A system and method for evaluating the resilience of an offshore island cluster deep soft soil foundation and transportation infrastructure structure system

Abstract

The application discloses a kind of offshore island group deep soft soil foundation and traffic infrastructure structure system flexibility collaborative evaluation system and method, the system includes: sampling module, for sampling offshore island group deep soft soil foundation, the indoor test is carried out to sample and obtains soil physical mechanics parameter;Response characteristic extraction module is used for based on soil physical mechanics parameter and resistance survey data, establishes offshore island group deep soft soil foundation dynamic response analysis model, and the ground dynamic response characteristics under different working conditions are calculated based on offshore island group deep soft soil foundation dynamic response analysis model;Index selection module is used for combining ground dynamic response characteristics and offshore island group deep soft soil foundation characteristics, selects traffic infrastructure structure system flexibility evaluation index;Collaborative evaluation module is used for using flexibility evaluation index point to offshore island group deep soft soil foundation traffic infrastructure flexibility and is evaluated, determines flexibility grade, completes flexibility collaborative evaluation method.

Description

Technical Field

[0001] This invention relates to the fields of civil engineering, geological engineering, and transportation engineering, and specifically to a collaborative evaluation system and method for the resilience of deep soft soil foundations and transportation infrastructure structures in offshore island groups. Background Technology

[0002] With the development and utilization of marine resources in my country, the number of transportation infrastructure projects in offshore island groups is increasing, such as cross-sea bridges and undersea tunnels. Most of these projects are located on deep soft soil foundations with weak bearing capacity, making them susceptible to strong dynamics and high additional stress. The complex geological conditions of offshore island groups mean that existing foundation treatment technologies are insufficient to meet the long-term stability and safety requirements of transportation infrastructure. Current toughness characterization methods are immature; conventional structures and buildings use commonly used design indicators such as strength, stability, or durability, but these differ from toughness design. Furthermore, current safety assessments of foundations and structures are often conducted separately, lacking a collaborative evaluation method for the toughness of deep soft soil foundations and transportation infrastructure structural systems, considering environmental factors, stability factors of deep soft soil foundations, disaster factors, and the multi-level functional serviceability of transportation infrastructure materials, components, and structures. Therefore, proposing a collaborative evaluation method for the toughness of deep soft soil foundations and transportation infrastructure structural systems in offshore island groups is of great significance. Summary of the Invention

[0003] To address the above technical problems, this invention provides a system and method for collaboratively evaluating the resilience of deep soft soil foundations and transportation infrastructure structures in offshore island groups. The method includes:

[0004] A collaborative evaluation system for the resilience of deep soft soil foundations and transportation infrastructure structures in offshore island groups, characterized in that the system comprises:

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

[0006] The response characteristic extraction module is used to establish a dynamic response analysis model for the deep soft soil foundation of offshore islands based on the physical and mechanical parameters of the soil and the resistance survey data, and to calculate the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model for the deep soft soil foundation of offshore islands.

[0007] The index selection module is used to select resilience evaluation indicators for transportation infrastructure structural systems by combining the aforementioned foundation dynamic response characteristics and the characteristics of deep soft soil foundations in offshore island groups.

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

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

[0010] The grade classification measures module is used to generate foundation treatment measures based on the toughness grade.

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

[0012] Optional evaluation indicators for the resilience of transportation infrastructure structural systems include: structural morphology parameters, hydrodynamic parameters, stress parameters at key nodes, patterns in structural safety monitoring data, soil physical properties, soil mechanical properties, soft soil foundation reinforcement methods, and patterns in soft soil foundation safety monitoring data.

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

[0014] Optionally, the process of determining the toughness rating specifically includes:

[0015] AHP is used to perform a 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 to obtain the weighted results;

[0017] The least squares method is used to calculate the comprehensive weight of the multi-indicator comprehensive correlation degree and the weighted result;

[0018] The resilience level is calculated based on the comprehensive weights.

[0019] Optionally, the content of the comprehensive correlation of the multiple indicators specifically includes:

[0020]

[0021] Where, α i For indicator c i The weighting coefficient, c i For the i-th indicator, v i Let n be the feature value corresponding to the evaluation index in the research object, n be the nth index, N be the given research object, and K be the feature value. j This represents the overall correlation of the indicators.

[0022] Optionally, the content of the comprehensive weight includes:

[0023]

[0024] This invention also discloses a method for synergistic evaluation of the resilience of deep soft soil foundations and transportation infrastructure structures in offshore island groups, the method comprising:

[0025] Step S1: Sample the deep soft soil foundation of the offshore islands and conduct indoor tests on the samples to obtain the physical and mechanical parameters of the soil.

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

[0027] Step S3: Combining the aforementioned foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of offshore island groups, select the resilience evaluation index for the transportation infrastructure structural system;

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

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] This invention fully considers the characteristics of deep soft soil foundations in offshore island clusters, making it 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 transportation infrastructure in offshore island clusters.

[0031] The resilience enhancement measures proposed in this invention help improve the stability and safety of transportation infrastructure on deep soft soil foundations in offshore island groups.

[0032] This invention is simple to operate, easy to promote, and has good economic and social benefits. Attached Figure Description

[0033] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a system structure diagram of the resilience co-evaluation system for deep soft soil foundation and transportation infrastructure structure of offshore islands, according to an embodiment of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be 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 deep soft soil foundations and transportation infrastructure structures in offshore island groups, such as... Figure 1 As shown, the system includes:

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

[0040] Sampling was conducted on the deep soft soil foundation of the offshore islands for laboratory tests to obtain soil physical and mechanical parameters, such as shear strength, compression modulus, and permeability coefficient. In this embodiment, the laboratory tests included: moisture content test (soil moisture content); density test (soil density); specific gravity test (soil particle specific gravity); particle size analysis test (soil particle size distribution 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 (soil unconfined compressive strength), etc. Specific procedures were performed in accordance with GB / T 50123-2019 "Standard for Geotechnical Testing Methods".

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

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

[0043] The dynamic response analysis models can be mainly categorized into the following types, which should be selected or combined according to engineering requirements and data conditions:

[0044] (1) Numerical Model

[0045] ① Finite Element Model (FEM): This model uses discretized foundation soil as mesh elements and combines constitutive models (such as the Mohr-Coulomb model and the modified Cambridge model) to simulate the nonlinear deformation and dynamic response of soft soil. It is mainly used for complex load coupling (earthquake + wave + traffic) and heterogeneous strata analysis; it has high accuracy and can simulate multiphysics coupling effects.

[0046] ② Finite Difference Model (FDM): Applicable to large deformation problems (such as liquefaction flow), it solves the dynamic behavior of soil through difference equations. It is mainly used for simulating soil flow caused by earthquake liquefaction and wave scour.

[0047] ③ Discrete Element Model (DEM): Primarily simulates the discrete interactions of particle-sized soils under dynamic loads, and is suitable for studying the microscopic mechanisms 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 assessment of seismic motion parameters (peak acceleration, spectral characteristics).

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

[0051] (3) Physical Model

[0052] ① Centrifuge test model: This model simulates the behavior of prototype soil under high gravity fields using a centrifuge, combined with sensor monitoring of dynamic response. It is primarily used to validate numerical models and study extreme conditions (such as super earthquakes).

[0053] ② Shaking table test: Seismic waves are applied to a scaled-down model to directly observe the interaction between the foundation and the structure.

[0054] (4) Data-driven model

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

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

[0057] ① Typical operating conditions are classified as shown in Table 1:

[0058] Table 1

[0059] Operating conditions Load Combination Engineering scenarios Earthquake conditions Seismic waves (such as El Centro waves, artificial waves) The island group is located in an active seismic zone. Wave cyclic load Wave force (regular wave / irregular wave) Offshore bridge pile foundations and revetment structures Traffic dynamic load Vehicle load spectrum (axle load, frequency) Inter-island highways and railway subgrades Coupled operating conditions Earthquake + Waves, Waves + Transportation Taking into account extreme conditions (such as earthquakes triggering tsunamis) Long-term service conditions Soft soil creep + periodic load Accumulated settlement during operation

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

[0061] Table 2

[0062]

[0063] The index selection module is used to select resilience evaluation indicators for transportation infrastructure structural systems by combining the aforementioned foundation dynamic response characteristics and the characteristics of deep soft soil foundations in offshore island groups.

[0064] The resilience evaluation indicators for transportation infrastructure structural systems include: structural morphological parameters, hydrodynamic parameters, stress parameters at key nodes, structural safety monitoring data patterns, soil physical properties, soil mechanical properties, soft soil foundation reinforcement methods, and soft soil foundation safety monitoring data patterns.

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

[0066] Based on the characteristics of deep soft soil foundations in offshore island groups, this paper selects the main factors affecting the resilience of transportation infrastructure, such as foundation bearing capacity, settlement deformation, and seismic liquefaction, and constructs a resilience evaluation index system.

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

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

[0069] Table 3 shows the resilience factors screened according to the two dimensions of "resistance capacity - recovery capacity":

[0070] Table 3

[0071]

[0072] ② Selection method:

[0073] Key factors are identified based on failure mode. FMEA (Failure Mode and Effects Analysis) is used to list potential infrastructure failure modes caused by soft soil foundations; settlement failure: differential settlement and cracking of roadbeds; bearing capacity failure: lateral instability of pile foundations; liquefaction failure: structural tilting due to sand liquefaction under earthquakes. Sensitivity is quantified by combining foundation parameters: grey relational 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: geological, structural, and construction experts score the importance of factors. Data-driven approach: parameter sensitivity is inverted using monitoring data (e.g., parameter sensitivity analysis reveals that settlement is most sensitive to changes in compression modulus).

[0074] ③ List of typical resilience factors (sorted by priority): 1. Foundation bearing capacity: Determines the static stability of infrastructure (quantified using CPT / SPT data). 2. Differential settlement: Affects pavement smoothness and structural stress concentration. 3. Liquefaction potential index (LPI): Quantifies the risk of earthquake liquefaction (LPI>15 indicates high risk). 4. Consolidation rate: Reflects the recovery capacity of soft soil after drainage reinforcement (calculated using pore pressure monitoring data). 5. Dynamic amplification factor: Assesses the amplification effect of seismic waves in soft soil (spectral analysis results). 6. Environmental erosion rate: The amount of soil loss caused by wave erosion (predicted through flume tests or numerical simulations).

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

[0076] The resilience of transportation infrastructure in the deep soft soil foundation of offshore island groups was evaluated and its resilience level was determined by using methods such as fuzzy comprehensive evaluation and hierarchical analysis.

[0077] Based on the failure characteristics of the wharf slope and structure obtained from numerical simulations, the safety levels are divided into five categories: extremely unsafe, unsafe, basically safe, safe, and extremely safe. According to the principle of extension theory, safety stability is described using matter-element theory, represented by ordered triples.

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

[0079] In the formula: N is the given name of the 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 individual indicator is weighted and averaged to calculate the comprehensive correlation of multiple indicators at each level:

[0081]

[0082] In the formula: α i For indicator C i The weighting coefficients satisfy

[0083] α is determined using the AHP-CRITIC combined weighting method. i The Analytic Hierarchy Process (AHP) compares all indicators pairwise, artificially creating an importance table and calculating the weight of each indicator based on its importance; this method is highly subjective. The CRITIC method, on the other hand, is entirely based on measured data, assigning different weights to indicators according to the degree of danger of the measured data, thus exhibiting high objectivity. The AHP-CRITIC combined weighting method balances the subjective judgment of AHP with the control of the importance of the measured values ​​by CRITIC. It calculates the weight of each indicator using both methods separately, and then uses the least squares method to calculate the final weight combining the two methods.

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

[0085] Tabular format: If the evaluation system has n indicators, then construct an n×n matrix;

[0086] Assignment rules: Use Saaty's 1-9 scale, where a larger number indicates that the former is more important than the latter (e.g., 1 = equally important, 3 = slightly important, 5 = significantly important, 9 = absolutely important).

[0087] Mathematical properties: The diagonal elements of the matrix are all 1 (comparing itself) and satisfy the reciprocal 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)] Then the assessed object N belongs to level j. For ease of description and calculation, the characteristic value j of the level variable is used. * To represent the security level, let:

[0093]

[0094] Based on the specific values ​​of the indicators to be tested, the evaluation level of the description layer is calculated. Then, the comprehensive correlation degree of the multiple indicators in the evaluation indicator layer is used as the single indicator correlation degree of the description layer to calculate the security level of the comprehensive evaluation layer.

[0095] The grade classification measures module is used to generate foundation treatment measures based on the toughness grade.

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

[0097] ① Safety level classification principle: 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] Threshold criteria: Standards and specifications: such as the "Code for Design of Port Engineering Foundations" (JTS147-2017) and the "Standard for Technical Condition Assessment of Highway Bridges" (JTG / T H21-2011). Numerical simulation and testing: Determining the limit state value through finite element analysis or centrifugal model testing. Historical data: Statistical analysis of long-term monitoring data from similar projects. Expert experience: Adjusting the threshold based on failure cases in engineering practice.

[0099] ② Examples of specific parameter security level classifications and thresholds

[0100] 1. Structural safety of transportation infrastructure

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

[0102] Table 5

[0103]

[0104] 2) The hydrodynamic parameters are shown in Table 6:

[0105] Table 6

[0106]

[0107] 3) The stress parameters 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 the soil are shown in Table 8:

[0112] Table 8

[0113]

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

[0115] Table 9

[0116]

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

[0118] Table 10

[0119]

[0120] ③Comprehensive security level determination

[0121] 1. Single-index weighted method: Calculate the comprehensive score based on the weight of each index (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 is directly judged to be in a dangerous state.

[0125] ④ Threshold dynamic adjustment suggestions

[0126] 1. Environmental sensitivity adjustment, as detailed below:

[0127] In typhoon-prone areas, the hydrodynamic index thresholds need to be reduced by 10% to 20% (e.g., the design wave height threshold is adjusted from 150% to 130%).

[0128] Seismic zones: The threshold values ​​for stress indicators at key nodes will be strictly controlled (e.g., the maximum principal stress / material strength threshold will be adjusted from 0.9 to 0.8).

[0129] 2. Time effect correction:

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

[0131] The impact of soft soil creep: The consolidation threshold needs to be dynamically adjusted in conjunction with long-term monitoring.

[0132] Example 2

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

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

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

[0136] The calculation methods include:

[0137] Based on a nonlinear model to describe the dynamic properties of soft soil, the dynamic equilibrium equation is:

[0138]

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

[0140] Dynamic response calculation process: 1. Static initialization. Calculate the initial ground stress equilibrium to ensure the model's stability under its own weight. 2. Dynamic Time History Analysis. Dynamic Load Input: Seismic wave (time history acceleration) or wave force (drag force + inertial force). Time Integration: Solve the dynamic equations stepwise using the Newmark-β method (unconditional stability). Nonlinear Iteration: Correct soil stiffness and damping within each time step (considering nonlinear deformation). 3. Key Output Results: Displacement Response: Maximum horizontal displacement, settlement. Acceleration Response: Peak ground acceleration (PGA) and spectral analysis. Pore Pressure Development: Excess pore water pressure ratio (ru), assessing liquefaction risk. 4. Stress-Strain Curve: Hysteresis characteristics and energy dissipation. Typical Working Condition Design; Seismic Working Condition: Input seismic wave, analyze soft soil deformation and liquefaction. Wave Working Condition: Apply periodic wave force, calculate cumulative settlement. Composite Working Condition: Synergistic effect under seismic + wave coupling.

[0141] Step S3: Based on the aforementioned foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of offshore island groups, select the resilience evaluation index for the transportation infrastructure structural system.

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

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

Claims

1. A collaborative evaluation system for the resilience of deep soft soil foundations and transportation infrastructure structures in offshore island groups, characterized in that the system... include: The sampling module is used to sample the deep soft soil foundation of offshore islands and conduct indoor tests on the samples to obtain the physical and mechanical parameters of the soil. The response characteristic extraction module is used to establish a dynamic response analysis model for the deep soft soil foundation of offshore islands based on the physical and mechanical parameters of the soil and geological survey data, and to calculate the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model for the deep soft soil foundation of offshore islands. The index selection module is used to select resilience evaluation indicators for transportation infrastructure structural systems by combining the aforementioned foundation dynamic response characteristics and the characteristics of deep soft soil foundations in offshore island groups. The collaborative evaluation module is used to evaluate the resilience of transportation infrastructure on deep soft soil foundations of offshore islands using the resilience evaluation index points, determine the resilience level, and complete the collaborative evaluation method for the resilience of the structural system of deep soft soil foundations and transportation infrastructure on offshore islands. The resilience evaluation indicators for transportation infrastructure structural systems include: structural morphological parameters, hydrodynamic parameters, stress parameters at key nodes, patterns in structural safety monitoring data, soil physical properties, soil mechanical properties, soft soil foundation reinforcement methods, and patterns in soft soil foundation safety monitoring data. The structural morphological parameters include cumulative settlement, horizontal displacement, structural tilt, and crack width and propagation rate; the hydrodynamic parameters include design wave height and period, water flow velocity and direction, and tidal frequency and amplitude; the key node stress parameters include maximum principal stress and shear stress, material strength degradation rate, cumulative fatigue damage, and corrosion rate; the structural safety monitoring data patterns include dynamic response spectrum characteristics, data trend analysis, and abnormal fluctuation threshold alarms; the soil physical properties include natural moisture content, void ratio, liquid limit and plastic limit, and compression index; the soil mechanical properties include undrained shear strength, consolidation coefficient, permeability coefficient, and bearing capacity; the soft soil foundation reinforcement methods include drainage well spacing and depth, preloading and time control, deep mixing pile strength, and pile foundation treatment effect verification; the soft soil foundation safety monitoring data patterns include foundation settlement rate, pore water pressure dissipation law, consolidation degree development curve, and differential settlement between reinforced and unreinforced areas.

2. The resilience co-evaluation system for deep soft soil foundation and transportation infrastructure structure of offshore island groups according to claim 1, characterized in that, The collaborative evaluation system also includes: The grade classification measures module is used to generate foundation treatment measures based on the toughness grade.

3. The resilience co-evaluation system for deep soft soil foundation and transportation infrastructure structure of offshore island groups according to claim 1, characterized in that, The physical and mechanical parameters of soil include shear strength, compression modulus, and permeability coefficient.

4. The resilience co-evaluation system for deep soft soil foundation and transportation infrastructure structure of offshore island groups according to claim 1, characterized in that, The process of determining the toughness rating specifically includes: AHP is used to perform a 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 to obtain the weighted results; The least squares method is used to calculate the comprehensive weight of the multi-indicator comprehensive correlation degree and the weighted result; The resilience level is calculated based on the comprehensive weights.

5. The resilience co-evaluation system for deep soft soil foundation and transportation infrastructure structure of offshore island groups according to claim 4, characterized in that, The content of the comprehensive correlation of the multiple indicators specifically includes: in, As an indicator The weighting coefficients, For the i-th indicator, These are the characteristic values ​​corresponding to the evaluation indicators in the research subjects. n For the nth indicator, N For a given research object, This represents the overall correlation of the indicators.

6. The resilience co-evaluation system for deep soft soil foundation and transportation infrastructure structure of offshore island groups according to claim 5, characterized in that, The content of the comprehensive weight includes: 。 7. A method for synergistic evaluation of the resilience of a structural system of deep soft soil foundation and transportation infrastructure in offshore island groups, wherein the method applies the system described in any one of claims 1-6, characterized in that, The methods include: Step S1: Sample the deep soft soil foundation of the offshore islands and conduct indoor tests on the samples to obtain the physical and mechanical parameters of the soil. Step S2: Based on the physical and mechanical parameters of the soil and the resistance survey data, establish a dynamic response analysis model for the deep soft soil foundation of the offshore islands, and calculate the dynamic response characteristics of the foundation under different working conditions based on the dynamic response analysis model for the deep soft soil foundation of the offshore islands. Step S3: Combining the aforementioned foundation dynamic response characteristics and the characteristics of the deep soft soil foundation of offshore island groups, select the resilience evaluation index for the transportation infrastructure structural system; Step S4: Use the aforementioned transportation infrastructure structural system resilience evaluation index to evaluate the resilience of transportation infrastructure in the deep soft soil foundation of offshore islands, determine the resilience level, and complete the collaborative evaluation method for the resilience of the deep soft soil foundation and transportation infrastructure structural system of offshore islands.

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