Deep sea temporary platform large diameter steel casing dynamic response analysis method

Abstract

The application provides a deep-sea temporary platform large-diameter steel casing dynamic response analysis method, and relates to the technical field of deep-sea engineering, and the method comprises the following steps: a three-dimensional explicit dynamic coupling model is established according to the typhoon frequency characteristics of a target sea area and steel casing structure parameters; according to the three-dimensional explicit dynamic coupling model, wave load is decomposed, and the vibration hammer, ocean current and internal wave flow load effects are integrated to determine the steel casing comprehensive dynamic load set. Through the establishment of an accurate model, the integration of multiple source loads, the identification of risk areas, the real-time monitoring of stress and the optimization of design parameters based on data, the application realizes the adaptive matching of the steel casing design and the complex marine environment, effectively improves the safety of the deep-sea temporary platform steel casing structure and reduces the cost.

Description

Technical Field

[0001] The present invention relates to the technical field of deep-sea engineering, and in particular to a method for analyzing dynamic responses of a large-diameter steel casing of a deep-sea temporary platform. Background Art

[0002] In the construction of temporary deep-sea platforms, traditional methods for analyzing the dynamic response of steel casings have drawbacks. First, they use simplified load models, isolating loads such as waves and currents while ignoring coupling effects. Second, they rely on a single computational approach, making it difficult to simulate the dynamic mechanical behavior of steel casings in complex marine environments and analyze stress transfer patterns in detail. Third, outdated monitoring technology, limited coverage, and low acquisition frequency make it difficult to capture stress changes in key areas in real time. Design parameters lack an adaptive mechanism, preventing dynamic optimization based on the marine environment, which can easily lead to overly conservative designs or insufficient load-bearing capacity.

[0003] For example, during the construction of an offshore platform in a typhoon-prone area, traditional methods independently calculated wave and current loads, failing to account for their combined effects. Material parameters were also calculated using conventional values. When a typhoon hit during construction, the actual loads far exceeded expectations, causing severe deformation of the steel casing. However, the monitoring system failed to provide a timely warning, ultimately halting the project for rectification and causing significant economic losses. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a dynamic response analysis method for large-diameter steel casings of deep-sea temporary platforms, which effectively improves the mechanical analysis accuracy, safety and design optimization level of steel casings in typhoon-prone sea areas.

[0005] In order to solve the above technical problems, the technical solutions of the present invention are as follows:

[0006] In a first aspect, a method for analyzing the dynamic response of a large-diameter steel casing of a deep-sea temporary platform is provided, the method comprising:

[0007] According to the typhoon-prone characteristics of the target sea area and the structural parameters of the steel casing, a three-dimensional explicit dynamic coupling model was established;

[0008] Based on the three-dimensional explicit dynamic coupling model, the wave load is decomposed and the load effects of the vibratory hammer, ocean current and internal wave current are integrated to determine the comprehensive dynamic load set of the steel casing.

[0009] The axial stress distribution characteristics during the penetration of the steel casing are calculated using the comprehensive dynamic load set of the steel casing. Based on the stress distribution characteristics, the stress distribution characteristics are analyzed to identify the stress concentration areas and buckling risk modes of the casing structure.

[0010] A waterproof full-bridge strain sensor array is deployed in the stress concentration area of ​​the cylinder structure. The waterproof full-bridge strain sensor array is used to collect the stress time history curve of the steel casing during the entire vibration penetration process in real time, and obtain the dynamic stress change data of the steel casing under actual working conditions.

[0011] Based on the dynamic stress change data of the steel casing under actual working conditions, the wall thickness of the steel casing and the material constitutive model parameters are corrected. Combined with the factors of different water depth gradients and soil stratification, a dynamic stress threshold database is established to achieve adaptive matching of the steel casing design parameters with the marine environmental conditions.

[0012] In a second aspect, a computing device includes:

[0013] one or more processors;

[0014] The storage device is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method.

[0015] According to a third aspect, a computer-readable storage medium stores a program, which implements the method described above when executed by a processor.

[0016] The above solution of the present invention includes at least the following beneficial effects:

[0017] A three-dimensional explicit dynamic coupling model is established based on the frequent typhoon characteristics of the target sea area and the structural parameters of the steel casing. At the same time, multiple load effects such as waves, vibrating hammers, ocean currents and internal waves are integrated. It can accurately simulate the actual stress conditions of the steel casing in the deep sea environment and provide a reliable model basis for the mechanical performance analysis of the steel casing.

[0018] By calculating the axial stress distribution characteristics during the steel casing penetration process and drawing a stress propagation cloud map, the stress concentration areas and buckling risk modes of the casing structure can be intuitively and accurately identified, allowing for the early detection of potential danger zones and structural weaknesses, effectively reducing the risk of structural failure and ensuring the safety of the deep-sea temporary platform during construction and operation. Deploying a waterproof full-bridge strain sensor array in the stress concentration area enables real-time acquisition of stress time-history curves throughout the entire vibration penetration process of the steel casing, capturing dynamic data on stress changes under actual operating conditions. This method enables continuous, comprehensive, and high-precision data acquisition, helping to timely understand the stress changes on the steel casing during construction.

[0019] Based on dynamic data on actual stress changes, the steel casing wall thickness and material constitutive model parameters are modified. This overcomes the limitations of traditional design, which relies on experience and assumptions, making the design parameters more consistent with actual working conditions and improving design accuracy. Furthermore, a dynamic stress threshold database is established, combining factors such as different water depth gradients and soil stratification, to avoid over-design or under-design and effectively reduce project costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The present invention provides a flowchart of a method for analyzing the dynamic response of a large-diameter steel casing of a deep-sea temporary platform. DETAILED DESCRIPTION

[0021] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0022] like Figure 1 As shown, an embodiment of the present invention provides a method for analyzing the dynamic response of a large-diameter steel casing of a deep-sea temporary platform, the method comprising the following steps:

[0023] Step 1: Based on the typhoon frequency characteristics of the target sea area and the structural parameters of the steel casing, a three-dimensional explicit dynamic coupling model is established;

[0024] Step 2: Based on the three-dimensional explicit dynamic coupling model, the wave load is decomposed and the load effects of the vibratory hammer, ocean current and internal wave current are integrated to determine the comprehensive dynamic load set of the steel casing;

[0025] Step 3: Calculate the axial stress distribution characteristics during the penetration of the steel casing using the integrated dynamic load set of the steel casing, and analyze the stress distribution characteristics to identify the stress concentration areas and buckling risk modes of the casing structure.

[0026] Step 4: Deploy a waterproof full-bridge strain sensor array in the stress concentration area of ​​the cylinder structure, and use the waterproof full-bridge strain sensor array to collect the stress time history curve of the steel casing during the entire vibration penetration process in real time, and obtain the dynamic data of the stress change of the steel casing under the actual working state;

[0027] Step 5: Based on the dynamic stress change data of the steel casing under actual working conditions, the wall thickness of the steel casing and the material constitutive model parameters are corrected. In combination with different water depth gradients and soil stratification factors, a dynamic stress threshold database is established to achieve adaptive matching of the steel casing design parameters with the marine environmental conditions.

[0028] In an embodiment of the present invention, a three-dimensional explicit dynamic coupling model is established based on the frequent typhoon characteristics of the target sea area and the structural parameters of the steel casing. The load effects of waves, vibrating hammers, ocean currents, and internal waves are decomposed and integrated, changing the shortcomings of traditional isolated analysis. It can accurately simulate the actual stress state of the steel casing in a complex marine environment, avoid design deviations caused by load misjudgment, and improve the accuracy of the analysis results. By calculating the axial stress distribution of the steel casing and drawing a stress propagation cloud map, stress concentration areas and buckling risk modes can be intuitively identified; waterproof full-bridge strain sensor arrays are deployed at key locations to collect stress time history curves in real time, making up for the shortcomings of insufficient coverage and data lag of traditional monitoring methods, realizing dynamic and accurate monitoring of the operating status of the steel casing, and facilitating the timely discovery of potential safety hazards.

[0029] Based on the dynamic data of actual stress changes, the wall thickness of the steel casing and the material constitutive model parameters are corrected, and a dynamic stress threshold database is established in combination with different marine environmental factors. This breaks the limitations of traditional design parameters that are fixed and difficult to adapt to environmental changes, and achieves adaptive matching of steel casing design parameters with marine environmental conditions. It can not only ensure structural safety, but also avoid design redundancy, reduce construction costs, and provide strong guarantees for the stable operation and efficient construction of deep-sea temporary platforms.

[0030] In a preferred embodiment of the present invention, the above step 1, establishing a three-dimensional explicit dynamic coupling model based on the typhoon frequency characteristics of the target sea area and the structural parameters of the steel casing, may include:

[0031] Step 100: extracting time-course data of wave elements, bottom current velocity, and extreme wind speed based on the frequent occurrence of typhoons in the target sea area, and obtaining quantitative values ​​of diameter, wall thickness, and material yield strength based on the structural parameters of the steel casing;

[0032] Step 101: Using the structural parameters of the steel casing, a thin shell structure of the steel casing is constructed using shell elements. During the construction process, the geometric shape of the steel casing, including the curvature of the casing and the structure of the connection parts, is analyzed, and the properties of each element, including the elastic modulus and Poisson's ratio parameters, are set to simulate the mechanical properties of the steel casing under stress. A soil model including a seabed silt layer, a sandy clay layer, and a weathered rock layer is constructed using solid elements according to the actual distribution of the strata.

[0033] Step 102: setting a contact algorithm, contact type, and contact parameters between the steel casing and the soil based on the thin shell structure of the steel casing and the soil model to simulate contact pressure transmission and relative sliding behavior between the steel casing and the soil.

[0034] Step 103: For the steel casing material, a bilinear model is defined, and the elastic modulus in the elastic stage, the yield strength in the plastic stage, and the hardening modulus parameters are determined to describe the overall characteristics of the steel material from elastic deformation to plastic deformation under load. For the soil, a Drucker-Prager constitutive relation is defined, and the mechanical response of the soil is described by setting the internal friction angle, cohesion, and dilatancy angle parameters.

[0035] Step 104 : Integrate the thin shell structure of the steel casing, the soil model, the contact algorithm, and the bilinear model into the 3D explicit dynamic analysis software to establish a 3D explicit dynamic coupling model.

[0036] In an embodiment of the present invention, when collecting meteorological and oceanographic environmental data for the target sea area, long-term meteorological observation data and typhoon historical databases can be obtained through authoritative institutions such as the National Marine Information Center and the Meteorological Science Data Sharing Service Platform. For wave elements, wave height meters and wave direction meters carried on ocean monitoring buoys can be used to continuously record wave height, period, and wave direction data at minute intervals; radar wave measurement systems at coastal observation stations can also provide high-resolution wave data. Bottom-layer current velocity data can be obtained using acoustic Doppler current profilers (ADCPs), which are deployed on the seabed or fixed to buoys to obtain current velocity profile time-course data at different depths. Extreme wind speed data mainly comes from meteorological satellite remote sensing inversion and actual anemometer measurements at coastal meteorological stations. Meteorological satellites can use equipment such as microwave radiometers to conduct large-scale monitoring of wind speeds over vast ocean areas.

[0037] For areas lacking measured data, the numerical simulation software SWAN (Simulating Waves Nearshore) is used as an example. The typhoon path (available from the Joint Typhoon Warning Center) and typhoon intensity (parameters such as central pressure and maximum wind speed radius) are first input. Combined with topographic data of the target sea area (such as a bathymetric topographic map), the software, based on a third-generation ocean wave model, simulates the wave generation, propagation, and deformation process through the energy balance equation and outputs time-course data for wave elements. FVCOM (Finite-Volume Community Ocean Model) can be used to simulate ocean currents. By inputting data such as wind fields, topography, and boundary conditions, the software solves the fluid dynamics equations using the finite volume method to obtain time-course data for bottom-level ocean current velocity.

[0038] In terms of obtaining the structural parameters of steel casings, for steel casings in the design phase, geometric parameters such as diameter, wall thickness, and length are directly extracted from the CAD design drawings, while mechanical parameters such as material yield strength are determined based on the technical specifications. For steel casings that have already been built or are in service, the diameter and wall thickness can be measured at multiple points using an ultrasonic thickness gauge and the average value taken; the length can be determined by measuring the elevation difference between the top and bottom of the steel casing using a total station. For material yield strength, the ultrasonic impact echo method in non-destructive testing technology is used to analyze the propagation characteristics of ultrasonic waves in steel and infer the material strength. At the same time, detailed records are kept of the number of steel casing segments, the length of each segment, the connection method (such as the bolt specifications for flange connections and the groove form of welded joints), and other information.

[0039] Step 101: When constructing a thin steel casing structure in ABAQUS, click the "Part" module, select "CreatePart," and in the pop-up window, select the "Shell, Extrusion" type. Enter the diameter and length of the steel casing, and use an extrusion operation to generate a preliminary geometry model of the casing. The "Sketch" module is then used to precisely adjust the casing geometry to ensure that the curvature meets design requirements. For the flange connection, a new component is created in the "Part" module to simulate the flange. The flange is assembled to the casing using the "Assembly" module, and the contact relationship between the two is defined as Tie. For the welded joint, the "MeshControl" function in the "Mesh" module is used to refine the local mesh in the weld area, setting the element size to 1 / 3-1 / 5 of the wall thickness to accurately simulate the mechanical properties of the welded joint. In the "Property" module, material properties are assigned to the steel casing, with an elastic modulus of 206 GPa and a Poisson's ratio of 0.3. These parameters can be obtained from the factory quality inspection report for the steel. Finally, based on the stress characteristics of the steel casing in actual work, the "Seed" function in the "Mesh" module was used to locally refine the mesh at the top of the casing (bearing the load of the superstructure), the bottom of the casing (the part in contact with the soil), and the connection parts. The seed spacing was set to 1 / 2 of that in the normal area.

[0040] When constructing the soil model, based on the submarine geological survey report, in the "Part" module of ABAQUS, create solid components representing different soil layers in sequence. Taking the submarine mud layer as an example, select "CreatePart", type "Solid, Extrusion", enter the thickness and plane dimensions of the mud layer, and generate a geometric model by stretching. According to the actual distribution of each soil layer, assemble it in the "Assembly" module. For interlayers in complex geological structures, if the thickness is thin (less than 0.5 meters), it can be equivalent to the adjacent soil layer; if the interlayer thickness is large and the mechanical properties are significantly different, it is modeled separately. In the "Property" module, each soil layer is assigned corresponding physical and mechanical parameters. For example, the density of the submarine mud layer is set to 1.6×10³kg / m³, the elastic modulus is 10MPa, and the Poisson's ratio is 0.45. These parameters are derived from the geotechnical test data in the geotechnical engineering survey report, including indoor density tests, compression tests, etc.

[0041] Step 102, when selecting the contact algorithm, take the augmented Lagrangian method as an example. Its principle is to satisfy the contact constraint conditions by iteratively adjusting the Lagrangian multiplier on the basis of the penalty function method. In the "Interaction" module of ABAQUS, click "CreateInteraction" and select "Surface-to-SurfaceContact" to create a surface-to-surface contact pair. The outer surface of the steel casing is defined as the contact surface (MasterSurface), and the surface where the soil contacts the steel casing is defined as the target surface (SlaveSurface). In the contact property settings, select "HardContact" for the normal behavior, and the software will automatically calculate the contact pressure to ensure that the two surfaces do not penetrate. The Coulomb friction model is used for the tangential behavior. For the contact between the sandy clay layer and the steel casing, the friction coefficient is set to 0.35 based on relevant engineering experience and soil property tests.

[0042] When setting contact parameters, determining contact stiffness (Penalty Stiffness) is crucial. Using the "Estimate from Material Properties" function, the software automatically estimates this based on the elastic moduli of the steel casing and soil. This value can also be adjusted through trial calculations, with a range of 0.01-0.1 times the elastic modulus of the steel casing. The contact tolerance (Contact Tolerance) controls the accuracy of contact determination and is set between 1% and 5% of the element characteristic size to balance calculation accuracy and efficiency.

[0043] Step 103, when defining the bilinear model of the steel casing material in the finite element software, select the "Plastic" option in the "Property" module and enter the elastic modulus of 206GPa in the elastic stage. This parameter can be determined by the slope of the elastic section of the stress-strain curve in the tensile test. The yield strength in the plastic stage is input according to the design drawings or material test reports, such as 355MPa. To obtain the hardening modulus, it is necessary to first conduct a tensile test on the steel material, record the stress-strain data after the yield point, and fit the data by the least squares method to obtain the tangent slope of the stress-strain curve, which is the hardening modulus, and the value is 0.01-0.1 times the elastic modulus.

[0044] To set up the Drucker-Prager constitutive relationship for soil, select the constitutive model in the "Property" module and enter the internal friction angle, cohesion, and dilatancy parameters. Taking the internal friction angle as an example, soil specimens are sheared under different normal pressures through indoor direct shear tests and the internal friction angle is calculated using the shear strength formula. For example, the internal friction angle of a sandy clay layer was experimentally determined to be 32°, the cohesion to be 12 kPa, and the dilatancy angle to be 8° based on experience. These parameters accurately reflect the mechanical response characteristics of the soil.

[0045] Step 104, when integrating each part model into LS-DYNA software, first import the steel casing thin shell structure model and soil model file (such as .inp format). In the "Contact" menu, check and confirm whether the contact algorithm and contact point settings are correct to ensure that the contact relationship between the steel casing and the soil is accurate. In the "Material" menu, check the material constitutive relationship and parameter settings to ensure that the mechanical properties of the steel casing and the soil are accurately described. In terms of mesh quality inspection, use the software's mesh inspection tool to view indicators such as the aspect ratio and distortion of the unit. For unqualified units (such as units with an aspect ratio greater than 10), return to the pre-processing software for mesh repair or re-division. In terms of boundary condition settings, set the bottom of the soil model to a fixed constraint (AllDOF=0) and apply horizontal displacement constraints on the side; apply load boundary conditions to the top of the steel casing according to the actual force conditions, such as vertical loads and horizontal loads. In the initial condition setting, consider the effect of gravity and apply gravity acceleration through the "InitialConditions" menu.

[0046] When setting the calculation parameters, the time step is determined based on the minimum element size and material wave velocity in the model. It is calculated according to the Courant-Friedrichs-Lewy (CFL) condition and is set to the ratio of the minimum element size to the material wave velocity. - In the Output Results section, select the output of stress, strain, and displacement time-history data for the steel casing, as well as the contact force data between the steel casing and the soil. After completing the above settings, debug the model and perform trial calculations to check for convergence issues. If convergence does occur, adjust the contact parameters, mesh quality, or time step until the model can be stably calculated, ultimately completing the establishment of the 3D explicit dynamic coupling model.

[0047] Suppose that the construction of an offshore wind turbine foundation in a typhoon-prone area requires dynamic analysis of the large-diameter steel casing. First, by collecting nearly 20 years of meteorological and oceanographic monitoring data for the area, we obtained time-history data showing that during typhoons, the maximum wave height can reach 15 meters, the period 12 seconds, the bottom current velocity can reach 1.5 m / s, and the extreme wind speed can reach 50 m / s. Furthermore, structural parameters such as the 8-meter diameter, 50-mm wall thickness, and 355 MPa material yield strength were obtained from the steel casing design drawings. In the finite element software ABAQUS, the thin shell structure of the steel casing was constructed using S4R shell elements, and the mesh at the joints was refined. A soil model consisting of a seafloor silt layer, a sandy clay layer, and a weathered rock layer was constructed using C3D8R solid elements according to the geological survey report. The contact algorithm used the augmented Lagrangian method, with the contact type set to surface-to-surface, hard contact in the normal direction, and a Coulomb friction model in the tangential direction, with a friction coefficient of 0.3. A bilinear model was used for the steel casing, with an elastic modulus of 206 GPa and a hardening modulus of 2 GPa. The Drucker-Prager constitutive relationship was used for the soil, with an internal friction angle of 30°, a cohesion of 15 kPa, and a dilatancy angle of 5°, as determined by geotechnical tests. Finally, these components were integrated into the software to create a 3D explicit dynamic coupling model, successfully simulating the mechanical response of the steel casing under typhoon conditions.

[0048] By extracting time-course data on waves, currents, and wind speeds from typhoon-prone waters, along with detailed structural parameters of the steel casing, the model accurately reproduces the complex marine environment and structural characteristics of the steel casing. Compared to traditional simplified models, this model improves the accuracy of its simulation of actual working conditions and provides a reliable foundation for accurate analysis of the stresses on the steel casing. Shell elements are used to construct the thin shell structure of the steel casing, while solid elements are used to construct the soil model. Detailed settings for the geometry and element properties enable accurate simulation of the mechanical properties of both the steel casing and the soil. Detailed settings for the contact behavior between the steel casing and the soil effectively reflect the interaction between the two, making the model more consistent with actual engineering conditions. Appropriate constitutive relationships are defined for the steel casing and soil, and relevant parameters are determined using experimental data. This accurately describes the mechanical response of the steel and soil under load, avoiding calculation errors caused by inappropriate material constitutive relationships and improving the reliability of the analysis results. By integrating the steel casing, soil, contact algorithm and material constitutive relationship into the three-dimensional explicit dynamic analysis software, a complete dynamic coupling model was established, which enabled a comprehensive simulation analysis of the dynamic response of the steel casing in a complex marine environment. This provided strong technical support for the design optimization and safety assessment of the steel casing, and helped to ensure the safety and economy of the construction of deep-sea temporary platforms.

[0049] In a preferred embodiment of the present invention, the above step 2, based on the three-dimensional explicit dynamic coupling model, decomposes the wave load and integrates the load effects of the vibratory hammer, ocean current and internal wave current to determine the comprehensive dynamic load set of the steel casing, which may include:

[0050] Step 201: Decompose the wave load according to the three-dimensional explicit dynamic coupling model, and calculate the velocity-related term and inertia term of the wave load according to the relevant parameters in the three-dimensional explicit dynamic coupling model, including the diameter of the steel casing, the wave height, and the period, to form a basic wave load component set.

[0051] Step 202 , using the Jones-Wepp spectrum, a non-stationary random wave sequence is generated, and the wave sequence is spatially and temporally coupled with the basic wave load component set to construct a wave load model that includes short-term sea state characteristics;

[0052] Step 203: Based on the wave load model, combined with the model, operating frequency, and exciting force parameters of the vibratory hammer, a vibratory hammer-steel casing coupling dynamic architecture is established, and the periodic exciting load generated by the vibratory hammer on the bottom of the steel casing is calculated using an explicit integration algorithm;

[0053] Step 204 , determining the magnitude and direction of the drag force of the ocean current on the steel casing based on the ocean current velocity field data in the vibratory hammer-steel casing coupled dynamic architecture and the shape and size parameters of the steel casing;

[0054] Step 205 , analyzing the ocean current drag force, ocean environment parameters, and structural response data of the steel casing under the action of the ocean current drag force, and establishing an internal wave impact load model to quantify the internal wave impact effect;

[0055] In step 206, the basic wave load component set, the periodic excitation load, the ocean current drag force, and the internal wave and current impact effect are superimposed to form a comprehensive dynamic load set including time domain, frequency domain, and space domain characteristics.

[0056] In the embodiment of the present invention, when the wave load acts on the steel casing, it can be decomposed into the velocity-related term (drag force) and the inertia term (inertia force) according to the Morison equation. In the three-dimensional explicit dynamic coupling model, the parameters such as the steel casing diameter D, wave height H, and period T are known, and the velocity of the water particle is calculated by combining the water particle motion theory (such as linear wave theory or nonlinear Stokes theory). (a vector representing the instantaneous velocity of a water particle in wave motion, including magnitude and direction) and acceleration (A vector representing the rate of change of the velocity of a water particle, including magnitude and direction).

[0057] For speed-related terms, the calculation formula is: ,in, The drag force of ocean current on the steel casing, is the density of seawater, is the drag coefficient (determined empirically, e.g. for a smooth cylindrical structure, The value is between 0.6-1.2). is the magnitude of the water particle velocity (scalar), ensuring that the velocity value participates in the amplitude calculation; the inertia term calculation formula is ,in, is the inertial force, is the inertia coefficient, set to 2.0. By calculating the water particle motion parameters at different times, the velocity-related and inertial components of the wave load at each moment are obtained, thereby forming a basic wave load component set. This process takes into account the attenuation and refraction characteristics of wave propagation, and makes corrections based on model parameters such as water depth and topography.

[0058] Step 202: The JONSWAP spectrum is a commonly used spectrum type to describe the distribution of wave energy. It can reflect the change of wave energy with frequency under different sea conditions. First, the parameters of the JONSWAP spectrum, such as the peak factor, are determined based on the wind field data (wind speed, wind direction, wind time, wind distance, etc.) of the target sea area. (The value is around 3.3 and can be adjusted according to sea conditions), spectral peak frequency, etc. Using random process theory and inverse Fourier transform, the Jones-Wepp spectrum is converted into a non-stationary random wave sequence. This sequence contains wave components of different frequencies, phases, and amplitudes, which can simulate the randomness and complexity of waves in actual sea conditions.

[0059] The generated wave sequence is spatiotemporally coupled with the basic wave load component set obtained in step 201. Considering the spatial propagation characteristics of waves and their interaction with the steel casing structure, the point and direction of wave load action on the steel casing surface at different times are determined based on the location and size of the steel casing. Using methods such as interpolation, the wave sequence and basic wave load components are matched in time and space to construct a wave load model that reflects short-term sea conditions and more closely reflects wave action in actual marine environments.

[0060] In step 203, based on the model of the vibratory hammer (e.g., the DZJ-180), obtain its operating frequency and excitation force parameters (e.g., maximum excitation force) from the equipment's technical manual. The vibratory hammer is simplified into a vibration source with a specific frequency and excitation force, and a coupled dynamic architecture is established with the steel casing. In 3D explicit dynamic analysis software, the dynamic transmission between the vibratory hammer and the steel casing is simulated by setting up spring-damper units or directly applying simple harmonic loads.

[0061] The explicit integration algorithm (such as the central difference method) is used to calculate the periodic excitation load generated by the vibratory hammer on the bottom of the steel casing. The algorithm is based on the dynamic equation ,in is the mass matrix, is the damping matrix, is the stiffness matrix, is the excitation load that changes with time. By dividing time into small time steps , gradually solve the displacement of the steel casing under the excitation load ,speed and acceleration , and then the magnitude and direction of the excitation load generated by the vibratory hammer on the bottom of the steel casing at different times are obtained. In the calculation process, the structural damping of the steel casing and the energy transfer efficiency between the vibratory hammer and the steel casing need to be considered.

[0062] Among them, the mass matrix ( ): describes the inertial characteristics of the system. In the steel casing-vibratory hammer system, its construction is based on structural discretization. The steel casing and vibratory hammer are divided into a finite number of units, and the mass of each unit is determined by the material density ( ), unit volume ( )Sure( = In the matrix, the diagonal elements correspond to the mass of each unit, and the off-diagonal elements reflect the mass coupling relationship between units. Taking the cylindrical steel casing as an example, the axial discretization is units, and the mass of each unit is concentrated at the node, forming a diagonally dominant mass matrix, such as , indicating the The quality of nodes, ( = ) is 0 when there is no special connection.

[0063] Damping matrix ( ): Reflects the energy dissipation characteristics of the system and adopts the Rayleigh damping model = + .in, 、 is the Rayleigh damping coefficient, which can be determined by structural modal analysis. Reflects mass-related damping, which is related to energy dissipation in the low-frequency range of structural vibration frequency; Reflects stiffness-related damping and affects high-frequency energy dissipation. For example, for steel casing structures, based on the internal friction characteristics of the material and the damping effect of the surrounding soil, combined with on-site dynamic test data, the appropriate 、 The damping matrix is ​​constructed based on the vibration value to describe the energy loss caused by internal friction of the material, soil resistance, etc.

[0064] Stiffness matrix ( ): Characterizes the ability of the structure to resist deformation, calculated based on material mechanics and elasticity theory. For steel casing units, based on Hooke's law, combined with unit geometric dimensions (such as length , cross-sectional area ) and the material elastic modulus ( ), the unit stiffness matrix is ​​derived by the finite element formula. For example, for a one-dimensional rod element, its stiffness matrix is = , assemble the stiffness matrices of each unit according to the node number to form the overall stiffness matrix The matrix element Representation node When unit displacement occurs at the node The force caused by the deformation reflects the relationship between the deformation and force of each part of the structure.

[0065] Step 204: Obtain ocean current velocity data in the vibratory hammer-steel casing coupled dynamic architecture. Ocean current velocities at different depths and locations can be obtained through ocean numerical models (such as FVCOM) or field measurements (such as ADCP measurements). According to the shape (cylindrical) and size parameters (diameter, length) of the steel casing, the drag force formula is used. Calculate the drag force of ocean current on the steel casing, where is the ocean current drag coefficient (the value ranges from 0.7 to 1.0 and can be adjusted according to the surface roughness of the steel casing and the characteristics of the ocean current), is the projected area of ​​the steel casing perpendicular to the direction of ocean current; is the density of seawater, about 1025kg / ; The drag force exerted by the ocean current on the steel casing is determined by ensuring that the direction of the drag force is consistent with the direction of the ocean current velocity. Considering the variation in ocean current velocity at different depths (for example, the presence of a thermocline may cause stratification of ocean current velocity), the drag force at different heights of the steel casing is calculated segmentally. The magnitude and direction of the drag force acting on the entire steel casing are then determined by integration or summation. The effect of the interaction between ocean currents and waves on the drag force must also be considered, and appropriate corrections should be made to the calculated results.

[0066] Step 205, the quantification of the internal wave and current impact effect requires comprehensive consideration of multiple factors. First, analyze the structural response data of the steel casing under the action of the ocean current drag force, such as displacement, stress, strain, etc., and obtain these data through real-time monitoring by sensors or numerical simulation. Combined with the ocean environment parameters, including the amplitude, propagation speed, wavelength, etc. of the internal wave (which can be obtained through ocean observation data), and the structural characteristics of the steel casing (such as natural frequency, damping ratio), an internal wave and current impact load model is established. Based on a combination of empirical formulas and numerical simulations. For example, the internal wave and current impact force ,in, is the correction factor (determined according to specific sea conditions and structural characteristics), is the internal wave amplitude, is the internal wave propagation speed, is the effective load-bearing area of ​​the steel casing. Through numerical simulation, the parameters in the formula are verified and adjusted, so that the model can accurately quantify the impact effect of internal wave flow, providing a reliable basis for the synthesis of subsequent load sets.

[0067] Step 206, superimpose the basic wave load component set, periodic excitation load, ocean current drag force and internal wave impact effect obtained in steps 201-205. During the superposition process, the time history and spatial distribution characteristics of each load need to be considered to ensure their consistency in the time domain, frequency domain and space domain. For the time domain characteristics, the curves of each load changing with time are added together at the corresponding moment; in the frequency domain, the frequency components of each load are analyzed by Fourier transform to ensure that the superimposed load set can reflect the comprehensive effect of loads of different frequencies; in the spatial domain, the distribution of the comprehensive load on the surface of the steel casing is accurately determined according to the geometric shape of the steel casing and the points of action of each load. Finally, a comprehensive dynamic load set containing time domain-frequency domain-space domain characteristics is formed, which can comprehensively and accurately describe the various dynamic loads that the steel casing is subjected to in a complex marine environment.

[0068] In an offshore bridge construction project in a typhoon-prone sea area, the dynamic characteristics of a large-diameter steel casing required analysis. First, in a three-dimensional explicit dynamic coupling model, the steel casing diameter was known to be 6 meters. Ocean monitoring data revealed a wave height of 8 meters and a period of 10 seconds in the area. The velocity-dependent and inertial components of the wave load were calculated using the Morison equation to form a basic wave load component set. Based on wind field data for the area, including wind speed (25 m / s) and wind duration (12 hours), the Jones-Wepp spectrum parameters were determined, and a non-stationary random wave sequence was generated. This wave load model was then constructed by spatiotemporally coupling the wave load sequence with the basic wave load component set. A DZJ-150 vibratory hammer with an operating frequency of 10 Hz and a maximum excitation force of 1500 kN was then used. An explicit integration algorithm was used to establish a vibratory hammer-steel casing coupling dynamic architecture, and the periodic excitation load generated by the hammer on the bottom of the steel casing was calculated. ADCP measurements revealed the ocean current velocity field in this area, revealing an average current velocity of 1.2 m / s at the location of the steel casing. The drag force on the steel casing was calculated using the drag force formula. Combined with ocean observation data, internal waves were detected in this area, with an amplitude of 3 m and a propagation velocity of 0.5 m / s. An internal wave impact load model was established to quantify the impact effects.

[0069] The basic wave load component set, periodic excitation load, ocean current drag force and internal wave impact effect are superimposed to form a comprehensive dynamic load set with time domain, frequency domain and space domain characteristics, providing accurate load input for the mechanical analysis of steel casing.

[0070] By decomposing and reconstructing wave loads and integrating multiple load effects, the combined effects of multiple factors on steel casings in typhoon-prone seas, such as waves, vibratory hammers, ocean currents, and internal wave currents, can be fully considered. Compared with traditional single load calculation methods, this method more realistically restores the actual stress state of the steel casing and improves the accuracy of the analysis results. Using the Jones-Wepp spectrum to generate non-stationary random wave sequences and perform spatiotemporal coupling, the randomness of ocean waves and short-term sea state characteristics are fully considered, making the wave load model more consistent with actual sea state changes, avoiding calculation deviations caused by fixed wave parameters, and providing a reliable basis for the safety assessment of steel casings under different sea conditions. A vibratory hammer-steel casing coupling dynamic architecture is constructed, and an explicit integration algorithm is used to calculate the excitation load. This accurately simulates the dynamic interaction between the vibratory hammer and the steel casing during construction, which helps analyze the stress and deformation characteristics of the steel casing during vibration penetration and optimizes construction technology and equipment selection.

[0071] For ocean current and internal wave loads, calculation models and impact load models were established respectively, taking into account the ocean current velocity field distribution, the structural response of the steel casing and the special effects of internal wave currents. This can accurately quantify the impact of these special loads on the steel casing, filling the gap in traditional analysis of insufficient consideration of the effects of complex ocean flow fields.

[0072] The final comprehensive dynamic load set with time-domain, frequency-domain, and space-domain characteristics comprehensively describes the loads on the steel casing from multiple dimensions, providing complete and accurate load input for subsequent steel casing stress analysis and structural optimization design based on this load set, which helps to improve the reliability and economy of the design of large-diameter steel casings for deep-sea temporary platforms.

[0073] In a preferred embodiment of the present invention, the above step 3, using the steel casing integrated dynamic load set to calculate the axial stress distribution characteristics during the steel casing penetration process, and analyzing the stress distribution characteristics to identify the stress concentration area and buckling risk mode of the cylinder structure, may include:

[0074] Step 301: Apply the integrated dynamic load set as a boundary condition to the steel casing structure in the three-dimensional explicit dynamic coupling model;

[0075] Step 302: performing time domain integration on the three-dimensional explicit dynamic coupling model to calculate the axial stress of each node at different positions and times during the steel casing penetration process;

[0076] Step 303: Analyze the density and change trend of stress distribution based on the axial stress of the casing at different positions and times, and locate the stress concentration area and distribution characteristics of the casing structure;

[0077] Step 304 : Determine the risk mode of buckling of the steel casing, including local buckling and global buckling, based on the characteristics of the stress concentration area, including location, range, and gradient.

[0078] In an embodiment of the present invention, the comprehensive dynamic load set obtained in step 206 is applied as a boundary condition to the steel casing structure in a three-dimensional explicit dynamic coupling model. First, it is clarified that the comprehensive dynamic load set includes a basic wave load component set, periodic excitation loads, ocean current drag forces, and internal wave and current impact effects. These loads have specific distribution and variation patterns in the time, frequency, and spatial domains. In finite element analysis software (such as LS-DYNA and ANSYS Explicit), the boundary condition setting module of the software applies the wave loads to the steel casing surface in the form of pressure or force according to their direction and point of action. The periodic excitation loads generated by the vibratory hammer are applied to the bottom of the steel casing or corresponding connection points in the form of simple harmonic loads or transient loads according to the action position and direction determined by the vibratory hammer-steel casing coupling dynamic architecture. The ocean current drag forces and internal wave and current impact effects are applied to the surface nodes at the corresponding locations of the steel casing based on their calculated results. During the application process, ensure that the size, direction and action time of the load are consistent with the comprehensive dynamic load set. At the same time, check whether other boundary conditions in the model (such as soil boundary constraints, steel casing top constraints, etc.) are reasonable to avoid affecting the accuracy of the calculation results due to improper boundary condition settings.

[0079] Step 302 performs a time-domain integral solution on the three-dimensional explicit dynamic coupling model after applying boundary conditions. During the calculation process, the mass matrix M, damping matrix C, and stiffness matrix K are updated in real time, taking into account the constitutive relationship of the steel casing material (e.g., bilinear model) and structural damping, as well as the contact interaction between the steel casing and the soil. This time-step calculation determines the displacement, velocity, and acceleration of each node at different locations and times during the steel casing penetration process. The axial stress at each node is then calculated based on material mechanics formulas.

[0080] Step 303: Extract the axial stress values ​​at different positions and times from the steel casing dynamic analysis model (e.g., a 3D explicit dynamic coupling model) and organize them into a structured data table. The table contains the following key information:

[0081] Spatial coordinates: covers the axial coordinates of the steel casing (such as the longitudinal position z from the top to the bottom) and circumferential angles (such as 0°, 90°, 180°, 270°, etc.).

[0082] Time parameter: corresponds to the time step in the time domain integration.

[0083] Stress value: the axial stress of the node at this position and time.

[0084] Check the stress values ​​at different axial positions of the steel casing to determine whether there is a high stress situation within a certain depth range. For a specific axial position (for example, z=10m), check the stress values ​​at various circumferential angles to determine whether the stress in a certain angle range is significantly higher than that in other directions. For the high-stress areas initially identified, check the changes in stress in this area over time to determine whether the stress will show periodic concentration due to load changes during the vibration penetration process. Set a stress threshold (for example, 70% of the yield strength of the steel) and filter out nodes where the stress exceeds this threshold. Count the spatial distribution density of these high-stress nodes. If the spatial density of high-stress nodes in a certain area is significantly higher than that of the surrounding areas (for example, the number of high-stress nodes per unit length exceeds twice the average value), then the area is identified as a potential stress concentration area. Use statistical methods (such as the local outlier factor (LOF) algorithm) to find locations where the stress values ​​are much higher than those of their adjacent nodes. These locations may be stress concentration areas.

[0085] For each node, the stress difference between it and adjacent nodes is calculated along the axial and circumferential directions to obtain the stress gradient. Areas where the gradient exceeds three times the average gradient indicate a dramatic stress change, which can easily lead to stress concentration. Ultimately, relevant information about the stress concentration area is determined, including its location (e.g., axial depth z = 20-25 m, circumferential range 180° ± 30°), distribution characteristics (e.g., banded circumferential distribution or localized point-like concentration), and gradient magnitude (e.g., axial gradient of 50 MPa / m, circumferential gradient of 80 MPa / rad).

[0086] Step 304: Extract the following key features from the analysis results of step 303:

[0087] Position characteristics: the specific location of the stress concentration area on the steel casing (such as near the bottom connection flange, the sudden change in wall thickness in the middle);

[0088] Range characteristics: the axial length of the region (e.g., 2 m), the circumferential angular range (e.g., 60°), or the number of structural units occupied;

[0089] Gradient characteristics: the maximum value and distribution direction of the stress gradient (such as the axial gradient is dominant, or the circumferential gradient is significant).

[0090] Local buckling occurs in small, high-gradient stress concentration areas and is characterized by the following:

[0091] The stress concentration area is smaller than the diameter of the steel casing, and the stress gradient is greater than the steel yield strength, indicating that the local cross-section is subject to excessive non-uniform stress. Structural geometric defects: For example, local depressions or weld protrusions have a stress concentration factor exceeding 2.0 (calculated through finite element simulation).

[0092] Global buckling involves the coupling of large-scale stress distribution with the overall stiffness of the structure and is characterized by the following:

[0093] The slenderness ratio of the steel casing exceeds the critical value, such as the casing slenderness ratio >100 (for Q345 steel); the axial average stress is close to the Euler critical stress; the buckling form is overall bending or compression bar instability, and the buckling wavelength is of the same order of magnitude as the steel casing length; key influencing factors include bottom constraint conditions (such as embedment depth), top load eccentricity, and lateral resistance distribution of seawater and soil.

[0094] If high-gradient local stresses and overall axial pressures coexist in stress concentration areas (e.g., high-frequency loads combined with static pressure during vibration penetration), the critical load safety factor must be calculated using eigenvalue buckling analysis or nonlinear buckling simulation. Buckling risk modes for the steel casing must be identified (e.g., "local buckling in the central circumferential stress concentration area" or "overall buckling due to excessive slenderness of the entire casing"), with the risk level (high, medium, or low) and corresponding stress thresholds (e.g., 350 MPa for local buckling and 5000 kN for overall buckling).

[0095] In a deep-sea wind power project, the dynamic characteristics of a large-diameter steel casing (8 meters in diameter and 60 meters in length) were analyzed. A comprehensive dynamic load set, including wave loads, vibratory hammer excitation loads, ocean current drag forces, and internal wave and current impact effects, was applied to the steel casing structure within an established 3D explicit dynamic coupling model.

[0096] LS-DYNA software was used for time-domain integration calculations, with a time step of 0.001 seconds. After tens of thousands of calculation steps, the axial stress magnitudes at various nodes at different locations and times during the steel casing penetration process were determined. The results were then imported into Tecplot software to generate a stress propagation contour map. The contour map clearly shows that the top flange connection and the middle portion of the steel casing, near the seabed, show significantly darker colors and denser contour lines, identifying these two areas as stress concentration zones.

[0097] Further analysis revealed that the top flange connection was subject to severe stress concentration due to the load transmitted from the upper structure and the excitation force of the vibrating hammer, posing a risk of local buckling. In the middle part close to the seabed, the steel casing was subjected to greater overall stress and had a larger slenderness ratio due to the combined effects of ocean currents and waves, posing a potential risk of overall buckling.

[0098] By accurately applying a comprehensive dynamic load set to a three-dimensional explicit dynamic coupling model and performing time-domain integral calculations, the stress state of the steel casing in a complex marine environment and during construction can be accurately simulated, and the axial stress of each node at different positions and times can be obtained. Compared with traditional simplified analysis methods, this method more realistically reflects the actual stress distribution of the steel casing and provides reliable data support for structural analysis. Combined with the characteristics of the stress concentration area, it is possible to accurately judge the local buckling and overall buckling risk modes of the steel casing and identify the potential instability risk of the structure in advance. Compared with traditional empirical judgment methods, this method is based on precise calculations and analysis, which improves the accuracy and reliability of buckling risk assessment, helps to take targeted preventive measures, and ensures the safety and stability of the steel casing structure.

[0099] By analyzing stress distribution characteristics and buckling risk modalities, a clear direction is provided for the structural optimization design of steel casings. For example, structural design can be strengthened (such as adding stiffeners and optimizing connection methods) in areas of stress concentration, and structural dimensions or material parameters can be adjusted in areas with higher buckling risk. This improves the bearing capacity and anti-buckling performance of the steel casing, reduces construction and operation risks, and achieves economical and rational structural design.

[0100] In a preferred embodiment of the present invention, step 302, performing time-domain integration on the three-dimensional explicit dynamic coupling model to calculate the axial stress magnitudes of each node at different positions and times during the steel casing penetration process, may include:

[0101] Step 3021, select a unit from the three-dimensional explicit dynamic coupling model and mark it as unit ;

[0102] Step 3022, determine the unit Corresponding elastic modulus of steel casing material and measuring unit The length of the unit The force on each node; according to the corresponding elements in the stiffness matrix and the time step, the restoring force generated by the elastic deformation is obtained;

[0103] Step 3023, according to the action on the unit Load vector on element The force on each node and the restoring force generated by elastic deformation determine the unit Comprehensive stress conditions of each node;

[0104] Step 3024, using the elements in the inverse matrix of the mass matrix, the comprehensive force condition is processed to obtain the Strain-related quantities at each node;

[0105] Step 3025, according to the elastic modulus, unit Length and unit The strain-related quantities of each node in the unit are obtained of axial stress.

[0106] In the embodiment of the present invention, a unit is selected from the three-dimensional explicit dynamic coupling model. Finally, determine the elastic modulus of the steel casing material This parameter is usually determined by tensile testing of materials according to Hooke's law. Length , which can be obtained from the model geometry data. The mass matrix is ​​determined according to the unit dynamics theory. , damping matrix and the stiffness matrix Taking the two-dimensional rod element as an example, the mass matrix ( is the unit mass), the stiffness matrix ( is the unit cross-sectional area), the damping matrix adopts the Rayleigh damping model = + ( 、 is the Rayleigh damping coefficient). Calculate the inverse mass matrix , whose elements are recorded as .

[0107] Step 3022, damping matrix element With time step Multiply to get = For the unit Each node ( =1 2 ⋯ , is the total number of nodes), With the node at time Displacement Multiply them together, and then sum the products of all nodes, that is, , this result is the unit Each node at time Forces due to damping effects. Stiffness matrix elements The square of the time step Multiply to get = For each node ,Will With the node at time Displacement Multiply and then sum over all nodes to get , which is the restoring force generated by elastic deformation.

[0108] Step 3023, known time Acting on the unit No. Load vectors at nodes , through the formula , calculate the unit No. Nodes at time The combined force after considering damping, elastic recovery and external loads.

[0109] Step 3024, using the mass matrix inverse matrix element , weighted processing is performed on the above comprehensive forces to obtain , convert it into a quantity related to acceleration; then From 1 to Sum, we get .

[0110] Through the strain-displacement matrix , the above results about From 1 to Sum, that is ,

[0111] Thus, we get the unit Quantities related to the strain at each node.

[0112] Step 3025: According to Hooke's law, the elastic modulus Multiply , and then multiply it by the above-mentioned quantity related to strain, through the formula ,

[0113] Finally, the unit is calculated At the moment of axial stress.

[0114] This formula, based on finite element theory and dynamic equations, comprehensively considers multiple factors such as material properties, unit geometry, mass, damping, stiffness, and external loads. It can accurately calculate the axial stress of each unit of the steel casing at different times. Compared with simplified calculation methods, it more realistically reflects the mechanical response of the steel casing under complex loads, providing reliable data for structural analysis. By combining the time dimension with numerical integration methods, it effectively captures the temporal variation of stress during the penetration of the steel casing and accurately simulates the dynamic process of stress propagation and distribution in the structure. This helps to deeply understand the mechanical behavior of the steel casing during construction and service, providing a scientific basis for engineering decision-making.

[0115] Accurate stress calculations can help engineers identify high-stress areas and weak links in the steel casing structure, allowing them to optimize the structure accordingly, such as adjusting wall thickness and adding reinforcements. This improves the structure's load-bearing capacity and stability, while avoiding overdesign and reducing project costs. Accurate stress calculations enable more reliable assessments of the steel casing's safety performance under complex marine environments and construction loads, enabling early detection of potential structural safety hazards and the implementation of appropriate preventive measures to ensure the safe construction and long-term stable operation of deep-sea temporary platforms.

[0116] In a preferred embodiment of the present invention, the above step 4, which deploys a waterproof full-bridge strain sensor array in the stress concentration area of ​​the cylindrical structure, and uses the waterproof full-bridge strain sensor array to collect the stress time history curve of the entire process of vibration penetration of the steel casing in real time, and obtains the dynamic data of stress changes of the steel casing under the actual working state, may include:

[0117] Step 401: Determine waterproof full-bridge strain sensors based on the stress concentration area of ​​the cylindrical structure, and evenly arrange waterproof full-bridge strain sensor arrays in the stress concentration area along the axial and circumferential directions to form a three-dimensional monitoring network;

[0118] Step 402 , connecting the signal lines of the waterproof full-bridge strain sensor array to a data acquisition instrument, and configuring the sampling frequency and storage path of the data acquisition instrument;

[0119] Step 403: During the vibration penetration of the steel casing, the waterproof full-bridge strain sensor array senses the strain change of the steel casing in real time, converts the strain signal into an electrical signal, and transmits it to the data acquisition instrument via the data transmission cable;

[0120] Step 404: read the original strain data from the data acquisition instrument and pre-process the original strain data to obtain processed strain data;

[0121] In step 405, the processed strain data is converted into stress data according to the elastic modulus of the steel casing material and Hooke's law, and a stress time history curve of the entire penetration process is drawn with time and stress as coordinates to obtain the stress change law, peak stress moment and size dynamic data.

[0122] In this embodiment of the present invention, through preliminary stress analysis of the steel casing (e.g., identifying stress concentration areas based on stress distribution characteristics calculated using a three-dimensional explicit dynamic coupling model), key areas requiring monitoring are identified. For steel casing, stress concentration areas typically occur at structural joints (e.g., flange connections), locations with sudden cross-sectional changes (e.g., locations with varying wall thicknesses), and areas subject to complex loads (e.g., locations near the seabed subject to significant earth pressure and wave forces). After identifying these stress concentration areas, a suitable waterproof full-bridge strain sensor is selected. This type of sensor must exhibit excellent waterproof performance (e.g., a sealed waterproof housing with an IP68 rating or higher to ensure long-term stable operation in marine environments), high accuracy (measurement error controlled within ±0.5%), and a wide measurement range (capable of covering the strain range expected from the steel casing under actual operating conditions).

[0123] Waterproof full-bridge strain sensors are evenly distributed axially and circumferentially in stress concentration areas. For axial deployment, sensor spacing is appropriately determined based on the length of the steel casing and the stress gradient (e.g., one sensor every 1-2 meters) to ensure that axial stress changes can be captured. For circumferential deployment, sensors are evenly distributed around the circumference of the steel casing (e.g., one sensor every 45° or 60°) to monitor stress conditions in different directions. This combined axial and circumferential approach forms a three-dimensional monitoring network, enabling comprehensive, multi-dimensional monitoring of stress concentration areas within the steel casing.

[0124] Step 402, connect the signal line of the waterproof full-bridge strain sensor array to the data acquisition instrument. The signal line needs to use a cable with good shielding performance (such as a double-shielded coaxial cable) to reduce external electromagnetic interference and ensure the accuracy and stability of signal transmission. During the connection process, strictly follow the interface specifications of the sensor and data acquisition instrument to ensure a firm connection and good contact. Configure the sampling frequency and storage path of the data acquisition instrument. The setting of the sampling frequency needs to be determined according to the dynamic characteristics of the steel casing vibration penetration process. Generally speaking, in order to accurately capture the high-frequency components of stress changes, the sampling frequency should be set to more than 10 times the vibration frequency of the steel casing (for example, if the maximum vibration frequency of the steel casing is 50Hz, the sampling frequency can be set to 500Hz and above).

[0125] In step 403, during the vibration penetration of the steel casing, the waterproof full-bridge strain sensor array begins operation. When the steel casing is strained by external loads (such as wave forces, vibration hammer excitation forces, and ocean current drag), the strain gauges within the sensor deform, causing their resistance to change. Based on the Wheatstone bridge principle, this change in resistance is converted into an electrical signal output. The sensor converts the strain signal into an electrical signal, which is then transmitted to the data acquisition device via a data transmission cable. During the transmission process, a signal amplifier is used to amplify the electrical signal to prevent signal attenuation and interference. The transmission cables are carefully routed to avoid parallel or crossover with high-voltage lines, minimizing electromagnetic coupling interference. Furthermore, regular inspections of cable connections and insulation performance are performed to ensure reliable data transmission.

[0126] Step 404: Read the raw strain data from the data acquisition instrument. The raw strain data may contain noise, outliers, drift, and other problems, so it needs to be preprocessed. First, use a filtering algorithm (such as low-pass filtering, band-pass filtering, etc.) to remove high-frequency noise and low-frequency drift, retaining the effective signal components related to the stress change of the steel casing. For example, for the noise generated by high-frequency electromagnetic interference, the noise above a certain frequency (such as the sampling frequency) can be filtered out by a low-pass filter. ) signal filtering. Data is then processed for outliers. Outliers are identified using statistical methods (such as the 3σ criterion), and data points that deviate from the normal range are corrected or removed. For example, if a data point differs from the mean by more than three standard deviations, it is considered an outlier and can be replaced with the average of the adjacent data points. Finally, the data is normalized to map it to a specific interval (such as [0, 1]).

[0127] Step 405 converts the processed strain data into stress data based on the elastic modulus of the steel casing material and Hooke's law. Given the elastic modulus of the steel casing material (available from design data), multiplying each strain data point by the elastic modulus yields the corresponding stress data. Using time and stress as coordinates, a stress-time history curve for the entire steel casing penetration process is plotted using data processing software (such as MATLAB or Origin). During the plotting process, the curve can be smoothed for clarity and visualization. By analyzing the stress-time history curve, it is possible to determine stress variation patterns (such as stress fluctuation trends over time and cyclical characteristics), as well as dynamic data on the peak stress moment and magnitude. For example, the curve can directly reveal the moment when stress reaches its peak, as well as the specific value of the peak stress, providing important information for assessing the stress state and structural safety of the steel casing.

[0128] Consider an offshore wind power project involving the construction of a large offshore wind turbine foundation, utilizing a large-diameter steel casing as the supporting structure. Preliminary analysis based on a three-dimensional explicit dynamic coupling model revealed significant stress concentrations at the flange connection on the top of the steel casing and in the central region near the seabed. To address these stress concentrations, waterproof full-bridge strain sensors with an IP68 rating and ±0.3% measurement accuracy were selected. Eight sensors were placed around the flange connection on the top of the steel casing, one every 45° along the circumference. A sensor was also placed 1 meter above and below the flange. In the central region near the seabed, six sensors were placed around the circumference, one every 60°. Sensors were also placed every 1.5 meters along the axial direction, forming a three-dimensional monitoring network. The sensor signal cables were connected to a high-precision data acquisition system via double-shielded coaxial cables. The data acquisition system's sampling frequency was set to 800 Hz, and the storage path was an external 1TB removable hard drive, with automatic cyclic storage enabled.

[0129] During the vibratory penetration of the steel casing, the strain sensor array senses the steel casing's strain changes in real time, converts the strain signals into electrical signals, and transmits them to the data acquisition instrument. After reading the raw strain data, a low-pass filter is used to remove high-frequency noise, and outliers are detected and corrected using the 3σ criterion, and the data is normalized.

[0130] The elastic modulus of the steel casing material is known to be 206×109Pa. The processed strain data was converted into stress data according to Hooke's law, and a stress-time curve was plotted using MATLAB. The curve clearly shows that a significant stress peak occurs when the steel casing penetrates near the seabed, reaching 350×106Pa 120 minutes after penetration begins. This provides critical data support for subsequent structural safety assessments and construction process optimization of the steel casing.

[0131] By deploying a waterproof full-bridge strain sensor array in stress concentration areas, engineers can accurately and in real time collect stress data on the steel casing throughout the entire vibration penetration process. Compared to traditional manual inspection or discrete point monitoring methods, this method provides more comprehensive and continuous stress information, enabling timely detection of abnormal stress conditions in the steel casing in complex marine environments and during construction. Accurately capturing dynamic data such as stress variation patterns, peak stress moments, and magnitudes helps engineers gain a deeper understanding of the actual stress state of the steel casing, proactively identifying potential structural safety hazards (such as localized plastic deformation and fatigue failure caused by stress concentration), enabling timely implementation of appropriate reinforcement or adjustment measures to ensure the safety and stability of the steel casing and reduce the probability of engineering accidents. Stress-time curves reflect the stress characteristics of the steel casing at different construction stages, providing data support for optimizing construction processes. For example, based on stress variations, vibratory hammer operating parameters (such as excitation force and vibration frequency) can be appropriately adjusted to reduce peak stress on the steel casing, avoid structural damage caused by excessive stress, and improve construction efficiency and quality. The collected dynamic stress data provides a valuable basis for the design, maintenance, and management of steel casings. Based on this data, the design model of the steel casing can be verified and optimized, improving the design of subsequent similar projects. During the operation and maintenance phase of the steel casing, long-term monitoring of stress changes can be used to assess the durability and remaining life of the structure, develop scientific and reasonable maintenance plans, and achieve data-driven intelligent decision-making. The waterproof full-bridge strain sensor array has excellent waterproof performance and anti-interference capabilities, and can operate stably in harsh marine environments and adapt to high humidity, strong corrosion, and complex electromagnetic interference conditions. It ensures the reliability and accuracy of data acquisition during the vibration penetration of the steel casing, providing a reliable technical means for monitoring marine engineering structures.

[0132] In a preferred embodiment of the present invention, the above step 5, based on the dynamic data of stress changes of the steel casing under actual working conditions, modifies the wall thickness of the steel casing and the material constitutive model parameters, and establishes a dynamic stress threshold database in combination with different water depth gradients and soil stratification factors to achieve adaptive matching of the steel casing design parameters with the marine environmental conditions, which may include:

[0133] Step 501: Analyze the dynamic data of stress changes of the steel casing under actual working conditions and extract stress characteristic parameters, including stress peak value and stress change frequency;

[0134] Step 502: Using a parameter inversion algorithm, the stress characteristic parameter is used as the objective function, and the steel casing wall thickness and material constitutive model parameters are used as design variables. Through continuous iteration, the revised steel casing wall thickness and material constitutive model parameters are obtained.

[0135] Step 503: Acquire marine environmental data and geological data related to different water depth gradients and soil stratification combinations, substitute the corrected steel casing parameters, marine environmental data, and geological data into a three-dimensional explicit dynamic coupling model, analyze the stress state of the steel casing under various conditions, and obtain simulation analysis results;

[0136] Step 504: Based on the simulation analysis results, a dynamic stress threshold database is established, including stress thresholds of steel casings, corresponding steel casing parameters, marine environment, and geological parameters under different water depth gradients and soil layer combinations.

[0137] Step 505: Acquire data matching the actual marine environmental conditions from the dynamic stress threshold database, including the stress threshold and the corresponding steel casing parameters, and compare the expected stress state of the steel casing under the actual marine environmental conditions with the stress threshold in the reference data. If the expected stress state is greater than or equal to the stress threshold, optimize and adjust the design parameters of the steel casing to achieve adaptive matching between the steel casing design parameters and the marine environmental conditions.

[0138] In an embodiment of the present invention, after obtaining dynamic stress change data of the steel casing under actual working conditions (such as the stress time history curve collected by a waterproof full-bridge strain sensor array), professional data processing software (such as MATLAB or Python's data analysis library) is used to conduct in-depth analysis of the data. For the stress time history curve, the maximum value in the curve is found by traversing the data points. This value is the stress peak. To avoid misjudgment due to data noise, a local extreme value search algorithm can be used to determine whether it is a true peak point within a certain data window (for example, the 10 data points before and after). For the stress change frequency, the stress time history data is subjected to a fast Fourier transform (FFT) to convert the time domain data into frequency domain data. In the frequency domain graph, the frequency components with concentrated energy are found. These frequencies are the main frequencies of stress change. Frequency thresholds can also be set to filter out frequency values ​​with practical significance and remove invalid frequencies caused by low-frequency and high-frequency noise interference.

[0139] In step 502, the parameter inversion algorithm adopts an optimization algorithm, such as a bacterial foraging algorithm. The stress peak value and stress change frequency extracted in step 501 are used as the objective function, that is, the optimization goal is set to make the calculated stress characteristic parameters as close as possible to the actual extracted parameters. The steel casing wall thickness and material constitutive model parameters (such as elastic modulus, yield strength, Poisson's ratio, etc.) are used as design variables. The fitness function value is calculated by comparing the difference between the calculated stress characteristic parameters and the actual objective function. The higher the fitness function value, the closer the parameter combination is to the actual situation. According to the fitness function value, a new parameter combination population is generated through genetic operations such as selection, crossover, and mutation, and this process is continuously iterated. When the maximum number of iterations is met, the obtained parameter combination is the corrected steel casing wall thickness and material constitutive model parameters.

[0140] In step 503, ocean monitoring equipment (such as sonar, temperature and salinity meters) and geological exploration methods (such as borehole sampling and static penetration) are used to obtain marine environmental data (such as wave forces, current velocity, and seawater density) and geological data (such as the elastic modulus, Poisson's ratio, internal friction angle, and cohesion of the soil) related to different water depth gradients and soil stratification combinations. The corrected steel casing parameters (wall thickness, material constitutive model parameters), marine environmental data, and geological data are substituted into a three-dimensional explicit dynamic coupling model. In finite element analysis software (such as ANSYS or ABAQUS), appropriate boundary conditions and solution parameters are set, such as the contact type between the steel casing and the soil (friction contact or bonded contact) and the time step (determined based on the dynamic response characteristics to ensure that the details of stress changes are captured). The model is run to analyze the stress state of the steel casing under various conditions, and simulation results are obtained, including stress magnitudes and distribution contours at different locations and times on the steel casing.

[0141] In step 504, the simulation analysis results obtained in step 503 are organized and analyzed. Based on different water depth gradients, soil stratification combinations, and other conditions, the maximum stress value that the steel casing can withstand under these conditions is determined and defined as the stress threshold. The stress threshold, corresponding steel casing parameters (corrected wall thickness, material constitutive parameters), marine environmental parameters (wave forces, current velocity, etc.), and geological parameters (soil mechanical parameters) are organized into a data table. A dynamic stress threshold database is established using a database management system (such as MySQL or SQL Server). The data table is imported into the database, and a reasonable indexing and query mechanism is configured.

[0142] Step 505: Before designing a new project or constructing a steel casing, obtain actual marine environmental data (such as water depth, wave statistics, and ocean current data at the project site) and geological survey data. From the dynamic stress threshold database, query the database to obtain data matching the actual marine environmental conditions, including stress thresholds and corresponding steel casing parameters. Use a three-dimensional explicit dynamic coupling model or other mechanical analysis methods to predict the expected stress state of the steel casing under actual marine environmental conditions. Compare the expected stress state with the stress threshold in the reference data. If the expected stress state is greater than or equal to the stress threshold, the currently designed steel casing may not meet the load-bearing requirements under the actual environment. At this point, optimize and adjust the steel casing design parameters (such as increasing wall thickness and adjusting material properties) based on the corresponding optimized steel casing parameter recommendations in the database, and re-simulate and analyze until the expected stress state is less than the stress threshold, achieving adaptive matching of the steel casing design parameters with the marine environmental conditions.

[0143] Assume that in a coastal bridge project, a conventionally designed steel casing with a diameter of 3 meters, a wall thickness of 20 mm, and a material of Q345 steel is used in the initial construction. During the vibration penetration of the steel casing and subsequent use, dynamic data of stress changes are collected through the waterproof full-bridge strain sensor array. The data is analyzed and the stress peak value of 320 MPa is extracted, and the main frequencies of stress changes are 20 Hz and 35 Hz. The bacterial foraging algorithm is used for parameter inversion, with the stress peak value and frequency as the objective function, and the steel casing wall thickness and the elastic modulus and yield strength of the material as design variables. After 100 iterations, the corrected steel casing wall thickness is 22 mm, and the material elastic modulus is adjusted to 2.1× MPa, and the yield strength is adjusted to 360 MPa.

[0144] Through marine environmental monitoring and geological surveys, relevant data on different water depth gradients (10-30 meters) and soil layer combinations (silty clay in the upper layer and medium sand in the lower layer) at the project site were obtained. The corrected steel casing parameters and environmental geological data were substituted into the three-dimensional explicit dynamic coupling model, and the stress state of the steel casing under different conditions was obtained through simulation analysis. Based on the simulation results, a dynamic stress threshold database was established. For example, under the conditions of a water depth of 20 meters, a thickness of 10 meters for the upper silty clay layer and a thickness of 10 meters for the lower medium sand layer, the stress threshold of the steel casing was determined to be 300 MPa. The corresponding steel casing parameters are a wall thickness of 2 mm and a material elastic modulus of 2.1× MPa, etc.

[0145] In future projects with similar marine environmental conditions, the corresponding stress threshold and steel casing parameters will be obtained by querying the database. If the calculated expected stress state of the steel casing in the new project is 310 MPa, exceeding the stress threshold, the steel casing wall thickness will be further increased to 24 mm and the simulation analysis will be repeated until the expected stress state is less than the stress threshold, achieving adaptive matching of the steel casing design with the environment.

[0146] Correcting steel casing parameters based on actual stress data overcomes the limitations of traditional design practices that rely on empirical formulas and assumptions, making design parameters more aligned with actual operating conditions. This improves the accuracy and reliability of steel casing design and avoids material waste or safety hazards caused by conservative design. Taking into account marine environmental and geological factors such as varying water depth gradients and soil stratification, a dynamic stress threshold database is established to adaptively match steel casing design parameters to actual environmental conditions. This ensures the stable operation of steel casing in complex and changing marine environments and enhances the adaptability of engineering structures to diverse environments. Parameter inversion and dynamic threshold analysis allow for rational adjustment of steel casing wall thickness and material properties, avoiding overdesign, reducing unnecessary consumption of steel and other materials, lowering construction costs, and improving resource efficiency, achieving a balance between economic benefits and project quality. Accurate stress threshold assessment and timely optimization of design parameters can proactively prevent structural damage (such as buckling and fracture) caused by excessive stress in steel casings, ensuring their structural safety during construction and operation, mitigating the risk of engineering accidents and minimizing potential economic losses and social impacts. The dynamic stress threshold database has accumulated a large amount of steel casing stress data and design parameters under different conditions, providing rich data reference and technical support for the subsequent design, construction and maintenance of similar marine projects, and helping to promote the improvement of design methods and technological innovation in the field of marine engineering.

[0147] In a preferred embodiment of the present invention, the above step 502 adopts a parameter inversion algorithm, uses the stress characteristic parameter as the objective function, and the steel casing wall thickness and material constitutive model parameters as the design variables, and obtains the corrected steel casing wall thickness and material constitutive model parameters through continuous iteration, which may include:

[0148] Step 5021: Using the bacterial foraging algorithm as a parameter inversion algorithm; combining the steel casing wall thickness and the material constitutive model parameters into a parameter vector, each parameter vector representing a bacterial individual, and randomly generating a certain number of bacterial individuals to form an initial bacterial population;

[0149] Step 5022: Set the parameters of the bacterial foraging algorithm, including the chemotaxis step length, the number of chemotaxis times, the number of replications, and the migration probability. Substitute the steel casing parameter vector corresponding to each bacterial individual into the three-dimensional explicit dynamic coupling model to simulate the stress conditions of the steel casing under actual working conditions and obtain the stress response of the steel casing.

[0150] Step 5023: Using the stress characteristic parameter as the objective function and calculating the fitness function value corresponding to each bacterial individual according to the stress response of the steel casing;

[0151] Step 5024: For each bacterial individual in the group, randomly select a direction to move in to obtain a new parameter vector;

[0152] Step 5025 , substituting the new parameter vector into the three-dimensional explicit dynamic coupling model to calculate the stress response, and re-evaluating the fitness function value of the corresponding bacterial individual;

[0153] Step 5026: Repeat the chemotaxis movement and evaluation process until a preset number of chemotaxis attempts is reached. The entire population is ranked according to the fitness function values ​​of the bacterial individuals to determine a portion of candidate bacterial individuals. The candidate bacterial individuals are then replicated to generate new individuals identical to the candidate bacterial individuals.

[0154] Step 5027: For each bacterial individual in the population, a random number between 0 and 1 is generated and compared with the preset migration probability. If the random number is less than the migration probability, the corresponding bacterial individual migrates and a new parameter vector is generated. If the random number is greater than the migration probability, the bacterial individual remains in its original position.

[0155] Step 5028, repeatedly perform the fitness function value calculation, chemotaxis, replication and migration operations until the preset number of iterations is reached, determine the final parameter vector based on the fitness function value of the bacterial individuals in the group, and use the final parameter vector as the corrected steel casing wall thickness and material constitutive model parameters.

[0156] In the embodiment of the present invention, the bacterial foraging algorithm is an intelligent optimization algorithm inspired by the behavior of bacteria in finding food in the environment. First, the wall thickness of the steel casing and the material constitutive model parameters (such as elastic modulus, yield strength, Poisson's ratio, etc.) are combined into a parameter vector. This vector is like the "gene" carried by individual bacteria and contains the key information of the steel casing design. For example, if the wall thickness of the steel casing is expressed as The elastic modulus is , the yield strength is , Poisson's ratio is , then the parameter vector can be expressed as [ ]. According to the scale of the actual problem and computing resources, a certain number of random During the generation process, the elements in each parameter vector must be randomly selected within a reasonable range of values. For example, the wall thickness of the steel casing must be between the minimum and maximum values ​​required by the engineering specifications, and the material parameters must conform to the actual performance range of the steel.

[0157] Step 5022: The chemotaxis step size determines the size of each chemotaxis movement of a bacterial individual, which affects the algorithm's ability to explore the search space. A step size that is too large may cause the algorithm to miss the optimal solution, while a step size that is too small will slow the algorithm's convergence. The chemotaxis count specifies the number of chemotaxis movements a bacterial individual makes before a replication operation, which controls the algorithm's search depth in a local area. The replication count determines the number of times a bacterial individual with good fitness is replicated. This replication operation preserves excellent parameter combinations and accelerates algorithm convergence. The migration probability indicates the likelihood of a bacterial individual migrating and is used to escape the local optimal solution, increasing the algorithm's global search capability.

[0158] The steel casing parameter vector corresponding to each bacterial individual is substituted into a three-dimensional explicit dynamic coupling model. In finite element analysis software (such as ANSYS or LS-DYNA), model parameters such as the steel casing's geometry and material properties are set based on the parameter vectors. Appropriate boundary conditions and load conditions are then set, taking into account actual marine environmental conditions (such as wave forces, current velocities, and soil mechanics). The model is then run to simulate the stresses acting on the steel casing under actual operating conditions, thereby determining its stress response.

[0159] In step 5023, stress characteristic parameters (such as peak stress and stress variation frequency) extracted from the actual operating state are used as the objective function. Based on the stress response of the steel casing obtained using the three-dimensional explicit dynamic coupling model, the fitness function value corresponding to each bacterial individual is calculated. The fitness function measures the degree to which the parameter vector represented by the bacterial individual matches the actual situation.

[0160] For example, if the objective function is the peak stress and stress change frequency The peak stress value calculated by the model is , the frequency is , then the fitness function ,in and Is the weight coefficient, which is used to adjust the importance of different objective functions. and The value range of is between 0 and 1, and + = 1. This is because the weight coefficient is essentially a proportional distribution that determines the relative importance of stress peak and stress change frequency in the overall evaluation, and their sum of 1 ensures comprehensive consideration on a unified scale.

[0161] In actual scenarios, if the sea conditions in a certain ocean area are complex and the wave action is frequent and strong, the stress peak will have a more prominent impact on the safety of the steel casing structure. For example, after comprehensive analysis of the historical sea conditions data, past engineering cases and the stress characteristics of the steel casing in this area, it is determined that =0.7, then =1-0.7=0.3. With this setting, when calculating the fitness function value, the difference in stress peak value has a greater impact on the result, which is more consistent with the actual situation in the area and can more accurately screen out parameter vectors that have a high degree of match with the actual working conditions.

[0162] On the contrary, if in certain specific sea areas, the stress change frequency has a significant impact on the fatigue life of the steel casing, such as the presence of periodic ocean currents or internal wave currents, which causes the steel casing to frequently bear alternating stress, then the stress should be increased. Assume that through detailed structural fatigue analysis and environmental load study, the =0.6, then =1-0.6=0.4, which highlights the importance of stress change frequency in evaluating the degree of matching between parameter vector and actual situation.

[0163] The smaller the fitness function value, the more accurate the parameter vector corresponding to the bacterial individual is. By properly adjusting the weight coefficients, the bacterial foraging algorithm can more accurately balance the two factors of stress peak and stress change frequency when searching for the final steel casing design parameter vector, improving the accuracy and reliability of the design parameters and thus ensuring the structural safety and stability of the steel casing in complex marine environments.

[0164] In step 5024, for each bacterial individual in the population, a direction is randomly selected in the search space for movement, thereby obtaining a new parameter vector. The search space here is a multidimensional space consisting of the range of values ​​of the steel casing wall thickness and the material constitutive model parameters. The random selection direction can be achieved by generating random increments in each parameter dimension. For example, for the parameter vector [ ], add random numbers to each dimension , and obtain the new parameter vector .

[0165] In step 5025, the new parameter vector is substituted into the three-dimensional explicit dynamic coupling model, the model parameters are reset, and calculations are performed to obtain a new stress response. Based on the new stress response, the fitness function value of the corresponding bacterial individual is re-evaluated according to the fitness function defined in step 5023. By comparing the fitness function values ​​before and after the movement, it is determined whether the movement has brought the bacterial individual closer to the final solution.

[0166] In step 5026, the chemotactic movement and evaluation process of steps 5024 and 5025 is repeated until the preset number of chemotactic attempts is reached. At this point, the entire bacterial population is ranked from smallest to largest (smaller fitness function values ​​are preferred) based on the fitness function values ​​of the individual bacteria. From the ranked population, a subset of bacterial individuals with good fitness are selected as candidate bacterial individuals (e.g., the top 50% of individuals). These candidate bacterial individuals are replicated to generate new individuals identical to the candidate individuals. The purpose of the replication operation is to preserve and expand the proportion of parameter combinations with good fitness within the population, accelerating the algorithm's convergence to the optimal solution. The newly generated individuals share the same parameter vectors as the original candidate individuals and will participate in subsequent calculations.

[0167] In step 5027, a random number between 0 and 1 is generated for each bacterial individual in the population. This random number is compared to the preset migration probability. If the random number is less than the migration probability, the corresponding bacterial individual is considered to have migrated. At this point, a new set of parameter vectors is randomly generated in the search space, causing the bacterial individual to "jump" to a new position. This helps the algorithm escape the local optimal solution and explore a wider search space. If the random number is greater than the migration probability, the bacterial individual remains in its original position, meaning its parameter vector remains unchanged.

[0168] Step 5028 repeats the fitness function value calculation, chemotaxis, replication, and migration operations until the preset number of iterations is reached. During this iterative process, the bacterial population continuously searches for a more optimal parameter combination within the search space. When the preset number of iterations is reached, the parameter vector corresponding to the bacterial individual with the best fitness (i.e., the smallest fitness function value) is selected as the final parameter vector based on the fitness function values ​​of the individual bacteria in the population. This final parameter vector is then used as the revised steel casing wall thickness and material constitutive model parameters for subsequent design and analysis.

[0169] Suppose that in a deep-sea wind power project, parameters for a 5-meter-diameter steel casing need to be optimized. In the initial design, the casing wall thickness is 25 mm, and the material used is Q390 steel. The elastic modulus, yield strength, and Poisson's ratio are assumed to be 2.06×105 MPa, 390 MPa, and 0.3. The casing wall thickness, elastic modulus, yield strength, and Poisson's ratio are combined into a parameter vector. An initial population of 100 bacterial individuals is randomly generated. For example, the parameter vector for one individual is [23, 2.08×105, 400, 0.28]. The chemotaxis step size is set to [0.5, 1000, 10, 0.01] (corresponding to the step size for wall thickness, elastic modulus, yield strength, and Poisson's ratio, respectively), the number of chemotaxis attempts is 10, the number of replications is 5, and the migration probability is 0.1. The parameter vector of each bacterial individual is substituted into the three-dimensional explicit dynamic coupling model. Combined with the wave force, ocean current velocity and seabed soil parameters of the project area, the stress conditions of the steel casing are simulated to obtain the stress response.

[0170] Given that the peak stress value obtained from actual monitoring is 380 MPa and the main stress variation frequency is 15 Hz, and the weight coefficient is set to 0.5, the fitness function value of each bacterial individual is calculated based on the peak stress value and frequency calculated by the model. The chemotaxis, fitness evaluation, replication, and migration operations of the bacterial individuals are continuously performed. For example, after a bacterial individual undergoes chemotaxis, the parameter vector changes from [23, 2.08×10⁵, 400, 0.28] to [24, 2.09×10⁵, 410, 0.29], and the fitness function value is recalculated. The replication operation increases the number of individuals with better fitness; some individuals migrate based on the migration probability, generating a new parameter vector. When the preset number of iterations of 50 is reached, the bacterial individual with the best fitness is selected from the population, and its parameter vector is [26, 2.1×105, 420, 0.31], which is determined as the corrected steel casing wall thickness and material constitutive model parameters, that is, the steel casing wall thickness is corrected to 26 mm, the elastic modulus is 2.1×105 MPa, the yield strength is 420 MPa, and the Poisson's ratio is 0.31.

[0171] The bacterial foraging algorithm simulates the foraging behavior of bacteria in a complex environment. Through operations such as chemotaxis, replication, and migration, it conducts a global search in the parameter space. Compared with traditional optimization methods, it can more effectively avoid falling into local optimal solutions, increase the probability of finding the global optimal parameter combination, and ensure that the revised steel casing wall thickness and material constitutive model parameters are more in line with the actual working conditions. Using the actual stress characteristic parameters as the objective function, the field monitoring data is closely combined with the algorithm optimization, so that the steel casing design parameters can be modified based on the actual working conditions, changing the limitations of the previous reliance on empirical formulas or simplified model design, and improving the accuracy and reliability of the design. The steel casing wall thickness and material constitutive model parameters are optimized as a whole, taking into account the mutual influence and coupling relationship between the parameters, avoiding the unreasonable design that may result from single parameter optimization, and realizing the coordinated optimization of multiple parameters, making the steel casing design more scientific and reasonable. During the algorithm optimization process, a three-dimensional explicit dynamic coupling model was used to simulate the stresses on the steel casing in an actual marine environment. The influence of various complex factors, such as waves, currents, and soil, was fully considered, ensuring that the optimized parameters could still guarantee the safety and stability of the steel casing structure under complex and changing marine conditions. Accurate parameter optimization can avoid material waste caused by conservative design and prevent the risk of structural failure caused by insufficient design. While ensuring project quality, it can also reasonably control the manufacturing and maintenance costs of the steel casing and improve the economic benefits of the project.

[0172] An embodiment of the present invention further provides a computing device comprising: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the above-described method. All implementations in the above-described method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0173] The embodiment of the present invention further provides a computer-readable storage medium storing instructions, which, when executed on a computer, causes the computer to execute the above-described method. All implementations in the above-described method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0174] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for dynamic response analysis of large-diameter steel casing of a deep-sea temporary platform, characterized in that: The method comprises: According to the typhoon-prone characteristics of the target sea area and the structural parameters of the steel casing, a three-dimensional explicit dynamic coupling model was established; The wave load is decomposed according to the three-dimensional explicit dynamic coupling model. The velocity-related and inertial components of the wave load are calculated based on the relevant parameters in the three-dimensional explicit dynamic coupling model, including the diameter of the steel casing, the wave height, and the period, to form a basic wave load component set. Using the JONSWAP spectrum, a non-stationary random wave sequence is generated, and the wave sequence is spatially and temporally coupled with the basic wave load component set to construct a wave load model that reflects the characteristics of short-term sea conditions. Based on the model, operating frequency, and excitation force parameters of the vibratory hammer, a vibratory hammer-steel casing coupling dynamic architecture was established, and the periodic excitation load generated by the vibratory hammer on the bottom of the steel casing was calculated using an explicit integration algorithm. In the vibratory hammer-steel casing coupled dynamic architecture, the ocean current velocity field data is obtained and combined with the shape and size parameters of the steel casing to determine the magnitude and direction of the ocean current drag force on the steel casing; Analyze the structural response data of the steel casing under the drag force of the ocean current, and establish an internal wave and current impact load model based on the marine environmental parameters and the structural characteristics of the steel casing to quantify the internal wave and current impact effect; The basic wave load component set, periodic excitation load, ocean current drag force and internal wave impact effect are superimposed to form a comprehensive dynamic load set for the steel casing with time domain, frequency domain and space domain characteristics. The axial stress distribution characteristics during the penetration of the steel casing are calculated using the comprehensive dynamic load set of the steel casing. The stress distribution characteristics are then analyzed to identify the stress concentration areas and buckling risk modes of the casing structure. A waterproof full-bridge strain sensor array is deployed in the stress concentration area of ​​the cylinder structure. The waterproof full-bridge strain sensor array is used to collect the stress time history curve of the steel casing during the entire vibration penetration process in real time, and obtain the dynamic stress change data of the steel casing under actual working conditions. Based on the dynamic data of stress changes in the steel casing under actual working conditions, the wall thickness of the steel casing and the parameters of the material constitutive model are corrected. Marine environmental data and geological data related to different water depth gradients and soil stratification combinations are obtained. The corrected steel casing parameters, marine environmental data, and geological data are substituted into the three-dimensional explicit dynamic coupling model to analyze the stress state of the steel casing under various conditions and obtain simulation analysis results. Based on the simulation analysis results, a dynamic stress threshold database is established, including the stress threshold of the steel casing, the corresponding steel casing parameters, marine environment and geological parameters under different water depth gradients and soil layer combinations; Reference data matching the actual marine environmental conditions are obtained from the dynamic stress threshold database, including the stress threshold and the corresponding steel casing parameters. The expected stress state of the steel casing under the actual marine environmental conditions is compared with the stress threshold in the reference data. If the expected stress state is ≥ the stress threshold, the design parameters of the steel casing are optimized and adjusted to achieve adaptive matching between the steel casing design parameters and the marine environmental conditions.

2. The method for dynamic response analysis of large-diameter steel casing of deep-sea temporary platform according to claim 1 is characterized in that: According to the frequent typhoon occurrence characteristics of the target sea area and the structural parameters of the steel casing, a three-dimensional explicit dynamic coupling model is established, including: Based on the frequent occurrence of typhoons in the target sea area, the time-course data of wave elements, bottom current velocity and extreme wind speed are extracted. Based on the structural parameters of the steel casing, the quantitative values ​​of diameter, wall thickness and material yield strength are obtained. Using the structural parameters of the steel casing, the thin shell structure of the steel casing is constructed using shell elements. During the construction process, the geometric shape of the steel casing is analyzed and the properties of each element, including the elastic modulus and Poisson's ratio parameters, are set to simulate the mechanical properties of the steel casing under stress. Using solid elements according to the actual distribution of the strata, a soil model containing submarine silt layers, sandy clay layers, and weathered rock layers is constructed. According to the thin shell structure of the steel casing and the soil model, the contact algorithm, contact type and contact parameters between the steel casing and the soil are set to simulate the contact pressure transmission and relative sliding behavior between the steel casing and the soil; For the steel casing material, a bilinear model is defined, and the elastic modulus in the elastic stage, the yield strength in the plastic stage, and the hardening modulus parameters are determined to describe the entire process characteristics of the steel from elastic deformation to plastic deformation under stress. For the soil, the Drucker-Prager constitutive relationship is defined, and the mechanical response of the soil is described by setting the internal friction angle, cohesion, and shear dilatancy angle parameters. The thin shell structure of the steel casing, soil model, contact algorithm and bilinear model are integrated into the 3D explicit dynamic analysis software to establish a 3D explicit dynamic coupling model.

3. The method for dynamic response analysis of large-diameter steel casing of deep-sea temporary platform according to claim 2 is characterized in that: The axial stress distribution characteristics during the penetration of the steel casing are calculated using the comprehensive dynamic load set of the steel casing. The stress distribution characteristics are then analyzed to identify stress concentration areas and buckling risk modes of the casing structure, including: The integrated dynamic load set is applied as boundary conditions to the steel casing structure in the 3D explicit dynamic coupling model. The 3D explicit dynamic coupling model is integrated in the time domain to calculate the axial stress of each node at different positions and times during the steel casing penetration process. According to the axial stress of the steel casing at different positions and times, the density and change trend of the stress distribution are analyzed to determine the stress concentration area and distribution characteristics of the casing structure; According to the characteristics of the stress concentration area, including location, range and gradient, the risk mode of steel casing buckling is determined, including local buckling and global buckling.

4. The method for dynamic response analysis of large-diameter steel casing of a deep-sea temporary platform according to claim 3 is characterized in that: A waterproof full-bridge strain sensor array is deployed in the stress concentration area of ​​the cylinder structure. The waterproof full-bridge strain sensor array is used to collect the stress time history curve of the steel casing during the entire vibration penetration process in real time, and obtain the dynamic stress change data of the steel casing under actual working conditions, including: According to the stress concentration area of ​​the cylinder structure, the waterproof full-bridge strain sensor is determined, and the waterproof full-bridge strain sensor array is evenly arranged in the axial and circumferential directions in the stress concentration area to form a three-dimensional monitoring network; Connect the signal lines of the waterproof full-bridge strain sensor array to the data acquisition instrument, and configure the sampling frequency and storage path of the data acquisition instrument; During the vibration penetration of the steel casing, the waterproof full-bridge strain sensor array senses the strain changes of the steel casing in real time, converts the strain signal into an electrical signal, and transmits it to the data acquisition instrument through the data transmission cable; Reading raw strain data from a data acquisition instrument, and preprocessing the raw strain data to obtain processed strain data; According to the elastic modulus of the steel casing material and Hooke's law, the processed strain data is converted into stress data, and the stress time history curve of the entire penetration process is drawn with time and stress as coordinates to obtain dynamic data, including the stress change law, peak stress time and magnitude.

5. The method for dynamic response analysis of large-diameter steel casing of deep-sea temporary platform according to claim 4 is characterized in that: Based on the dynamic stress change data of the steel casing under actual working conditions, the wall thickness of the steel casing and the material constitutive model parameters are modified, including: Analyze the dynamic data of stress changes of steel casing under actual working conditions and extract stress characteristic parameters, including stress peak value and stress change frequency; A parameter inversion algorithm is used, with stress characteristic parameters as the objective function, steel casing wall thickness and material constitutive model parameters as design variables. Through continuous iteration, the corrected steel casing wall thickness and material constitutive model parameters are obtained.

6. The method for dynamic response analysis of large-diameter steel casing of deep-sea temporary platform according to claim 5 is characterized in that: Using the parameter inversion algorithm, the stress characteristic parameters are used as the objective function, and the steel casing wall thickness and material constitutive model parameters are used as design variables. Through continuous iteration, the revised steel casing wall thickness and material constitutive model parameters are obtained, including: The bacterial foraging algorithm is used as a parameter inversion algorithm. The steel casing wall thickness and material constitutive model parameters are combined into a parameter vector. Each parameter vector represents a bacterial individual. A certain number of bacterial individuals are randomly generated to form the initial bacterial population. The parameters of the bacterial foraging algorithm were set, including the chemotaxis step length, number of chemotaxis times, number of replications, and migration probability. The steel casing parameter vector corresponding to each bacterial individual was substituted into the three-dimensional explicit dynamic coupling model to simulate the stress conditions of the steel casing under actual working conditions and obtain the stress response of the steel casing. The stress characteristic parameter is used as the objective function, and the fitness function value corresponding to each bacterial individual is calculated according to the stress response of the steel casing. For each bacterial individual in the group, randomly select a direction to move and obtain a new parameter vector; Substitute the new parameter vector into the three-dimensional explicit dynamic coupling model to calculate the stress response and re-evaluate the fitness function value of the corresponding bacterial individual; Repeat the chemotaxis movement and evaluation process until the preset number of chemotaxis is reached. The entire population is ranked according to the fitness function value of the bacterial individuals to determine a portion of candidate bacterial individuals. The candidate bacterial individuals are replicated to generate new individuals that are identical to the candidate bacterial individuals. For each bacterial individual in the population, a random number between 0 and 1 is generated and compared with the preset migration probability. If the random number is less than the migration probability, the corresponding bacterial individual migrates and a new parameter vector is generated. If the random number is greater than the migration probability, the bacterial individual remains in its original position. The fitness function value calculation, chemotaxis, replication, and migration operations are repeated until the preset number of iterations is reached. The final parameter vector is determined based on the fitness function value of the individual bacteria in the population, and the final parameter vector is used as the revised steel casing wall thickness and material constitutive model parameters.

7. A computing device, characterized in that include: one or more processors; A storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

Images