Prediction method for long-term settlement of rigid and soft foundation of immersed tube tunnel

Abstract

The invention relates to the technical field of immersed tube tunnel foundation bed long-term deformation prediction, and discloses an immersed tube tunnel rigid and flexible foundation long-term settlement prediction method, which comprises the following steps: obtaining foundation soil long-term compression deformation data through an indoor long-age one-dimensional compression test; fitting according to data to obtain a long-term compression modulus time-varying reference function; selecting a plurality of characteristic time nodes, determining the corresponding settlement influence depth according to the time-varying reference function for each node, and taking the maximum value as the design influence depth; and constructing a final analysis model based on the design influence depth, and performing long-term analysis in the model by adopting the time-varying reference function to obtain a long-term settlement result of the immersed tunnel. The system comprises a data acquisition module, a function fitting module, a depth determination module and a settlement prediction module. According to the method, the time-varying property of the material performance and the spatial range of stress influence are coupled, it is ensured that the calculation model can envelope the most unfavorable working condition, and the accuracy and reliability of long-term settlement prediction are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of long-term deformation prediction of immersed tube tunnel foundation, in particular to a long-term settlement prediction method for rigid-flexible foundation of immersed tube tunnel. BACKGROUND

[0002] As an important cross-sea project, the long-term stability of the foundation of the immersed tube tunnel is of great importance. In actual projects, such as the Dalian Bay Subsea Tunnel, the tunnel often needs to pass through multiple soft and hard strata with significant differences, and is leveled by laying gravel bed at the bottom of the foundation trench. This "rigid-flexible composite foundation" composed of gravel cushion, underlying soft soil and locally existing hard rock layer makes the supporting stiffness of the foundation highly uneven in space, bringing great challenges to settlement prediction.

[0003] However, when dealing with such complex foundation problems, the existing settlement prediction methods have significant limitations. Traditional methods often simplify the foundation as a homogeneous soil layer for analysis, or use the layer-wise summation method which is difficult to accurately describe the complex stress transfer mechanism of the hard layer to the underlying soft soil layer, resulting in deviations in the judgment of the settlement influence range.

[0004] Existing calculations generally rely on the compression modulus of the soil obtained through short-term tests, which ignores the creep and secondary consolidation effects of the soil under long-term load, thus systematically underestimating the final settlement deformation of the immersed tube tunnel, leaving potential risks for the long-term safe operation of the project.

[0005] Therefore, the present application proposes a long-term settlement prediction method for rigid-flexible foundation of immersed tube tunnel to solve the problems of the prior art. SUMMARY

[0006] In view of the deficiencies of the prior art, the present application provides a long-term settlement prediction method for rigid-flexible foundation of immersed tube tunnel, which solves the problem that the settlement prediction method for the foundation of the immersed tube tunnel generally regards the mechanical parameters of the foundation soil as constant short-term parameters, and fails to fully consider the interaction between the long-term performance degradation of the foundation material and the spatial range of settlement influence, resulting in deviations in the prediction results of the long-term settlement deformation of the immersed tube tunnel.

[0007] To solve the above technical problems, the present application provides a new long-term settlement prediction method and system for rigid-flexible foundation of immersed tube tunnel.

[0008] The present application provides a long-term settlement prediction method for rigid-flexible foundation of immersed tube tunnel, which establishes a time function of the compression modulus of the foundation soil, and couples and iterates this time function with the analysis process of the settlement influence depth, finally determines a most unfavorable design influence depth that can envelope the full time domain, and performs long-term settlement analysis based on this, thereby obtaining more physically realistic prediction results.

[0009] The method specifically comprises the following steps:

[0010] The long-term compression deformation data of the foundation soil is obtained through indoor tests. In a specific embodiment, this step comprises performing a long-term one-dimensional compression test on the obtained undisturbed soil sample, and recording the change of the sample height with time under different loads during the test. Before the compression test, the relative density G s and the dry density p d of the undisturbed soil sample can be measured, and the initial void ratio e0of the undisturbed soil sample is calculated according to the measured relative density G s and the dry density p d by the following formula:

[0011]

[0012] In the formula, p w is the density of water.

[0013] According to the long-term compression deformation data, a long-term compression modulus time-varying reference function characterizing the change of the compression modulus of the foundation soil with time is fitted. This process can comprise:

[0014] According to the long-term compression deformation data and the initial void ratio e0, the void ratios e p1 and e p2 of the soil sample after being stabilized under the action of adjacent two levels of loads p1and p2are calculated, and the compression coefficient a v of the soil in this load interval is calculated by the following formula:

[0015]

[0016] According to the compression coefficient a v and the initial void ratio e0, the compression modulus of the foundation soil at different time points is converted, and regression analysis is performed on the data of the change of the compression modulus with time, to obtain the long-term compression modulus time-varying reference function. In a specific embodiment, the expression of the long-term compression modulus time-varying reference function may be an exponential decay form:

[0017]

[0018] In the formula, E is the average compression modulus at time t, t is time; C1is the final stable value of the compression modulus; C2is the decaying part of the compression modulus; k is the decay rate of the compression modulus, and C1, C2, and k are all material constants obtained through regression analysis.

[0019] Next, multiple characteristic time nodes within the design service life of the immersed tunnel are selected, and for each characteristic time node, the corresponding settlement influence depth is determined based on the time-varying reference function of the long-term compression modulus, thereby obtaining a set composed of multiple settlement influence depths. For each characteristic time node t... j Determine the corresponding settlement influence depth H inf (t j The process is based on the calculated settlement impact reference rate β. i (t j The settlement influence reference rate β was determined by [the method / procedure]. i (t j The calculation of ) is based on the characteristic time node t. j Below, the benchmark settlement S calculated using the finite element model is... inf (t j ) and rigid boundaries are located at different depths H i Settlement at point S(H) i ,t j As input, the settlement influence reference rate β i (t j The formula for calculating ) is:

[0020]

[0021] In the formula, β i (t j ) is at the characteristic time node t j Below, the rigid boundary is located at depth H i The reference rate for settlement impact at that time. When the depth H... i The reference rate β of the settlement effect corresponding to the two consecutive increments i (t j When the change in depth H is less than a preset threshold, the depth H at this time can be... i The depth of settlement influence, H, was determined to be... inf (t j ).

[0022] Subsequently, all settlement influence depths in the set of settlement influence depths are compared, and the maximum value is taken as the design influence depth. This process uses the set of settlement influence depths as calculation input and determines the design influence depth H through a maximum value function. design The determination process is represented by the following formula:

[0023] H design =max{H inf (t1),H inf (t2),…,H inf (t n)};

[0024] H design is the design influence depth;{H inf (t1), H inf (t2), …, H inf (t n )} is a set composed of the settlement influence depths; H inf (t1), H inf (t2), H inf (t n ) is a settlement influence depth in the set; and n is the total number of the settlement influence depths in the set.

[0025] Finally, a final analysis model is constructed based on the design influence depth, long-term analysis is performed in the final analysis model by using the long-term compression modulus time-varying reference function, and a long-term settlement result of the immersed tunnel is obtained. The final analysis model is constructed with the design influence depth as a lower boundary depth, and the long-term settlement result includes a settlement history curve and a final settlement value of the immersed tunnel over time. The obtained final settlement value can be compared with a pre-set settlement control standard to judge the long-term settlement stability of the immersed tunnel.

[0026] The second aspect of the present application provides a long-term settlement prediction system for a rigid-flexible foundation of an immersed tunnel, and the system comprises:

[0027] A data acquisition module is configured to acquire long-term compression deformation data of the foundation soil through an indoor test.

[0028] A function fitting module is configured to fit a long-term compression modulus time-varying reference function representing the change of the compression modulus of the foundation soil over time according to the long-term compression deformation data.

[0029] A depth determination module is configured to select a plurality of characteristic time nodes within the design service life of the immersed tunnel, determine a corresponding settlement influence depth for each characteristic time node according to the long-term compression modulus time-varying reference function, thereby obtaining a set composed of a plurality of settlement influence depths, and compare all the settlement influence depths in the set composed of the settlement influence depths, and take the maximum value as a design influence depth.

[0030] A settlement prediction module is configured to construct a final analysis model based on the design influence depth, perform long-term analysis in the final analysis model by using the long-term compression modulus time-varying reference function, and obtain a long-term settlement result of the immersed tunnel.

[0031] The present application provides a long-term settlement prediction method for a rigid-flexible foundation of an immersed tunnel, and has the following beneficial effects:

[0032] 1. The application can reflect the creep and consolidation effect of the foundation material under long-term load by establishing the time-varying reference function of the long-term compression modulus of the foundation soil, describing the compression modulus of the soil body as a continuous process changing with time, overcoming the technical defects of the traditional method using short-term constant parameters, and improving the accuracy and reliability of the settlement prediction results.

[0033] 2. The application can couple the time-varying material modulus and the calculation of the settlement influence depth at multiple characteristic time nodes, and finally select the maximum value of the influence depth as the design influence depth. The interaction between material performance degradation and stress influence space range is fully considered, the boundary conditions of the calculation model can envelope the most unfavorable working conditions in the entire design service life, so that the structure design is based on safer consideration, and the long-term stability of the project is improved.

[0034] 3. The application provides a systematic analysis process, which can output the complete settlement history curve and the final settlement value of the immersed tunnel with time development. This quantitative and process-based prediction result provides clear technical basis for engineering design optimization, construction risk control and operation period maintenance, reduces the experience-based judgment in the design process, and enhances the scientificity and flexibility of engineering decision-making. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 is a numerical model schematic diagram of the joint action of the gravel base and the soft soil foundation of the application;

[0036] Figure 2 is a numerical model schematic diagram of the joint action of the gravel base and the soft and hard uneven foundation of the application;

[0037] Figure 3 is a time history curve diagram of the sample settlement amount changing with time in the one-dimensional compression test of the application;

[0038] Figure 4 is a time history curve diagram of the sample void ratio changing with time in the one-dimensional compression test of the application;

[0039] Figure 5 is a time history curve diagram of the sample compression modulus changing with time in the one-dimensional compression test of the application;

[0040] Figure 6 is a time history curve diagram of the average compression modulus changing with time and the fitting result diagram of the application;

[0041] Figure 7 is a flow chart of the long-term settlement prediction method of the immersed tunnel rigid and flexible foundation of the application;

[0042] Figure 8 is a functional module block diagram of the long-term settlement prediction system of the immersed tunnel rigid and flexible foundation of the application.

[0043] Wherein, 10, data acquisition module;20, function fitting module;30, depth determination module;40, settlement prediction module. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the specification of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0045] Referring to the drawings Figure 1 to the drawings Figure 7 , the drawings Figure 1 It is a numerical model schematic diagram of the combined action of the gravel base and the soft soil foundation according to an embodiment of the present application;The drawings Figure 2 It is a numerical model schematic diagram of the combined action of the gravel base and the soft and hard uneven foundation according to an embodiment of the present application;The drawings Figure 3 It is a time curve graph of the sample settlement amount changing with time in the one-dimensional compression test according to an embodiment of the present application;The drawings Figure 4 It is a time curve graph of the sample void ratio changing with time in the one-dimensional compression test according to an embodiment of the present application;The drawings Figure 5 It is a time curve graph of the sample compression modulus changing with time in the one-dimensional compression test according to an embodiment of the present application;The drawings Figure 6 It is a time curve graph of the average compression modulus changing with time and a fitting result graph according to an embodiment of the present application;The drawings Figure 7 The flow chart of the long-term settlement prediction method of the immersed tunnel rigid and flexible foundation provided by the embodiments of the present application.

[0046] The embodiments of the present application provide a long-term settlement prediction method of an immersed tunnel rigid and flexible foundation, which takes a specific immersed tunnel project as the background, and can include the following steps:

[0047] S1, obtaining long-term compression deformation data of foundation soil of an engineering site through indoor test;

[0048] S2, fitting a long-term compression modulus time-varying reference function representing the compression modulus of the foundation soil changing with time according to the long-term compression deformation data;

[0049] S3, selecting a plurality of characteristic time nodes within the design service life of the immersed tunnel, and for each characteristic time node, determining a corresponding settlement influence depth according to the long-term compression modulus time-varying reference function, so as to obtain a set composed of a plurality of settlement influence depths;

[0050] S4. Compare all settlement influence depths in the set of settlement influence depths and take the maximum value as the design influence depth.

[0051] S5. Based on the design influence depth, construct the final analysis model. In the final analysis model, use the time-varying benchmark function of long-term compression modulus to conduct long-term analysis and obtain the long-term settlement results of the immersed tunnel.

[0052] In one specific embodiment, the basic physical and mechanical parameters and long-term deformation data of the foundation soil are first obtained through step S1. This process includes drilling and sampling at the engineering site to obtain undisturbed soil samples, and determining the relative density G of the soil particles through laboratory geotechnical tests. s and dry density ρ d Based on the measured parameters, the initial void ratio e0 of the undisturbed soil sample is calculated using the following formula:

[0053]

[0054] In the formula, ρ w This is the density of water.

[0055] Subsequently, long-term one-dimensional consolidation compression tests with graded loading were conducted on the undisturbed soil samples, and the changes in sample settlement over time under each load level were recorded, as shown in the attached figure. Figure 3 As shown.

[0056] In step S2, based on the experimental data obtained in step S1, a constitutive relation reflecting the long-term mechanical behavior of the foundation soil is established. First, based on the settlement recorded in the experiments, the void ratio at different time points is calculated, and its variation process is shown in the attached figure. Figure 4 As shown. Based on the porosity e of the soil sample after stabilization under adjacent load levels p1 and p2. p1 and e p2 The soil compression coefficient α within the load range can be calculated using the following formula. v :

[0057]

[0058] Based on the soil compression coefficient and void ratio, the soil compression modulus E at different time points was calculated. s Its changing pattern over time is shown in the attached figure. Figure 5 As shown. To characterize the long-term deformation properties of the foundation as a whole, the compression modulus of multiple soil samples with loading times exceeding a specific duration (e.g., 100 days) can be averaged, and the average compression modulus can be calculated. The variation of the function with time t was fitted using a function, and the results are shown in the appendix. Figure 6 As shown. In this embodiment, an exponentially decaying function can be used as the time-varying reference function for the long-term compressibility modulus:

[0059]

[0060] In the formula, C1 is the average compressive modulus at time t, where t is time; C2 is the final stable value of the compressive modulus; C2 is the decaying part of the compressive modulus; k is the decay rate of the compressive modulus, and C1, C2, and k are all material constants obtained through regression analysis.

[0061] In steps S3 and S4, a design influence depth that encompasses the entire time domain under the most unfavorable operating condition is determined using numerical simulation. This process involves repeatedly performing influence depth analysis at multiple selected characteristic time nodes (e.g., year 1, year 10, year 50, and year 100). At each characteristic time node t... j The long-term compressive modulus at that moment The material parameters are input into the finite element analysis model. This is achieved by establishing the model as shown in the attached figure. Figure 1 The semi-infinite foundation model shown and attached Figure 2 The finite element numerical model with a rigid boundary at the bottom, as shown, was used to calculate the reference settlement S. inf (t j ) and the rigid boundary are located at different depths H i Settlement at point S(H) i ,t j Based on these two settlement values, the settlement influence reference rate β is calculated using the following formula. i (t j ):

[0062]

[0063] By judging β i (t j Determine the time point t by checking if the rate of change of ) is less than a preset threshold. j The depth of the settlement influence S inf (t j After completing the calculations for all characteristic time points, the set {H} of the obtained settlement influence depths is compared. inf (t1),H inf (t2),…,H inf (t n The maximum value among them is taken as the final design influence depth H. design .

[0064] In step S5, the final long-term settlement prediction is performed. This is based on the design influence depth H determined in step S4. design Construct the geometric boundary of the final analysis model and apply the time-varying reference function of the long-term compressibility modulus. The ground material is endowed to the model. Through a complete long-term time-history analysis of the model, the settlement history curve and the final settlement value of the immersed tunnel in the entire design service life are finally obtained.

[0065] The embodiment of the present application also provides a long-term settlement prediction system for immersed tunnel rigid-flexible foundation, which is used to execute the above method. The system can include a data acquisition module 10, a function fitting module 20, a depth determination module 30 and a settlement prediction module 40. The data acquisition module 10 is used to execute the function of step S1 to acquire the long-term compression deformation data of the foundation soil. The function fitting module 20 is used to execute the function of step S2 to fit the long-term compression modulus time-varying reference function. The depth determination module 30 is used to execute the functions of steps S3 and S4 to determine the final design influence depth. The settlement prediction module 40 is used to execute the function of step S5 to obtain the final long-term settlement result.

[0066] Referring to the drawings Figure 3 to the drawings Figure 6 The process corresponds to the aforementioned steps S1 and S2, and the purpose is to establish a mathematical model that can accurately describe the mechanical property change of the foundation soil under long-term load action through indoor test and data analysis.

[0067] Firstly, the long-term compression deformation data acquisition of the foundation soil is executed. This step starts from the engineering site, a plurality of undisturbed soil samples are taken from different strata under the immersed tunnel by drilling and the like, and are sealed and stored to maintain the natural water content and structure state. Then, a series of tests are performed on the soil samples in the laboratory.

[0068] Firstly, the basic physical property indexes of the soil sample are measured. Part of the undisturbed soil sample is taken, and its soil particle relative density G s and dry density ρ d are measured by standard soil test method. Based on the two parameters, the initial void ratio e0 of the soil sample can be calculated, and the calculation formula is:

[0069]

[0070] In the formula, G s is the soil particle relative density; ρ d is the dry density of the soil sample; and ρ w is the density of water.

[0071] Secondly, the long-term one-dimensional consolidation compression test is performed. The prepared saturated undisturbed soil sample is placed in a one-dimensional consolidation instrument, and a vertical load is applied by using a staged loading method. After each stage of load is applied, the development process of the height change value (i.e. settlement amount) of the soil sample with time is continuously monitored and recorded until the deformation is stable or the preset test time is reached. As shown in FIG. 2, the test process is divided into three stages: the first stage is the pre-consolidation stage, the second stage is the consolidation stage, and the third stage is the post-consolidation stage. Figure 3As shown, the figure demonstrates the settlement-time curves of 8 different soil samples under staged loading, and the loading time of some soil samples exceeds 100 days to fully capture the secondary consolidation deformation or creep effect of the soil.

[0072] Then, based on the obtained experimental data, data processing and function fitting are performed.

[0073] First, the void ratio and compression coefficient are calculated. According to the real-time change value of the sample height under each load recorded in the one-dimensional compression test, the void ratio e corresponding to different time points is converted. As shown in the attached Figure 4 As shown, the figure demonstrates the void ratio-time curves of 8 soil samples during the test. Subsequently, according to the void ratios e p1 and e p2 under the action of any two adjacent loads p1 and p2, the compression coefficient a v of the soil in this load interval is calculated by the following formula:

[0074]

[0075] In the formula, e p1 is the stable void ratio under the load p1; e p2 is the stable void ratio under the load p2.

[0076] Second, the time-varying compression modulus is calculated and fitted. The compression modulus E s of the soil can be converted by the compression coefficient a v and the corresponding void ratio e, and the conversion formula is E s = (1+e) / a v . Through this formula, the compression modulus values of different soil samples at different time points can be obtained, and the change trend is shown in the attached Figure 5 In order to obtain parameters that can represent the overall characteristics of the entire rigid-flexible foundation, the compression modulus calculated at each time point for multiple soil samples with sufficient loading time (for example, soil samples 4, 5, 6, 7, and 8 with loading time exceeding 100 days) can be averaged and weighted.

[0077] Finally, function regression analysis is performed on the scatter data of the average compression modulus versus time t, so as to obtain a continuous and smooth long-term compression modulus time-varying reference function. As shown in the attached Figure 6 figure, the scatter points are the average compression modulus data, and the solid line is the function curve fitted. In a specific embodiment, the function can be selected in the form of exponential decay:

[0078]

[0079] In the formula, Let C1 be the average compressive modulus at time t, where t is time; C2 be the final stable value of the compressive modulus; C3 be the decaying portion of the compressive modulus; and k be the decay rate of the compressive modulus. C1, C2, and k are all material constants obtained through regression analysis. This function is the core constitutive input for subsequent long-term settlement analysis.

[0080] See attached document Figure 1 With appendix Figure 2 This process corresponds to steps S3 and S4 mentioned above. Its core lies in coupling the long-term performance evolution of the foundation soil with the spatial range of settlement effects to determine a design influence depth that can cover all working conditions throughout the entire design service life. This process is not a single static calculation, but an iterative process of analyzing and optimizing the influence depth multiple times over time.

[0081] First, select several characteristic time nodes within the design service life of the immersed tunnel. For example, if the design service life is 100 years, the 1st year, the 10th year, the 50th year, and the 100th year can be selected as characteristic time nodes t. j , where j = 1, 2, 3, 4.

[0082] Subsequently, for each selected feature time node t j The depth of settlement influence H at that moment was determined by numerical simulation. inf (t j This step is performed in a loop, for each t. j Repeat the following steps:

[0083] First, determine the material parameters at the current time point. Set the current characteristic time point t... j Substitute into the time-varying reference function of long-term compressive modulus In the calculation, the average compressibility modulus of the foundation at that moment is obtained. This modulus value will be used as the foundation material parameter for the numerical model in the current loop.

[0084] Second, a numerical analysis model was established using the finite element analysis software ABAQUS to calculate the settlement. This process requires the creation of two types of finite element models. One type is a semi-infinite foundation model used to calculate the baseline settlement, as shown in the attached figure. Figure 1 As shown in the figure. In ABAQUS, this model includes an equivalent strip foundation for the immersed tunnel, a gravel subgrade, and a soft soil foundation. The foundation depth and width are both set to sufficiently large values ​​(e.g., 10 times the foundation width) to simulate the boundary conditions of an infinitely deep foundation. Another type is a finite element model with a rigid boundary at the bottom, used to calculate settlement at different depths, as shown in the attached figure. Figure 2 As shown, rigid boundaries (e.g., dense silty sand layers) are set at different depths H from the top surface of the soft soil foundation. i Place.

[0085] In ABAQUS, configure the model as follows: set the strip foundation as a rigid body; the soft soil foundation model can be set as an elasto-plastic body that obeys the Tresca yield criterion, with its elastic modulus based on the time-varying compressive modulus at the current time point. Confirm that the crushed stone subgrade material can be set to obey the Mohr-Coulomb yield criterion. Configure the interactions between different parts of the model and apply appropriate displacement boundary conditions to the sides and bottom of the model. In the load analysis step, apply the design load to the foundation. After completing the model setup and mesh generation, submit the job for analysis.

[0086] Using ABAQUS calculations, the baseline settlement S was obtained for a semi-infinite foundation model. inf (t j Then, for the bottom rigid boundary located at depths H1, H2, ..., H, respectively. m Multiple finite element models were used to calculate the settlement values ​​S(H1,t) one by one, resulting in a series of corresponding settlement values. j ),S9H2,t j ),…,S9H m ,t j ).

[0087] Third, calculate the settlement impact reference rate and determine the impact depth at this time node. Based on the baseline settlement obtained in the previous step and the settlement at a series of different depths, calculate the impact depth at the current characteristic time node t using the following formula. j Below, the rigid boundary is located at different depths H i Reference rate β of settlement effect at time i (t j 0:

[0088]

[0089] In the formula, S(H i ,t j ) represents the time node t j The lower, rigid boundary is located at depth H i Settlement at time; S inf (t j ) represents the time node t j The baseline settlement of the lower and semi-infinite foundations.

[0090] By analyzing the reference rate β of the subsidence impact i (t j With depth H i The pattern of change determines the current time point t. j The depth of the settlement influence H inf (t j The criterion is: when the depth H ithe ratio of the settlement influence reference rate corresponding to the two consecutive increments of the settlement (e.g. β i (t j ) / β i+1 (t j )) is less than a preset threshold value, or the rate of change is less than a preset threshold value (e.g. 5%), it can be considered that the contribution of the deeper stratum to the settlement is negligible, and the depth H i at this time is determined as the settlement influence depth H inf (t j ) of the time node.

[0091] After the cyclic calculation of all characteristic time nodes is completed, a set {H inf (t1), H inf (t2), …, H inf (t n )} consisting of multiple settlement influence depths is obtained.

[0092] Finally, all the settlement influence depths in the set are compared, and the maximum value is taken as the final design influence depth H design . The process is represented by the following formula:

[0093] H design = max{H inf (t1), H inf (t2), …, H inf (t n )};

[0094] In the formula, H design is the design influence depth; {H inf (t1), H inf (t2), …, H inf (t n )} is the set consisting of settlement influence depths; H inf (t1), H inf (t2), H inf (t n ) is the settlement influence depth in the set; and n is the total number of settlement influence depths in the set. The design influence depth H design represents the maximum spatial influence range that the foundation settlement may reach within the entire design service life, and provides a reliable model boundary for subsequent final settlement prediction.

[0095] The process corresponds to the aforementioned step S5, and is a step of performing final long-term settlement analysis of the immersed tunnel after the design influence depth and the long-term constitutive relationship of the foundation soil are determined.

[0096] First, based on the design influence depth H designThe final analysis model was constructed using the finite element analysis software ABAQUS. The geometric dimensions and structural composition (including the equivalent strip foundation of the immersed tunnel, the crushed stone subgrade, and the foundation soil) of this model are basically the same as the previous model. The key difference is that the lower boundary of this model is set at a depth of H. design At this point, a fixed displacement boundary (i.e., a rigid boundary) is applied. This ensures that the computational model has a reasonable computational boundary that covers the most unfavorable conditions throughout the entire design time domain.

[0097] Then, material properties are assigned to the final analysis model, and long-term time history analysis is performed. For the foundation soil in the model, its core mechanical behavior is determined by a time-varying reference function of the long-term compression modulus. This is used to describe the process. In ABAQUS, this time-varying function can be used as the constitutive relation input for the foundation material through a user-defined material subroutine (UMAT) or the software's built-in creep and consolidation modules. The properties of other materials in the model (such as the gravel subgrade) remain unchanged.

[0098] After completing the model setup, apply the design loads and set an analysis step that covers the entire design service life (e.g., 100 years). After submitting the job, ABAQUS will perform a complete long-term time history analysis to calculate the settlement values ​​of the immersed tunnel foundation at various time points within the design service life.

[0099] Finally, the analysis results are extracted and applied. Two core long-term settlement prediction results can be obtained from the calculations:

[0100] First, there is the settlement history curve of the immersed tunnel over time, which can intuitively show the rate and trend of settlement in the early, middle and late stages.

[0101] Second, the final settlement value of the immersed tunnel, that is, the total settlement at the end of its designed service life.

[0102] The final settlement value obtained can be compared with the settlement control standards or specification limits set in advance for the project, so as to directly judge whether the long-term settlement stability of the immersed tunnel meets the design requirements, thereby providing direct technical support for engineering design and risk assessment.

[0103] See attached document Figure 8 , attached Figure 8 This is a functional block diagram of a long-term settlement prediction system for rigid-flexible foundations of immersed tunnels according to an embodiment of the present invention.

[0104] The embodiment of the present application also provides a long-term settlement prediction system for a rigid-flexible foundation of a immersed tunnel. The system can be a general computer device installed and running a specific application program, or a special computer device. The system can include one or more processors, memories and bus systems for connecting various components in the hardware structure. The memories store computer program instructions, and when the processors execute the instructions, the long-term settlement prediction method for the rigid-flexible foundation of the immersed tunnel in the foregoing embodiment can be implemented.

[0105] Functionally, the system can be divided into multiple functional modules, and each module is configured to perform a specific step in the method. In one specific embodiment, the system can include a data acquisition module 10, a function fitting module 20, a depth determination module 30 and a settlement prediction module 40.

[0106] The data acquisition module 10 is used to perform the acquisition and management of long-term compression deformation data of the foundation soil. The module is configured to receive or read the original data obtained by the indoor long-term one-dimensional compression test from the outside (such as a test database or user input), including the records of the settlement of the sample under each load with time and the basic physical property indexes of the soil sample.

[0107] The function fitting module 20 is used to fit the time-varying reference function of the long-term compression modulus according to the data provided by the data acquisition module 10. The module internally integrates the algorithms of data processing and regression analysis. It is configured to perform the following operations: according to the input test data, the void ratio and the compression coefficient of the soil body at different time points are calculated; the compression modulus of the soil body at different time points is converted based on these parameters; the function fitting is performed on the obtained average compression modulus and time scatter data to determine the specific expression of the time-varying reference function (including the material constants C1, C2, k therein), and the function is provided for the subsequent module.

[0108] The depth determination module 30 is used to determine the depth affected by the time and space coupling. The module is a functional unit for implementing the core technical scheme of the present application, and it is configured to perform the following operations: receiving the time-varying reference function generated by the function fitting module 20; performing loop calculation according to a plurality of preset characteristic time nodes; at each time node, calling a numerical simulation program (such as ABAQUS), taking the time-varying compression modulus corresponding to the time as a material parameter to calculate the reference settlement and the settlement under different boundary depths; determining the settlement affected depth at the time node according to the calculation result; after completing the calculation of all nodes, comparing all affected depth values, and outputting the maximum value as the final design affected depth.

[0109] A settlement prediction module 40 is configured to perform the final long-term settlement prediction. The module receives the design-induced depth from the depth determination module 30 and the time-varying reference function from the function fitting module 20. It is configured to construct a final numerical analysis model based on the received design-induced depth, to input the time-varying reference function as the ground material constitutive, to call a numerical simulation program to perform a long-term time history analysis covering the entire design service life, and finally to extract and output the settlement history curve and the final settlement value of the immersed tunnel from the analysis results.

[0110] While embodiments of the application have been shown and described, it is to be understood that the application is not limited to these embodiments. Rather, it is the intention that all variations and modifications, which can become apparent to those skilled in the art, be included within the scope of the application as defined by the appended claims and their equivalents.

Claims

1. A method for long-term settlement prediction of rigid- flexible foundation of immersed tube tunnel, characterized in that, The method comprises the following steps: S1, obtaining long-term compression deformation data of foundation soil through indoor test; S2, fitting a long-term compression modulus time-varying reference function representing the change of compression modulus of the foundation soil with time according to the long-term compression deformation data; S3, selecting a plurality of characteristic time nodes within the design service life of the immersed tunnel, and determining the corresponding settlement influence depth for each characteristic time node according to the long-term compression modulus time-varying reference function, thereby obtaining a set composed of a plurality of settlement influence depths; S4, comparing all the settlement influence depths in the set composed of the settlement influence depths, and taking the maximum value as the design influence depth; S5, constructing a final analysis model based on the design influence depth, and performing long-term analysis in the final analysis model by using the long-term compression modulus time-varying reference function, thereby obtaining the long-term settlement result of the immersed tunnel.

2. The method of long-term settlement prediction of rigid-soft ground for immersed tunnel according to claim 1, characterized in that, In step S1, the step of obtaining long-term compression deformation data of foundation soil through indoor test comprises: Before acquiring long-term compression deformation data of the ground soil through indoor test, the relative density G of soil particles of undisturbed soil sample is measured s and the dry density p d , and the initial void ratio e0 of the undisturbed soil sample is calculated from the measured relative density G of soil particles s and the dry density p d by the following formula: where p is the density of water. w where p is the density of water.

3. The method of predicting long-term settlement of a rigid- flexible ground of a immersed tunnel according to claim 1, wherein, In step S2, the step of fitting a long-term compression modulus time-varying reference function representing the change of compression modulus of the foundation soil with time according to the long-term compression deformation data comprises: According to the long-term compression deformation data, the void ratio e of the soil sample after being stabilized under the action of adjacent two levels of load p1 and p2 is calculated p1 and e p2 , and the compression coefficient a of the soil body in the load interval is calculated by the following formula v : According to the soil compression coefficient a v and the initial void ratio e0, the compression modulus of the foundation soil at different time points is converted. performing regression analysis on the data representing the change of compression modulus with time, thereby obtaining the long-term compression modulus time-varying reference function.

4. The method of claim 3, wherein, The long-term compression modulus time-varying reference function The expression is of an exponential decay form: wherein C1is the final stabilized value of the compression modulus; C2is the decaying portion of the compression modulus; k is the decay rate of the compression modulus, C1, C2, k are all material constants obtained by regression analysis.

5. The method of predicting long-term settlement of a rigid- flexible ground of a immersed tunnel according to claim 1, wherein, In step S3, the step of selecting a plurality of characteristic time nodes within the design service life of the immersed tunnel, and determining the corresponding settlement influence depth for each characteristic time node according to the long-term compression modulus time-varying reference function, thereby obtaining a set composed of a plurality of settlement influence depths comprises: For each of the characteristic time nodes t j , the process of determining the corresponding settlement influence depth H inf (t j ) is based on the calculated settlement influence reference rate β i (t j ). The reference rate β for the impact of settlement i (t j The calculation of ) is based on the characteristic time node t. j Below, the benchmark settlement S calculated using the finite element model is... inf (t j ) and rigid boundaries are located at different depths H i Settlement at point S(H) i ,t j As input, the settlement influence reference rate β i (t j The formula for calculating ) is: where β i (t j ) is the reference rate of the settlement influence at the characteristic time node t j , when the rigid boundary is located at the depth H i .

6. The method of long-term settlement prediction of rigid- flexible ground of immersed tunnel according to claim 5, characterized in that, determining the settling influence depth H inf (t j ) is given by when the depth H i corresponding to the two consecutive increments of the depth H i (t j ) is less than a preset threshold value, the depth H i at this time is determined as the settlement influencing depth H inf (t j ).

7. The long-term settlement prediction method of a rigid- flexible ground of a immersed tube tunnel according to claim 1, characterized in that, In step S4, the step of comparing all the settlement influence depths in the set composed of the settlement influence depths, and taking the maximum value as the design influence depth comprises: The process of comparing a plurality of characteristic time nodes within the design service life of the immersed tunnel, and taking the maximum value as the design influence depth, is to take the set composed of the settlement influence depths as the calculation input, and determine the design influence depth by using the maximum value function, and the determination process is represented by the following formula: H design = max{H inf (t1), H inf (t2),..., H inf (t n )}; where H design is the design impact depth;{H inf (t1), H inf (t2),..., H inf (t n ) is a set of the settlement impact depths; H inf (t1), H inf (t2), H inf (t n ) is a settlement impact depth in the set; and n is the total number of settlement impact depths in the set.

8. The long-term settlement prediction method of a rigid- flexible ground of a immersed tube tunnel according to claim 1, characterized in that, In step S5, the step of constructing a final analysis model based on the design influence depth, and performing long-term analysis in the final analysis model by using the long-term compression modulus time-varying reference function, thereby obtaining the long-term settlement result of the immersed tunnel comprises: The final analysis model is constructed by taking the design influence depth as the lower boundary depth, and the long-term settlement result comprises the settlement history curve and the final settlement value of the immersed tunnel with time.

9. System for long-term settlement prediction of rigid- flexible foundations of immersed tunnels, to be applied to the method according to any one of claims 1-8, characterized in that, The system comprises: a data acquisition module configured to obtain long-term compression deformation data of foundation soil through indoor test; a function fitting module configured to fit a long-term compression modulus time-varying reference function representing the change of compression modulus of the foundation soil with time according to the long-term compression deformation data; a depth determination module configured to select a plurality of characteristic time nodes within a design service life of the immersed tunnel, and for each of the characteristic time nodes, determine a corresponding settlement influence depth according to the long-term compression modulus time-varying reference function, so as to obtain a set composed of a plurality of the settlement influence depths, and compare all the settlement influence depths in the set composed of the settlement influence depths, and take a maximum value as a design influence depth; a settlement prediction module configured to construct a final analysis model based on the design influence depth, and perform long-term analysis in the final analysis model by using the long-term compression modulus time-varying reference function, so as to obtain a long-term settlement result of the immersed tunnel.

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