Cooperative evaluation system and method for toughness of deep and thick soft soil foundation and traffic infrastructure structural system of offshore island group

Abstract

The invention discloses an offshore island group deep soft soil foundation and traffic infrastructure structural system toughness collaborative evaluation system and method, and the system comprises a sampling module which is used for sampling an offshore island group deep soft soil foundation, and carrying out the indoor test of a sample to obtain the physical and mechanical parameters of a soil body; the response characteristic extraction module is used for establishing a dynamic response analysis model of the deep soft soil foundation of the offshore island group based on the physical and mechanical parameters of the soil body and the resistance investigation data, and calculating the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model of the deep soft soil foundation of the offshore island group; the index selection module is used for selecting the toughness evaluation index of the traffic infrastructure structure system by combining the dynamic response characteristics of the foundation and the characteristics of the deep and thick soft soil foundation of the offshore island group; and the collaborative evaluation module is used for evaluating the toughness of the traffic infrastructure of the deep and thick soft soil foundation of the offshore island group by using the toughness evaluation index points, determining the toughness grade and completing the toughness collaborative evaluation method.

Description

Technical Field

[0001] The present invention relates to the technical fields of civil engineering, geological engineering, and transportation engineering, and in particular to a system and method for collaboratively evaluating the toughness of deep soft soil foundations of offshore islands and transportation infrastructure structural systems. Background Art

[0002] With the development and utilization of my country's marine resources, the number of transportation infrastructure construction projects in offshore island regions, such as cross-sea bridges and undersea tunnels, is increasing. Most of these projects are located on deep, soft soil foundations with weak bearing capacity and are susceptible to strong dynamic forces and high additional stresses. Due to the complex geological conditions in offshore island regions, existing foundation treatment technologies are unable to meet the long-term stability and safety requirements of transportation infrastructure. Existing toughness characterization methods are still immature. Conventional structures and buildings use common design indicators such as strength, stability, or durability, but these indicators fall short of resilient design. Furthermore, current safety assessments of foundations and structures are often conducted separately, lacking a collaborative assessment method for the resilience of deep soft soil foundations and transportation infrastructure structures, including environmental factors, factors affecting the stability of deep soft soil foundations, disaster factors, and the multi-level functional serviceability of transportation infrastructure materials, components, and structures. Therefore, it is of great significance to propose a collaborative assessment method for the resilience of deep soft soil foundations and transportation infrastructure structures in offshore island regions. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention provides a system and method for collaboratively evaluating the resilience of deep soft soil foundations of offshore islands and transportation infrastructure structures. The method comprises:

[0004] A collaborative evaluation system for the resilience of offshore island deep soft soil foundation and transportation infrastructure structure system, characterized in that the system includes:

[0005] The sampling module is used to sample deep soft soil foundations of offshore islands and conduct indoor tests on the samples to obtain the physical and mechanical parameters of the soil;

[0006] a response characteristic extraction module for establishing a dynamic response analysis model for deep soft soil foundation of offshore islands based on the soil physical and mechanical parameters and resistance survey data, and calculating the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model for deep soft soil foundation of offshore islands;

[0007] An indicator selection module is used to select the resilience evaluation index of the transportation infrastructure structure system based on the foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of the offshore islands;

[0008] The collaborative evaluation module is used to evaluate the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structure system using the resilience evaluation index points, determine the resilience level, and complete the collaborative evaluation method for the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structure system.

[0009] Optionally, the collaborative evaluation system further includes:

[0010] The grading measures module is used to generate foundation treatment measures according to the toughness grade.

[0011] Optionally, the soil physical and mechanical parameters include shear strength, compression modulus and permeability coefficient.

[0012] Optionally, the resilience evaluation indicators of the transportation infrastructure structural system include: structural morphological parameter indicators, hydrodynamic indicators, key node force indicators, structural safety monitoring data patterns, soil physical property indicators, soil mechanical properties, soft soil foundation reinforcement methods and soft foundation safety monitoring data patterns.

[0013] Optionally, the structural morphological parameter indicators include cumulative settlement, horizontal displacement, structural inclination, and crack width and expansion rate; the hydrodynamic indicators include design wave height and wave period, water flow velocity and direction, and tidal action frequency and amplitude; the key node force indicators include maximum principal stress and shear stress, material strength degradation rate, fatigue cumulative damage and corrosion rate; the structural safety monitoring data rules include dynamic response spectrum characteristics, data trend analysis and abnormal fluctuation threshold alarm; the soil physical property indicators include natural water content, porosity, liquid limit and plastic limit and compression index; the soil mechanical properties include undrained shear strength, consolidation coefficient, permeability and bearing capacity; the soft soil foundation reinforcement method includes drainage sand well spacing and depth, preload and time control, deep mixing pile strength and pile foundation treatment effect verification; the soft foundation safety monitoring data rules include foundation settlement rate, pore water pressure dissipation law, consolidation degree development curve and differential settlement between reinforced and non-reinforced areas.

[0014] Optionally, the process of determining the toughness level may include:

[0015] Use AHP to perform weighted average of the correlation of individual indicators to obtain the comprehensive correlation of multiple indicators at each level;

[0016] The CRITIC method is used to weight the indicators and obtain the weighted results;

[0017] Calculate the comprehensive weight of the comprehensive correlation degree of the multiple indicators and the weighted result using the least square method;

[0018] The toughness grade is calculated based on the comprehensive weights.

[0019] Optionally, the content of the multi-indicator comprehensive correlation degree specifically includes:

[0020]

[0021] Among them, α i is the indicator c i The weight coefficient, c i is the i-th indicator, v i is the characteristic value corresponding to the evaluation index in the research object, n is the nth index, N is the given research object, K j is the comprehensive correlation of indicators.

[0022] Optionally, the comprehensive weight includes:

[0023]

[0024] The present invention also discloses a method for collaboratively evaluating the resilience of deep soft soil foundations of offshore islands and transportation infrastructure structures, the method comprising:

[0025] Step S1: sampling deep soft soil foundations of offshore islands and conducting indoor tests on the samples to obtain soil physical and mechanical parameters;

[0026] Step S2: establishing a dynamic response analysis model for deep soft soil foundation of offshore islands based on the soil physical and mechanical parameters and resistance survey data, and calculating the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model for deep soft soil foundation of offshore islands;

[0027] Step S3: selecting a toughness evaluation index for the transportation infrastructure structure system based on the foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of the offshore islands;

[0028] Step S4: Use the transportation infrastructure structural system resilience evaluation index to evaluate the resilience of the transportation infrastructure on the deep soft soil foundation of the offshore island group, determine the resilience level, and complete the collaborative evaluation method for the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structural system.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] This invention fully considers the characteristics of deep soft soil foundations in offshore islands and is highly targeted and practical. Through dynamic response analysis and toughness evaluation, it provides a theoretical basis for the design, construction, and operation and maintenance of offshore island transportation infrastructure.

[0031] The resilience enhancement measures proposed in the present invention help to improve the stability and safety of transportation infrastructure with deep soft soil foundations on offshore islands.

[0032] The present invention is simple to operate, easy to promote, and has good economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 This is a system structure diagram of a collaborative evaluation system for the resilience of offshore island deep soft soil foundation and transportation infrastructure structural system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0036] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0037] Example 1

[0038] A collaborative evaluation system for the resilience of offshore island deep soft soil foundation and transportation infrastructure structure system, such as Figure 1 As shown, the system includes:

[0039] The sampling module is used to sample deep soft soil foundations of offshore islands and conduct indoor tests on the samples to obtain the physical and mechanical parameters of the soil.

[0040] Sampling deep soft soil foundations on offshore islands was conducted for indoor testing to obtain soil physical and mechanical parameters such as shear strength, compression modulus, and permeability coefficient. In this embodiment, the indoor testing included: moisture content test (soil moisture content); density test (soil density); specific gravity test (soil particle specific gravity); particle analysis test (soil particle grading curve); relative density test (soil relative density); permeability test (soil permeability coefficient); consolidation test (soil cohesion and internal friction angle); triaxial compression test (soil compression modulus); and unconfined compressive strength test (unconfined compressive strength). Specific operations were performed in accordance with GB / T 50123-2019, "Standard for Geotechnical Test Methods."

[0041] The response characteristic extraction module is used to establish a dynamic response analysis model of deep soft soil foundation of offshore islands based on the physical and mechanical parameters of the soil and the resistance survey data, and calculate the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model of deep soft soil foundation of offshore islands.

[0042] Based on on-site monitoring data and geological survey information, a dynamic response analysis model for deep soft soil foundations in offshore island groups was established to calculate the dynamic response characteristics of the foundation under different working conditions.

[0043] The dynamic response analysis model can be expressed in the following ways, which need to be selected or combined based on project requirements and data conditions:

[0044] (1) Numerical model

[0045] Finite Element Model (FEM): This model discretizes the foundation soil into grid elements and combines constitutive models (such as the Mohr-Coulomb and modified Cambridge models) to simulate the nonlinear deformation and dynamic response of soft soils. This model is primarily used for complex load coupling (earthquake, wave, and traffic) and heterogeneous strata analysis. It offers high accuracy and can simulate the effects of multiple physical fields.

[0046] Finite Difference Model (FDM): Applicable to large deformation problems (such as liquefaction flow), it uses differential equations to solve the dynamic behavior of soil. It is mainly used to simulate soil flow and wave scour caused by earthquake liquefaction.

[0047] ③ Discrete element model (DEM): It mainly simulates the discrete interaction of particle-level soil under dynamic loads and is suitable for the study of the microscopic mechanism of sand liquefaction.

[0048] (2) Analytical model

[0049] ① Wave theory model: Based on the elastic wave equation, it calculates the propagation characteristics of seismic waves in soil (such as reflection, refraction, and amplification effects). It is mainly used for preliminary evaluation of ground motion parameters (peak acceleration, spectral characteristics).

[0050] ② Simplified empirical formulas: For example, the Seed simplified method for estimating liquefaction potential or the bearing capacity formula based on the Standard Penetration Test (SPT). These formulas offer the advantage of rapid estimation and are suitable for the scheme selection stage.

[0051] (3) Physical model

[0052] ① Centrifuge test model: This model simulates the behavior of a prototype soil under high gravity using a centrifuge and uses sensors to monitor the dynamic response. This is primarily used to validate numerical models and study extreme conditions (such as super-strong earthquakes).

[0053] ② Shaking table test: Apply seismic waves to a scaled model to directly observe the foundation-structure interaction.

[0054] (4) Data-driven model

[0055] Machine learning models: Use historical monitoring data to train neural networks (such as LSTM and random forests) to predict dynamic responses. These models are suitable for mining complex nonlinear relationships but rely on large amounts of data.

[0056] The dynamic response characteristics of the foundation include:

[0057] ① Typical working conditions are shown in Table 1:

[0058] Table 1

[0059] Working condition type Load combination Engineering scenarios Earthquake conditions Seismic waves (such as El Centro waves, artificial waves) The island group is located in an earthquake-prone zone Wave cyclic loading Wave force (regular waves / irregular waves) Offshore bridge pile foundations and bank protection structures Traffic dynamic load Vehicle load spectrum (axle weight, frequency) Inter-island highway and railway subgrade Coupling conditions Earthquake + waves, waves + traffic Combined extreme conditions (such as earthquake-triggered tsunamis) Long-term service conditions Soft soil creep + cyclic loading Accumulated settlement during operation period

[0060] ②Key analysis indicators are shown in Table 2:

[0061] Table 2

[0062]

[0063] An indicator selection module is used to select the resilience evaluation index of the transportation infrastructure structure system based on the foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of the offshore islands;

[0064] The resilience evaluation indicators of the transportation infrastructure structural system include: structural morphological parameter indicators, hydrodynamic indicators, key node force indicators, structural safety monitoring data patterns, soil physical property indicators, soil mechanical properties, soft soil foundation reinforcement methods and soft foundation safety monitoring data patterns.

[0065] The structural morphological parameter indicators include cumulative settlement, horizontal displacement, structural inclination, crack width and expansion rate; the hydrodynamic indicators include design wave height and wave period, water flow velocity and direction, tidal action frequency and amplitude; the key node force indicators include maximum principal stress and shear stress, material strength degradation rate, fatigue cumulative damage and corrosion rate; the structural safety monitoring data patterns include dynamic response spectrum characteristics, data trend analysis and abnormal fluctuation threshold alarm; the soil physical property indicators include natural water content, porosity, liquid limit and plastic limit and compression index; the soil mechanical properties include undrained shear strength, consolidation coefficient, permeability and bearing capacity; the soft soil foundation reinforcement methods include drainage sand well spacing and depth, preload and time control, deep mixing pile strength and pile foundation treatment effect verification; the soft foundation safety monitoring data patterns include foundation settlement rate, pore water pressure dissipation law, consolidation degree development curve and differential settlement between reinforced and non-reinforced areas.

[0066] Considering the characteristics of deep soft soil foundation of offshore islands, the main factors affecting the resilience of transportation infrastructure, such as foundation bearing capacity, settlement deformation, earthquake liquefaction, etc., are selected to construct a resilience evaluation index system.

[0067] The selection of the main factors is mainly determined by the following contents:

[0068] ① The mapping relationship between foundation characteristics and toughness factors: The core characteristics of deep, soft soil foundations in offshore islands include: high compressibility, which is prone to long-term settlement and uneven deformation; low permeability, which results in slow drainage and consolidation, and difficulty in dissipating excess pore water pressure; low shear strength, which is prone to shear failure or lateral flow; and high dynamic sensitivity, which is prone to liquefaction or strength degradation under earthquake or wave loads.

[0069] The resilience factors screened by the dual dimensions of "resistance-recovery" are shown in Table 3:

[0070] Table 3

[0071]

[0072] ②Selection method:

[0073] Identify key factors based on failure modes. Through FMEA (Failure Mode and Effects Analysis): list the infrastructure failure modes that may be caused by soft soil foundations; Settlement failure: cracking of roadbed due to differential settlement. Bearing capacity failure: lateral instability of pile foundations. Liquefaction failure: liquefaction of sand layers under earthquakes causes structural tilt. Combined with foundation parameter quantification sensitivity: Grey correlation analysis or principal component analysis (PCA) is used to calculate the correlation between each factor and historical disaster data. Expert-data joint screening: Delphi method: organize geological, structural, and construction experts to score the importance of factors. Data-driven: use monitoring data to invert parameter sensitivity (for example, through parameter sensitivity analysis, it is found that settlement is most sensitive to changes in compression modulus).

[0074] ③ List of typical resilience factors (in order of priority): 1. Foundation bearing capacity: determines the static stability of infrastructure (quantified by CPT / SPT data). 2. Differential settlement: affects road surface smoothness and structural stress concentration. 3. Liquefaction potential index (LPI): quantifies the risk of earthquake liquefaction (LPI>15 is high risk). 4. Consolidation rate: reflects the recovery capacity of soft soil after drainage and reinforcement (calculated by pore pressure monitoring data). 5. Dynamic amplification factor: evaluates the amplification effect of seismic waves in soft soil (spectral analysis results). 6. Environmental erosion rate: the amount of soil loss caused by wave scouring (predicted by flume tests or numerical simulations).

[0075] The collaborative evaluation module is used to evaluate the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structure system using the resilience evaluation index points, determine the resilience level, and complete the collaborative evaluation method for the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structure system.

[0076] The fuzzy comprehensive evaluation method, hierarchical analysis method and other methods were used to evaluate the resilience of transportation infrastructure with deep soft soil foundation in offshore islands and determine its resilience level.

[0077] Combined with the damage characteristics of the wharf slope and structure obtained by numerical simulation, the safety levels of each layer are divided into 5 levels: extremely unsafe, unsafe, basically safe, safe, and extremely safe. According to the principle of extenics, the safety and stability are described by matter-element, which is expressed as an ordered triple:

[0078] R=(N,C,V)

[0079] In the formula: N is the name of a given thing, C is the characteristic of the corresponding thing, and V is the specific value of thing N with respect to characteristic C.

[0080] Based on the importance of each indicator, the correlation of each single indicator is weighted averaged to calculate the comprehensive correlation of multiple indicators at each level:

[0081]

[0082] Where: α i C i The weight coefficient satisfies

[0083] The AHP-CRITIC combined weighting method was used to determine α i The Analytic Hierarchy Process (AHP) compares all indicators pairwise, manually develops an importance table, and calculates the weight of each indicator based on the degree of importance, which is highly subjective. The CRITIC rule is completely based on measured data, assigning different weights to indicators according to the degree of danger of the measured data, and is highly objective. The AHP-CRITIC combined weighting method takes into account the subjective judgment of the analytic hierarchy process and the control of the importance of the measured values by CRITIC. The weight of each indicator is calculated using two methods respectively, and the least squares method is further used to calculate the final weight combining the two methods.

[0084] The importance table is a table constructed based on the importance relationship between two comparison indicators. Specifically:

[0085] Tabular form: If the evaluation system has n indicators, then an n×n matrix is constructed;

[0086] Assignment rules: Use Saaty's 1-9 scale method, where the larger the value, the more important the former is than the latter (for example: 1 = equally important, 3 = slightly important, 5 = obviously important, 9 = absolutely important);

[0087] Mathematical properties: The matrix diagonal elements are all 1 (self-comparison) and satisfy the inverse relationship (a_ij = 1 / a_ji);

[0088] Example judgment matrix:

[0089] The indicators are settlement, bearing capacity and repair time, as shown in Table 4:

[0090] Table 4

[0091]

[0092] If K j0 (N) = max[K j (N)], the assessed object N belongs to level j. For the convenience of description and calculation, the level variable characteristic value j is used. * To express the security level, let:

[0093]

[0094] According to the specific values of the indicators to be measured, the evaluation level of the description layer is calculated. Then, the comprehensive correlation degree of multiple indicators of the evaluation indicator layer is used as the single indicator correlation degree of the description layer to calculate the safety level of the comprehensive evaluation layer.

[0095] The grading measures module is used to generate foundation treatment measures according to the toughness grade.

[0096] Based on the evaluation results, targeted foundation treatment measures are proposed, such as reinforcement, drainage, and replacement, to improve the resilience of transportation infrastructure with deep soft soil foundations on offshore islands.

[0097] ① Principles of safety level classification: Level classification: usually divided into five levels: safe (Level I), relatively safe (Level II), critical (Level III), relatively dangerous (Level IV), and dangerous (Level V).

[0098] Thresholds based on: Standards and regulations, such as the "Specifications for Port Engineering Foundations" (JTS147-2017) and the "Technical Condition Assessment Standard for Highway Bridges" (JTG / T H21-2011). Numerical simulation and testing: Determine limit state values through finite element analysis or centrifuge model testing. Historical data: Statistical analysis of long-term monitoring data from similar projects. Expert experience: Revise thresholds based on failure cases from engineering practice.

[0099] ②Specific parameter security level classification and threshold examples

[0100] 1. Structural safety of transportation infrastructure

[0101] 1) Structural morphological parameters are shown in Table 5:

[0102] Table 5

[0103]

[0104] 2) Hydrodynamic indicators are shown in Table 6:

[0105] Table 6

[0106]

[0107] 3) The stress indexes of key nodes are shown in Table 7:

[0108] Table 7

[0109]

[0110] 2. Safety of deep soft soil foundation

[0111] 1) The physical properties of soil are shown in Table 8:

[0112] Table 8

[0113]

[0114] 2) The mechanical properties of soil are shown in Table 9:

[0115] Table 9

[0116]

[0117] 3) The monitoring data patterns are shown in Table 10:

[0118] Table 10

[0119]

[0120] ③ Comprehensive safety level assessment

[0121] 1. Single indicator weighted method: Calculate the comprehensive score based on the weight of each indicator (e.g., structural safety weight 0.6, foundation safety weight 0.4):

[0122] Level I: ≥85 points, Level II: 70-84 points, Level III: 55-69 points, Level IV: 40-54 points; Level V: <40 points.

[0123] 2. Veto method:

[0124] If any key indicator (such as maximum principal stress / material strength ≥1.0, foundation settlement rate >20mm / month) reaches Level V, the system will be directly judged to be in a dangerous state.

[0125] ④Threshold dynamic adjustment suggestions

[0126] 1. Environmental sensitivity adjustment, as follows:

[0127] Typhoon-prone areas: The hydrodynamic index threshold needs to be reduced by 10% to 20% (for example, the design wave height threshold is adjusted from 150% to 130%).

[0128] Earthquake zones: The stress index thresholds of key nodes are strictly controlled (for example, the maximum principal stress / material strength threshold is adjusted from 0.9 to 0.8).

[0129] 2. Time effect correction:

[0130] Long-term service structure: The corrosion rate threshold increases with age (for example, the corrosion rate threshold is reduced by 20% after 10 years).

[0131] Impact of soft soil creep: The consolidation threshold needs to be dynamically revised in combination with long-term monitoring.

[0132] Example 2

[0133] A collaborative evaluation method for the resilience of deep soft soil foundations and transportation infrastructure structures in offshore islands, comprising:

[0134] Step S1: sampling the deep soft soil foundation of the offshore islands, and conducting indoor tests on the samples to obtain the physical and mechanical parameters of the soil.

[0135] Step S2: Based on the soil physical and mechanical parameters and the resistance survey data, a dynamic response analysis model of deep soft soil foundation of offshore islands is established, and the dynamic response characteristics of the foundation under different working conditions are calculated based on the dynamic response analysis model of deep soft soil foundation of offshore islands.

[0136] Calculation methods include:

[0137] Based on the nonlinear model to describe the dynamic characteristics of soft soil, the dynamic balance equation is:

[0138]

[0139] The model input parameters are soil density, soil shear wave velocity, dynamic shear modulus, damping ratio, earthquake acceleration time history and wave force. The boundary conditions are set as bottom fixed or input earthquake wave, viscous boundary on the side, free top or world wave load.

[0140] Dynamic response calculation process: 1. Static initialization. Calculate the initial ground stress balance to ensure the stability of the model under its own weight 2. Dynamic time-history analysis. Dynamic load input: seismic waves (time-history acceleration) or wave forces (drag force + inertia force). Time integration: The dynamic equations are solved step by step using the Newmark-β method (unconditionally stable). Nonlinear iteration: The soil stiffness and damping are corrected in each time step (considering nonlinear deformation). 3. Key output results: Displacement response: maximum horizontal displacement, settlement. Acceleration response: Peak acceleration (PGA) and spectrum analysis. Pore pressure development: Excess pore water pressure ratio (ru, to assess liquefaction risk. 4. Stress-strain curve: hysteresis characteristics and energy dissipation. Typical working condition design; seismic working condition: input seismic waves, analyze soft soil deformation and liquefaction. Wave working condition: apply periodic wave forces, calculate cumulative settlement. Composite working condition: synergistic effect under the coupling of earthquake and waves.

[0141] Step S3: selecting a resilience evaluation index for the transportation infrastructure structural system based on the foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of the offshore islands.

[0142] Step S4: Use the transportation infrastructure structural system resilience evaluation index to evaluate the resilience of the transportation infrastructure on the deep soft soil foundation of the offshore island group, determine the resilience level, and complete the collaborative evaluation method for the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structural system.

[0143] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A collaborative evaluation system for the resilience of offshore islands' deep soft soil foundations and transportation infrastructure structures, characterized in that the system include: The sampling module is used to sample deep soft soil foundations of offshore islands and conduct indoor tests on the samples to obtain the physical and mechanical parameters of the soil; a response characteristic extraction module for establishing a dynamic response analysis model for deep soft soil foundation of offshore islands based on the soil physical and mechanical parameters and resistance survey data, and calculating the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model for deep soft soil foundation of offshore islands; An indicator selection module is used to select the resilience evaluation index of the transportation infrastructure structure system based on the foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of the offshore islands; The collaborative evaluation module is used to evaluate the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structure system using the resilience evaluation index points, determine the resilience level, and complete the collaborative evaluation method for the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structure system.

2. The offshore island deep soft soil foundation and transportation infrastructure structural system resilience collaborative evaluation system according to claim 1 is characterized by: The collaborative evaluation system further includes: The grading measures module is used to generate foundation treatment measures according to the toughness grade.

3. The offshore island deep soft soil foundation and transportation infrastructure structural system resilience collaborative evaluation system according to claim 1 is characterized by: The physical and mechanical parameters of soil include shear strength, compression modulus and permeability coefficient.

4. The offshore island deep soft soil foundation and transportation infrastructure structural system resilience collaborative evaluation system according to claim 3 is characterized by: The resilience evaluation indicators of the transportation infrastructure structural system include: structural morphological parameter indicators, hydrodynamic indicators, key node force indicators, structural safety monitoring data patterns, soil physical property indicators, soil mechanical properties, soft soil foundation reinforcement methods and soft foundation safety monitoring data patterns.

5. The offshore island deep soft soil foundation and transportation infrastructure structural system resilience collaborative evaluation system according to claim 4 is characterized by: The structural morphological parameter indicators include cumulative settlement, horizontal displacement, structural inclination, crack width and expansion rate; the hydrodynamic indicators include design wave height and wave period, water flow velocity and direction, tidal action frequency and amplitude; the key node force indicators include maximum principal stress and shear stress, material strength degradation rate, fatigue cumulative damage and corrosion rate; the structural safety monitoring data patterns include dynamic response spectrum characteristics, data trend analysis and abnormal fluctuation threshold alarm; the soil physical property indicators include natural water content, porosity, liquid limit and plastic limit and compression index; the soil mechanical properties include undrained shear strength, consolidation coefficient, permeability and bearing capacity; the soft soil foundation reinforcement method includes drainage sand well spacing and depth, preload and time control, deep mixing pile strength and pile foundation treatment effect verification; the soft foundation safety monitoring data patterns include foundation settlement rate, pore water pressure dissipation law, consolidation degree development curve and differential settlement between reinforced and non-reinforced areas.

6. The offshore island deep soft soil foundation and transportation infrastructure structural system resilience collaborative evaluation system according to claim 1 is characterized by: The process of determining the toughness level includes: Use AHP to perform weighted average of the correlation of individual indicators to obtain the comprehensive correlation of multiple indicators at each level; The CRITIC method is used to weight the indicators and obtain the weighted results; Calculate the comprehensive weight of the comprehensive correlation degree of the multiple indicators and the weighted result using the least square method; The toughness grade is calculated based on the comprehensive weights.

7. The offshore island deep soft soil foundation and transportation infrastructure structural system resilience collaborative evaluation system according to claim 6 is characterized by: The content of the multi-indicator comprehensive correlation degree specifically includes: Among them, α i is the indicator c i The weight coefficient, c i is the i-th indicator, v i is the characteristic value corresponding to the evaluation index in the research object, n is the nth index, N is the given research object, K j is the comprehensive correlation of indicators.

8. The offshore island deep soft soil foundation and transportation infrastructure structural system resilience collaborative evaluation system according to claim 7 is characterized by: The comprehensive weight includes:

9. A method for collaboratively evaluating the resilience of deep soft soil foundations and transportation infrastructure structures of offshore islands, the method using the system according to any one of claims 1 to 8, characterized in that: Methods include: Step S1: sampling deep soft soil foundations of offshore islands and conducting indoor tests on the samples to obtain soil physical and mechanical parameters; Step S2: establishing a dynamic response analysis model for deep soft soil foundation of offshore islands based on the soil physical and mechanical parameters and resistance survey data, and calculating the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model for deep soft soil foundation of offshore islands; Step S3: selecting a toughness evaluation index for the transportation infrastructure structure system based on the foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of the offshore islands; Step S4: Use the transportation infrastructure structural system resilience evaluation index to evaluate the resilience of the transportation infrastructure on the deep soft soil foundation of the offshore island group, determine the resilience level, and complete the collaborative evaluation method for the resilience of the deep soft soil foundation of the offshore island group and the transportation infrastructure structural system.

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