depth; z is the cross-section height; when calculating P Dmax and M Dmax When z1=0 and z2=d+η max , when calculating P Imax and M Imax When z1=0 and z2=d+η max -H / 2,η max It is the maximum height of the wave crest above the still water surface.

[0125] Wave force calculation diagram Figure 3 The peak height η specified in the specification max Values ​​such as Figure 4 shown.

[0126] When P Dmax ≤0.5P Imax When , the maximum horizontal force on the foundation under the action of waves is:

[0127] P m =P Imax

[0128] The maximum moment of the foundation under the action of waves is:

[0129] M m =MImax

[0130] When P Dmax >0.5P Imax When , the maximum horizontal force on the foundation under the action of waves is:

[0131]

[0132] The maximum moment of the foundation under the action of waves is:

[0133]

[0134] S6. The failure envelope formula of the suction bucket foundation on soft foundation is used as the foundation failure judgment condition;

[0135] Substitute the horizontal force H and moment M calculated by S5 into the failure envelope formula of the suction bucket foundation on the soft foundation. If it is not less than 1, the foundation will fail, otherwise the foundation will be stable. The formula is as follows:

[0136]

[0137] Where H and M are the horizontal force and moment on the foundation respectively; H ult_V and M ult_V are the horizontal ultimate bearing capacity and moment ultimate bearing capacity under a certain vertical load, respectively; ζ and ξ are parameters, see Table 7.

[0138] Calculate the horizontal ultimate bearing capacity H under a certain vertical load ult_V and moment limit bearing capacity M ult_V , including the following steps:

[0139] (1) Determine the basic conditions: foundation type (non-compartmented NSBF or four-compartment SBFICS with cross plates), foundation diameter D, foundation depth-to-diameter ratio d / D, soil shear strength s at the mud surface um , the rate of change of soil shear strength with depth k and the mass of the structural system m. According to the basic conditions, the shear strength of the soil at the bottom of the bucket s can be obtained u0 =s um + kd, soil heterogeneity index κ = kD / s um and vertical load G = mg;

[0140] (2) Calculation of the vertical bearing capacity coefficient N under unidirectional loading cV , horizontal bearing capacity coefficient N cH and moment bearing capacity factor N cM According to the bearing capacity coefficients provided in Table 6 (Vulpe, 2015; Xiao et al., 2020), N for different d / D and κ is obtained by interpolation. cV、N cH and N CM ;

[0141] (3) Calculation of the vertical ultimate bearing capacity V of the bucket foundation under unidirectional load ult , horizontal ultimate bearing capacity H ult and moment limit bearing capacity M ult . V ult =0.25N cV πD 2 s u0 , H ult =0.25N cH πD 2 s u0 , M ult =0.25N cM πD 3 s u0 ;

[0142] (4) Calculate the intermediate variables v, h, and m. v = G / V ult , h=1-v q , m=1-v p NSBF takes q = 4.14, p = 2.12, SBFICS takes q = 5.36, p = 2.36 (Vulpe, 2015; Xiao et al., 2020);

[0143] (5) Calculate the horizontal ultimate bearing capacity H under a certain vertical load ult_V and moment limit bearing capacity M ult_V . H ult_V =hH ult , M ult_V =mM ult ;

[0144] (6) Calculate parameters α and β. Based on the parameter values ​​provided in Table 7 (Vulpe, 2015; Xiao et al., 2020), the parameters α and β for different d / D and κ are obtained by interpolation.

[0145] In summary, we only need to give the structural system mass m, suction bucket foundation type (non-compartmented NSBF or four-compartmented SBFICS with cross plates), foundation diameter D, foundation depth-to-diameter ratio d / D, and soil shear strength s at the mud surface in the soil condition. um and the rate of change k of soil shear strength with depth, the failure envelope formula of suction bucket foundations of different types and sizes under different soil conditions can be calculated.

[0146] Table 6 Bearing capacity coefficients of NSBF and SBFICS under uniaxial loading

[0147]

[0148] Table 7 ζ and ξ parameter values ​​of the failure envelope of NSBF and SBFICS

[0149]

[0150]

[0151] S7. Calculate the failure probability of each sampling, and obtain the average failure probability after multiple rounds of sampling;

[0152] Statistical failure sample N f After calculating the failure probability P of each sampling and the total sample size N i =N f / N, calculate the average failure probability by looping multiple times In the present invention, the total number of samples is 10,000, the number of cycles is 100, and the average failure probability varies with the number of cycles as shown in the following figure: Figure 5 shown.

[0153] In this example, the NREL-5MW standard wind turbine is selected, with an impeller radius of 60m, a hub center distance from sea level of 90m, a tower diameter of 3m, a structural mass m of 700 tons, and a water depth of 30m. The following working conditions are considered for soft soil foundation: For homogeneous soil, the undrained shear strength s of the soil is taken as follows: u =5, 10, 15, 20, 25, 30 kPa; For heterogeneous soil, there are two types of working conditions: one is to maintain the shear strength of the soil at the mud surface s um =10kPa unchanged, and take the rate of change of soil shear strength with depth k=1, 2, 3, 4, 5, 6kPa / m respectively; second, keep k=2kPa / m unchanged, and take s um =5, 10, 15, 20, 25, 30 kPa. The average failure probability calculation results of the non-compartment suction bucket foundation (NSBF) and the four-compartment suction bucket foundation with cross plate (SBFICS) under various working conditions are as follows Figure 6 、 7 , 8. Using an Intel Core i9-13900HX CPU and 32G memory, the average calculation time for the failure probability of a single working condition is 18 seconds, which proves the computational efficiency of this method.

[0154] S8. Establish the corresponding relationship between the average failure probability and safety factor of the suction bucket foundation of offshore wind turbines under different design loads;

[0155] The safety factor method defines the safety factor (FoS) as the ratio of the distance from the intersection of the ray passing through the normalized load and the failure envelope to the coordinate origin to the distance from the normalized load point to the coordinate origin. The present invention takes several typical working conditions as examples and gives the results of the homogeneous soil s u , k and s of heterogeneous soil um The relationship between the bearing capacity failure envelope of NSBF and SBFICS and the normalized 100-year load position changes with the foundation depth-to-diameter ratio d / D when different values ​​are taken, as shown in the figure below: Figure 9 、 10 , 11. The five colors in the figure correspond to the foundation depth-to-diameter ratio d / D from 0.1 to 0.5. The solid line and solid star represent the bearing capacity failure envelope and normalized 100-year load of NSBF, respectively. The dotted line and hollow star represent the failure envelope and normalized 100-year load of SBFIFC, respectively.

[0156] The present invention adopts the wind and wave values ​​of 20 years, 50 years and 100 years as the load design values, and calculates and compares the safety factor FoS and the average failure probability of the suction bucket foundation bearing capacity under all the above working conditions. The corresponding relationship between the two was established. The fitting results show that the corresponding relationship between the two is independent of the type, size and soil properties of the bucket foundation, but only related to the selected load design value, and its influence is very small. If the allowable failure probability is 5%, the load design value of the suction bucket foundation is taken as the wind and wave value of 20 years, 50 years and 100 years, and the corresponding safety factors are 1.235, 1.137 and 1.076 respectively. Figure 12 shown.

[0157] The design load is the wind and wave value with a return period of 20 years:

[0158] The design load is the wind and wave value of once in fifty years:

[0159] The design load is the wind and wave value of 100 years:

Claims

1. A failure evaluation method for a suction bucket structure based on the failure envelope theory, characterized in that: The following steps are involved: (1) Collect wave height, wave period and wind speed data in the study area for many consecutive years; (2) Using several different distributions to fit the wave height, wave period and wind speed data, the fitting parameters are obtained, and the goodness of fit test is performed. Then, the optimal marginal distribution of wave height, wave period and wind speed is selected; (3) Several Archimedean Copula functions are used to establish the joint distribution of wave height, wave period and wind speed data and calculate the correlation coefficient θ. The goodness of fit test is then performed and the optimal joint distribution is selected. (4) Generate random variables of the Archimedean Copula function based on the selected optimal joint distribution, and then generate random sample data of wave height, wave period and wind speed through Laplace transform; (5) Calculate the wind load and wave load on the suction bucket foundation of the offshore wind turbine in each sample group based on the generated random data of wave height, wave period and wind speed; (6) The damage envelope formula of the offshore wind turbine suction bucket foundation is used as the foundation failure judgment condition. If the required load is within the damage envelope, the foundation is stable; otherwise, the foundation fails. The method is: 1) Assume that the horizontal force and moment of the foundation calculated in step (5) are H and M respectively, and the horizontal ultimate bearing capacity and moment ultimate bearing capacity under a certain vertical load are H respectively. ult_V and M ult_V , determine the failure envelope formula of the offshore wind turbine suction bucket foundation: Where ζ and ξ are parameters; 2) If If it is not less than 1, the foundation will fail, otherwise the foundation will be stable; (7) Calculate the failure probability of each sampling by counting the number of failed samples and the total number of samples, and obtain the average failure probability after multiple cycles of sampling; (8) Different multi-year return load values ​​are used as design loads, and the corresponding relationship curves between the average failure probability and safety factor of the offshore wind turbine suction bucket foundation under different design loads are established.

2. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 1 is characterized in that: The data collected in step (1) are wind and wave observation data from the Lianyungang Ocean Station in Jiangsu, China. In step (2), the optimal marginal distributions of wave height, wave period, and wind speed are selected as follows: Lognormal distribution for wave height, Gamma distribution for wave period, and Lognormal distribution for wind speed.

3. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 1 is characterized in that: In step (2), four distributions, Gumebl, Weibull, Gamma and Lognormal, are used to fit the wave height, wave period and wind speed data respectively and obtain the fitting parameters. The goodness of fit is tested by three methods, namely KS hypothesis test, root mean square error method and Akaike information criterion.

4. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 1 is characterized in that: In step (3), four Archimedean Copula functions, namely Clayton, Frank, Gumbel-Hougaard and Ali-Mikhail-Haq, are used to establish the joint distribution of the three and calculate the correlation coefficient θ. The goodness of fit is tested by the root mean square error method and the Akaike information criterion.

5. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 1 is characterized in that: In step (3), the Gumbel-Hougaard Copula function is selected as the optimal joint distribution: u, v, and w are the marginal distributions of wave height, wave period, and wind speed, respectively.

6. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 5 is characterized in that: In step (4), for the Gumbel-Hougaard Copula function, Y follows the stable distribution Y~Stable(α, β, γ, δ), α=1 / θ, β=1, γ=1, δ=0.

7. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 6 is characterized in that: The method of step (4) is as follows: 1) Generate independent uniform random variables v for wave height, wave period and wind speed i , i=1,2,3; 2) Select the random variable Y corresponding to the Archimedean Copula function according to the optimal joint distribution; 3) Generate marginal distributions u, v, w of wave height, wave period and wind speed, and generate random sample data by sampling according to the generated marginal distributions.

8. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 7 is characterized in that: In step (4), let the intermediate variable s i =-lnv i / Y; pass Generate marginal distributions u, v, w of wave height, wave period and wind speed, and generate random sample data by sampling according to the generated marginal distributions, where: u i Calculate as follows: Where, Generating function for the Gumbel-Hougaard Copula The inverse function of .

9. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 1 is characterized in that: In step (5), the calculation of wind load and wave load on the suction bucket foundation of the offshore wind turbine adopts the maximum static load method; the calculation method of wind load includes calculating the wind turbine force by the wind turbine thrust coefficient method and calculating the tower force by the piecewise integration method; the calculation method of wave load is to calculate the tower force by the Morrison equation of linear wave theory.

10. The failure evaluation method for a suction bucket structure based on the failure envelope theory according to claim 1, characterized in that: In step (6), the parameters required to solve the failure envelope formula of the offshore wind turbine suction bucket foundation include: the mass m of the structural system, the suction bucket foundation type, the foundation diameter D, the foundation depth-to-diameter ratio d / D, and the soil shear strength s at the mud surface in the soil condition. um and the rate of change of soil shear strength with depth k.

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