Computer-aided simulation method for groundwater level and soil deformation

Abstract

The present application relates to the technical field of data simulation, and particularly relates to a computer-aided simulation method for groundwater level and soil deformation. The method determines the theoretical ground surface response characteristics corresponding to each set of geological parameters through a theoretical response simulation model, and then compares the theoretical ground surface response characteristics with the actual ground surface response characteristics. The geological parameter degradation index between the actual and the theoretical is determined by using intuitive data comparison, and the deviation distance is obtained. The deviation distance can be used to adjust the complexity of the constitutive relation of the initial simulation model, and the geological parameter simulation unit of the simulation model is adjusted through the geological parameter degradation index. The model optimization of the present application can more accurately simulate the spatial distribution and time evolution of the groundwater pressure field and the soil stress-strain field, and ensure the accuracy of the simulation model output results.

Description

Technical Field

[0001] This invention relates to the field of data simulation technology, specifically to a computer-aided simulation method for groundwater level and soil deformation. Background Technology

[0002] In soft soil foundation reinforcement projects, such as those involving coastal areas or reclamation, plastic drainage boards (PVD) systems accelerate soil consolidation and enhance foundation strength by providing superior drainage channels. However, the long-term efficiency of PVD deteriorates due to two main mechanisms. The first is physical blockage, where fine soil particles migrate and accumulate around the PVD filter membrane under the influence of water flow, forming low-permeability zones that directly hinder pore water drainage. The second is biochemical gas lock, commonly found in soft soils rich in organic matter. The anaerobic decomposition of organic matter produces insoluble gases, which occupy pore channels, not only blocking water flow but also significantly altering the soil's compressibility. Both of these degradation mechanisms lead to a slowdown in the foundation consolidation rate, but their physical causes and the ways in which they affect the hydraulic and mechanical properties of the soil are fundamentally different.

[0003] These two degradation mechanisms are difficult to distinguish in traditional computer simulation models used to guide engineering practice, and it is difficult to provide dynamic PVD system health status information covering the entire engineering site. This lack of information causes the simulation model to be seriously out of touch with the actual engineering state due to the lack of accurate parameter input. Blindly making engineering judgments based on simulation results may lead to the risk of project delays or even project failure. Summary of the Invention

[0004] To address the technical problem in existing simulation models where the inability to distinguish between two degradation mechanisms leads to incorrect parameter input and inaccurate simulation output, this invention aims to provide a computer-aided simulation method for groundwater level and soil deformation. The specific technical solution adopted is as follows:

[0005] This invention proposes a computer-aided simulation method for groundwater level and soil deformation, the method comprising:

[0006] Obtain the surface elevation and tidal response sequences and tidal water level sequences at various locations within the PVD engineering site;

[0007] The pressure transmission delay between the surface elevation tidal response sequence and the tidal water level sequence is obtained; the pulsation amplitude of the surface elevation tidal response sequence is obtained; and the pressure transmission delay and pulsation amplitude are used as the actual surface response characteristics at each location.

[0008] Using soil permeability coefficient and gas saturation as geological parameters, a pre-trained theoretical response simulation model is used to obtain the theoretical surface response characteristics corresponding to each set of geological parameters; the projection characteristics of the actual surface response characteristics in the theoretical surface response characteristic set are obtained; the geological parameters corresponding to the projection characteristics are compared with healthy geological parameters to obtain the geological parameter deterioration index; and the deviation distance between the actual surface response characteristics and the projection characteristics is obtained.

[0009] An initial simulation model is constructed. The geological parameter simulation units of the initial simulation model are calibrated according to the geological parameter deterioration index. The constitutive complexity of the initial simulation model is calibrated according to the deviation distance to obtain the calibrated optimized simulation model.

[0010] Furthermore, the method for obtaining the surface elevation tidal response sequence includes:

[0011] The surface elevation change sequence at each location is obtained, and the surface elevation change sequence is decomposed using a signal decomposition algorithm based on coefficient recovery theory to obtain the surface elevation tidal response sequence.

[0012] Furthermore, the method for obtaining the pressure transmission delay includes:

[0013] The cross-correlation function of the surface elevation tidal response sequence and the tidal water level sequence is obtained, and the time lag corresponding to the peak value of the cross-correlation function is used as the pressure transmission delay.

[0014] Furthermore, the method for obtaining the pulsation amplitude includes:

[0015] The average amplitude of the surface elevation tidal response sequence is obtained, and the average amplitude is normalized to obtain the pulsating amplitude.

[0016] Furthermore, the theoretical response simulation model is based on Biot's consolidation theory, constructed using parameters of the soil structure, with the boundary condition being the tidal water level sequence, the input being geological parameters, and the output being the theoretical surface elevation tidal response sequence; the theoretical surface response characteristics are obtained based on the theoretical surface elevation tidal response sequence and the tidal water level sequence.

[0017] Furthermore, the method for obtaining the projection features includes:

[0018] The theoretical surface response features are mapped into multiple data points in a two-dimensional parameter space, and the two-dimensional surface formed by the data points is the theoretical surface. The two dimensions of the two-dimensional parameter space are pressure transmission delay and pulsation amplitude. The mapping points of the actual surface response features in the two-dimensional parameter space are taken as actual points. The data point closest to the actual point on the theoretical surface is taken as the projection point of the actual point, and the pressure transmission delay and pulsation amplitude corresponding to the projection point are taken as the projection features.

[0019] Furthermore, the method for obtaining the geological parameter deterioration index includes:

[0020] The geological parameter deterioration index includes the siltation degree index and the air resistance degree index;

[0021] The siltation index is obtained by the difference between the soil permeability coefficient in the projection feature and the maximum soil permeability coefficient under healthy conditions.

[0022] The gas resistance index is obtained by the difference between the gas saturation in the projected features and the minimum gas saturation under healthy conditions.

[0023] Furthermore, the deviation distance is the distance between the actual point and the projected point in the two-dimensional parameter space.

[0024] Furthermore, the geological parameter simulation unit for calibrating the initial simulation model based on the geological parameter deterioration index includes:

[0025] After mapping and normalizing the negative correlation of the siltation degree index, the soil permeability coefficient adjustment index is obtained. The initial soil permeability coefficient in the geological parameter simulation unit is multiplied by the soil permeability coefficient adjustment index to obtain the soil permeability coefficient after adjustment in the geological parameter simulation unit.

[0026] After normalizing the gas resistance index, add it to the positive integer 1 to obtain the gas saturation adjustment index. Multiply the initial gas saturation in the geological parameter simulation unit by the gas saturation adjustment index to obtain the adjusted gas saturation in the geological parameter simulation unit.

[0027] Further, calibrating the constitutive complexity of the initial simulation model based on the deviation distance includes:

[0028] After normalizing the deviation distance, add it to the positive integer 1 to obtain the complexity adjustment index. Multiply the initial constitutive relation complexity in the initial simulation model by the complexity adjustment index to obtain the adjusted constitutive relation complexity of the initial simulation model.

[0029] The present invention has the following beneficial effects:

[0030] This invention addresses the ill-conditioned inversion problem with multiple degradation mechanisms by not directly solving for the features. Instead, it uses a theoretical response simulation model to determine the theoretical surface response characteristics corresponding to each set of geological parameters, transforming the unstable inversion problem into a data model with a defined numerical space. This model is then compared with the actual surface response characteristics. The intuitive data comparison determines the geological parameter degradation index between the actual and theoretical values, and yields the deviation distance. The deviation distance represents the discrepancy between theory and practice. Therefore, it can be used to adjust the constitutive complexity of the initial simulation model and adjust the geological parameter simulation units of the simulation model using the geological parameter degradation index. This ensures that the initial simulation model incorporates the correct geological parameters, enabling it to more accurately simulate the spatial distribution and temporal evolution of groundwater pressure and soil stress-strain fields. This guarantees the accuracy of the simulation model's output results and improves the accuracy of its predictions of long-term foundation deformation and the remaining service life of the PVD system. Attached Figure Description

[0031] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be 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.

[0032] Figure 1 The flowchart illustrates a computer-aided simulation method for groundwater level and soil deformation, as provided in one embodiment of the present invention. Detailed Implementation

[0033] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a computer-aided simulation method for groundwater level and soil deformation proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0035] The following description, in conjunction with the accompanying drawings, details the specific scheme of a computer-aided simulation method for groundwater level and soil deformation provided by this invention.

[0036] Please see Figure 1The diagram illustrates a computer-aided simulation method for groundwater level and soil deformation according to an embodiment of the present invention. The method includes:

[0037] Step S1: Obtain the surface elevation tidal response sequence and tidal water level sequence at various locations in the PVD engineering site.

[0038] The settlement of the foundation in coastal areas is directly affected by tides. Tidal changes affect groundwater dynamics, thereby altering the land structure and causing settlement. Therefore, to analyze the hydraulic and mechanical properties of the soil, it is necessary to analyze the actual relationship between tides and settlement in the engineering area. Thus, step S1 first obtains the surface elevation tidal response sequence and tidal water level sequence at various locations within the PVD engineering site. The tidal water level sequence can be directly obtained from the region's geographic and meteorological monitoring results, while the surface elevation tidal response sequence represents the response of the engineering site height to tides.

[0039] Preferably, in this embodiment of the invention, because the directly collected surface elevation change sequence is a mixture of deformation caused by long-term consolidation settlement, elastic response to tidal loads, and other factors, and its observation frequency is much lower than the tidal frequency, direct analysis cannot effectively identify the tidal response. Therefore, the method for obtaining the surface elevation tidal response sequence in this embodiment of the invention includes:

[0040] The surface elevation change sequence at various locations is obtained, and this sequence is decomposed using a signal decomposition algorithm based on coefficient retrieval theory to obtain the surface elevation tidal response sequence. Because tidal motion is composed of the superposition of a finite number of tidal constituents with definite astronomical frequencies, the elastic response it induces on the Earth's surface is sparsity in the frequency domain. Therefore, by using a signal decomposition algorithm based on coefficient retrieval theory, a continuous surface elevation tidal response sequence can be separated from the information-mixed surface elevation change sequence. The surface elevation tidal response sequence eliminates the interference of deformation components such as long-term consolidation, retaining only the elastic cyclic deformation process of the land skeleton in response to tidal level changes, i.e., the "response" to the tides.

[0041] It should be noted that the method for collecting land elevation information under the engineering site is a well-known technique in the field, and the signal decomposition algorithm based on coefficient recovery theory is also an existing algorithm. The specific acquisition method and algorithm content will not be elaborated here.

[0042] Step S2: Obtain the pressure transmission delay between the surface elevation tidal response sequence and the tidal water level sequence; obtain the pulsation amplitude of the surface elevation tidal response sequence; use the pressure transmission delay and pulsation amplitude as the actual surface response characteristics at each location.

[0043] For the relationship between the surface elevation tidal response sequence and the tidal water level sequence, the pressure transmission delay between the two sequences should be analyzed first. This is because the decrease in permeability caused by physical blockage will lead to a large delay in the tidal influence and response. Therefore, the pressure transmission delay can be used as an important characteristic to reflect the physical degradation of PVD.

[0044] This invention further analyzes the pulsation amplitude of the surface elevation tidal response sequence. The pulsation amplitude characterizes the magnitude of the elastic strain generated by the soil under unit pressure fluctuation, directly reflecting the equivalent compressibility of the soil-pore fluid mixture. Insoluble bubbles generated by biochemical air resistance significantly increase the compressibility of the pore fluid, causing most of the external load energy to be used to compress the gas rather than causing soil skeleton deformation. Therefore, the air resistance effect directly manifests as a significant reduction in pulsation amplitude.

[0045] Therefore, pressure transmission delay and pulsation amplitude can be used as the actual surface response characteristics at various locations. That is, the actual surface response characteristics are two-dimensional features, with the two dimensions representing the physical or chemical degradation characteristics that may exist in PVD.

[0046] Preferably, the method for obtaining the pressure transmission delay in this embodiment of the invention includes:

[0047] The cross-correlation function of the surface elevation tidal response sequence and the tidal water level sequence is obtained, and the time lag corresponding to the peak value of the cross-correlation function is used as the pressure transmission delay.

[0048] Preferably, in this embodiment of the invention, the method for obtaining the pulsation amplitude includes:

[0049] The average amplitude of the surface elevation tidal response sequence is obtained, and the average amplitude is normalized to obtain the pulsating amplitude.

[0050] In this embodiment of the invention, the normalization method chosen is range standardization. By analyzing the maximum and minimum values ​​of the data interval, the normalized value of the data is determined. The specific method is a well-known technique to those skilled in the art and will not be described in detail here.

[0051] After step S2, each location at the engineering site will obtain a two-dimensional actual surface response characteristic during the monitoring period. It should be noted that the data processing method is the same for each location at the engineering site, therefore it will not be repeated; the following description will only use one location as an example.

[0052] Step S3: Using soil permeability coefficient and gas saturation as geological parameters, obtain the theoretical surface response characteristics corresponding to each set of geological parameters using a pre-trained theoretical response simulation model; obtain the projection characteristics of the actual surface response characteristics in the theoretical surface response characteristic set; compare the geological parameters corresponding to the projection characteristics with healthy geological parameters to obtain the geological parameter deterioration index; obtain the deviation distance between the actual surface response characteristics and the projection characteristics.

[0053] Soil permeability coefficient and gas saturation are important geological parameters in the scenario described in this invention embodiment. Soil permeability coefficient can characterize the soil's clogging status for PVD; gas saturation affects the equivalent volumetric compressibility modulus of pore fluid (water-gas mixture), thereby altering the overall compressibility of the soil. Therefore, this invention embodiment analyzes these two important parameters as geological parameters.

[0054] For ill-conditioned inversion problems with multiple quantitative mechanisms, directly solving for geological parameters from the information reflected in the actual surface response characteristics leads to non-unique solutions, and the solution process is quite sensitive to noise. To avoid these ill-conditioned problems, this embodiment of the invention does not directly solve for the deterioration characteristics, but instead determines the theoretical surface response characteristics corresponding to each set of geological parameters through a theoretical response simulation model. This transforms the unstable inversion problem into a data model with a clear numerical space, which is then compared with the actual surface response characteristics. The intuitive data comparison is used to determine the geological parameter deterioration index between the actual and theoretical values, and the deviation distance is obtained.

[0055] First, a theoretical response simulation model needs to be pre-trained. The input to this model is geological parameters, and the output results yield the theoretical surface response characteristics corresponding to each set of geological parameters. This model can simultaneously couple pore fluid pressure diffusion with the elastic deformation of the soil skeleton, representing a foundation response model under an idealized assumption: the independent influence of two mechanisms, physical blockage and chemical vapor resistance. This theoretical response simulation model is common in engineering fields and only reflects the results of one theory; further details will not be elaborated upon.

[0056] It should be noted that the geological parameters include soil permeability coefficient and gas saturation. In this embodiment of the invention, the values ​​of these two parameters within a certain range are combined to obtain multiple sets of results. Specifically, the soil permeability coefficient can be used as the horizontal axis and the gas saturation as the vertical axis. A dense and uniform grid is then used to select points in this two-dimensional coordinate system, with each grid point corresponding to a set of geological parameters. The range of soil permeability coefficient is typically from its maximum value under healthy conditions (e.g., 10^-6 m / s) to its minimum value under severely blocked conditions (e.g., 10^-9 m / s); the range of gas saturation is typically from 0% under no gas resistance conditions to 15% under severely blocked gas resistance conditions.

[0057] Preferably, in this embodiment of the invention, the theoretical response simulation model is based on Biot's consolidation theory, constructed using soil structure parameters, with the tidal water level sequence as the boundary condition, geological parameters as the input, and the theoretical surface elevation tidal response sequence as the output. The theoretical surface response characteristics are obtained based on the theoretical surface elevation tidal response sequence and the tidal water level sequence. The soil structure parameters include, for example, the thickness, stratification, and compression modulus and Poisson's ratio of each layer as specified in the geological survey report. It should be noted that the boundary conditions of the theoretical response simulation model should be the same as the tidal water level sequence collected in step S1 during this monitoring period, because the desired result is the theoretical response relative to these boundary conditions. Through the simulation of the theoretical response model, each set of geological parameters corresponds to a theoretical surface elevation tidal response sequence under the current tidal water level sequence, and thus corresponds to a theoretical surface response characteristic. The method for obtaining the theoretical surface response characteristics is the same as the method for obtaining the actual surface response characteristics, and will not be elaborated further.

[0058] After the above processing, the theoretical surface response characteristics corresponding to each set of geological parameters under the current tidal water level sequence are obtained. These theoretical surface response characteristics can then be used as a dataset to analyze the projection characteristics of the actual surface response characteristics onto the theoretical surface response characteristic set. This projection characteristic represents the idealized state point that theoretically best explains the actual observation conditions. Therefore, the geological parameters corresponding to the projection characteristics can be compared with healthy geological parameters to obtain the geological parameter deterioration index. The geological parameter deterioration index is the deterioration analysis result obtained from both physical and chemical dimensions during the theoretical analysis process. Furthermore, the deviation distance between the actual surface response characteristics and the projection characteristics is obtained. This deviation distance characterizes the gap between reality and theory. The larger the deviation distance, the more the real physical process deviates from the theoretical independent deterioration assumption, indicating that there may be complex interactions between physical blockage and biogas resistance at the corresponding location under the current observation period. For example, the distribution and migration of bubbles may be affected by the local water flow gradient caused by blockage. This interaction cannot be directly identified by traditional simulation models, therefore, adjustments and further optimization of the simulation model are required.

[0059] Preferably, in order to effectively compare the actual and theoretical states, the theoretical surface response features are mapped into multiple data points in a two-dimensional parameter space. The two dimensions of the two-dimensional parameter space are pressure conduction delay and pulsation amplitude, and the two-dimensional surface formed by the data points is the theoretical surface. By constructing the theoretical surface, the orthogonal physical relationships inherent in the construction of the theoretical surface can be utilized to decouple the physical and chemical degradation mechanisms through purely geometric positioning operations. The mapping point of the actual surface response features in the two-dimensional parameter space is taken as the actual point; the data point on the theoretical surface closest to the actual point is taken as the projection point of the actual point, and the pressure conduction delay and pulsation amplitude corresponding to the projection point are taken as the projection features.

[0060] It should be noted that the theoretical surface is the set of all surface responses that may be generated by the deterioration of the engineering site under idealized assumptions. The construction of the theoretical surface is a one-time computational input, and it can be reused for all subsequent analyses of the engineering site after completion.

[0061] Preferably, in this embodiment of the invention, the geological parameter deterioration index includes a siltation degree index and a gas resistance degree index;

[0062] The siltation index is obtained by the difference between the soil permeability coefficient in the projected features and the maximum soil permeability coefficient under healthy conditions. This index describes the deterioration that can be attributed to a simple decrease in soil permeability. The gas resistance index is obtained by the difference between the gas saturation in the projected features and the minimum gas saturation under healthy conditions. This index describes the deterioration that can be attributed to a simple increase in soil compressibility.

[0063] In this embodiment of the invention, the difference between the maximum soil permeability coefficient and the soil permeability coefficient in the projected features is obtained. This difference is used as the numerator, and the range between the maximum and minimum soil permeability coefficients is used as the denominator to obtain the siltation degree index. The difference between the gas saturation in the projected features and the minimum gas saturation under healthy conditions is obtained. This difference is used as the numerator, and the range between the maximum and minimum gas saturation is used as the denominator to obtain the air resistance degree index. That is, both the siltation degree index and the air resistance degree index in this embodiment of the invention are normalized results, with values ​​ranging from 0 to 1.

[0064] Furthermore, since the embodiments of the present invention construct a theoretical surface and transform the data features into a geometric space, the deviation distance is the distance between the actual point and the projected point in the two-dimensional parameter space.

[0065] Step S4: Construct an initial simulation model, calibrate the geological parameter simulation units of the initial simulation model according to the geological parameter deterioration index, calibrate the constitutive complexity of the initial simulation model according to the deviation distance, and obtain the calibrated optimized simulation model.

[0066] Based on the above steps, a set of characteristics, including the geological parameter deterioration index and deviation distance, is obtained for each location within a monitoring cycle. These characteristics can be used as physical constraints to dynamically calibrate a large-scale computer simulation model describing the consolidation process of soft soil foundations. Traditional simulation models use static, homogeneous parameters, which cannot reflect the real performance of the PVD system over time and with spatial differences. Therefore, by dynamically adjusting the traditional simulation model using these acquired characteristics, the parameters in the model can be adjusted according to the actual conditions of the engineering site, thereby outputting accurate and effective simulation results.

[0067] In this embodiment of the invention, the first step is to establish a finite element or finite difference simulation model based on Biot's consolidation theory, covering the entire engineering site. The spatial location of this initial simulation model corresponds to various locations within the engineering site, and its initial physical parameters can be preliminarily set based on the geological survey report. Specifically, the initial physical parameters are the two important geological parameters proposed in this embodiment: soil permeability coefficient and gas saturation. Furthermore, constitutive complexity is introduced into the initial physical parameters, using a coupling coefficient describing the sensitivity of permeability changes to stress changes as the initial constitutive relation complexity. The geological parameter simulation units of the initial simulation model can be calibrated according to the geological parameter deterioration index, and the constitutive relation complexity of the initial simulation model can be calibrated according to the deviation distance, i.e., dynamically correcting the initial physical parameters in the model to obtain the calibrated optimized simulation model.

[0068] Preferably, the geological parameter simulation unit of the initial simulation model calibrated according to the geological parameter deterioration index includes:

[0069] After negatively mapping and normalizing the siltation degree index, the soil permeability coefficient adjustment index is obtained. The initial soil permeability coefficient in the geological parameter simulation unit is multiplied by this adjustment index to obtain the adjusted soil permeability coefficient. That is, for the initial soil permeability coefficient, the lower the siltation degree, the more normal the actual geological condition of the current engineering site should be; the larger the soil permeability coefficient adjustment index, the larger the soil permeability coefficient should be. In other words, the soil permeability coefficient should have a negative correlation with the siltation degree index; a larger soil permeability coefficient in a healthy state corresponds to a smaller siltation degree index. In this embodiment, the soil permeability coefficient adjustment index (within the range of 0 to 1) is directly multiplied by the initial soil permeability coefficient to obtain the adjusted soil permeability coefficient. That is, the lower the siltation degree, the smaller the downward adjustment of the initial soil permeability coefficient. In the optimal case, the soil permeability coefficient adjustment index is 1, meaning the initial soil permeability coefficient does not need adjustment. This mapping relationship ensures that the dissipation rate of pore water pressure in the model is directly and uniquely controlled by the physical siltation degree.

[0070] After normalizing the air resistance index, it is added to a positive integer 1 to obtain the gas saturation adjustment index. The initial gas saturation in the geological parameter simulation unit is then multiplied by this adjustment index to obtain the adjusted gas saturation. Conversely to the above-described blockage analysis process, the air resistance index is positively correlated with gas saturation; that is, the minimum gas saturation corresponds to the healthy state, and a higher gas saturation indicates a greater air resistance. Therefore, in this embodiment of the invention, the air resistance index does not require negative correlation mapping; it is directly normalized and added to a positive integer 1 to obtain the gas saturation adjustment index. In other words, for the initial gas saturation, the adjustment process is a gain adjustment. This mapping adjustment ensures that the deformation of the soil under stress in the model is directly and uniquely controlled by the degree of biological air resistance.

[0071] It should be noted that, in this embodiment of the invention, the negative correlation mapping can be performed using the exponential function mapping method, where the opposite of the data is used as the power of an exponential function with the natural constant as the base, and the output of the exponential function is the negative correlation mapping result, with the mapping result value range between 0 and 1.

[0072] Preferably, in this embodiment of the invention, calibrating the constitutive complexity of the initial simulation model based on the deviation distance includes:

[0073] After normalizing the deviation distance, it is added to a positive integer 1 to obtain the complexity adjustment index. The initial constitutive relation complexity in the initial simulation model is then multiplied by this adjustment index to obtain the adjusted constitutive relation complexity of the initial simulation model. In other words, adjusting the constitutive relation complexity is also a form of gain adjustment; the gain is greater when the deviation distance is larger, enhancing the coupling in the constitutive relation. This mapping relationship fully utilizes the information contained in the deviation distance as a continuous variable, enabling the simulation model to smoothly transition and reflect the complexity of physical processes in different regions.

[0074] In this embodiment of the invention, an automated calculation loop is further used to synchronize the simulation model with physical reality, thereby continuously updating and correcting it. After acquiring data for a new monitoring cycle, the geological parameter deterioration index and deviation distance are obtained through the steps described above in this embodiment. These features are then used to adjust the simulation model. Using the adjusted and optimized simulation model, starting from the state of the previous monitoring cycle, the simulated total settlement and pore water pressure distribution for the current monitoring cycle are extrapolated. This loop continues as new observation data is acquired, ensuring synchronization between theory and reality in each monitoring cycle.

[0075] For predicting long-term soil deformation, the time series of three features—historical geological parameter deterioration index, deviation distance, and so on—can be used to predict future characteristics. After inputting these predicted features into a calibrated and optimized simulation model, the soil deformation curve and differential settlement distribution map for future timeframes can be obtained. For predicting the remaining working life of the PVD system, a functional failure threshold can be defined according to engineering specifications. For example, for any geological parameter deterioration index, when the index exceeds the warning value, based on the predicted data trend, the time when the functional failure threshold will be reached can be calculated. Finally, a full-field remaining working life prediction map can be generated, providing quantitative guidance for maintenance decisions and subsequent construction plans. Specifically, the prediction of the remaining working life of the PVD system is the application process of the optimized simulation model in this embodiment of the invention. The prediction method can be selected according to the actual application scenario, and will not be elaborated or limited further.

[0076] In summary, this invention determines the theoretical surface response characteristics corresponding to each set of geological parameters through a theoretical response simulation model, and then compares them with the actual surface response characteristics. By using intuitive data comparison, the geological parameter deterioration index between the actual and theoretical values ​​is determined, and the deviation distance is obtained. The deviation distance can be used to adjust the constitutive complexity of the initial simulation model, and the geological parameter simulation units of the simulation model can be adjusted using the geological parameter deterioration index. The model optimization of this invention enables the model to more accurately simulate the spatial distribution and temporal evolution of groundwater pressure fields and soil stress-strain fields, ensuring the accuracy of the simulation model output results.

[0077] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A computer-aided simulation method for groundwater level and soil deformation, characterized in that, The method includes: Obtain the surface elevation and tidal response sequences and tidal water level sequences at various locations within the PVD engineering site; The pressure transmission delay between the surface elevation tidal response sequence and the tidal water level sequence is obtained; the pulsation amplitude of the surface elevation tidal response sequence is obtained; and the pressure transmission delay and pulsation amplitude are used as the actual surface response characteristics at each location. Using soil permeability coefficient and gas saturation as geological parameters, a pre-trained theoretical response simulation model is used to obtain the theoretical surface response characteristics corresponding to each set of geological parameters. The theoretical response simulation model is based on Biot's consolidation theory, constructed using soil structure parameters, with the tidal water level sequence as the boundary condition. The input is the geological parameters, and the output is the theoretical surface elevation tidal response sequence. The theoretical surface response characteristics are obtained based on the theoretical surface elevation tidal response sequence and the tidal water level sequence. The projection characteristics of the actual surface response characteristics onto the theoretical surface response characteristic set are obtained. The geological parameters corresponding to the projection characteristics are compared with healthy geological parameters to obtain the geological parameter deterioration index. The deviation distance between the actual surface response characteristics and the projection characteristics is obtained. An initial simulation model is constructed. The geological parameter simulation units of the initial simulation model are calibrated according to the geological parameter deterioration index. The constitutive complexity of the initial simulation model is calibrated according to the deviation distance to obtain the calibrated optimized simulation model.

2. The computer-aided simulation method for groundwater level and soil deformation according to claim 1, characterized in that, The method for obtaining the surface elevation tidal response sequence includes: The surface elevation change sequence at each location is obtained, and the surface elevation change sequence is decomposed using a signal decomposition algorithm based on coefficient recovery theory to obtain the surface elevation tidal response sequence.

3. The computer-aided simulation method for groundwater level and soil deformation according to claim 1, characterized in that, The method for obtaining the pressure transmission delay includes: The cross-correlation function of the surface elevation tidal response sequence and the tidal water level sequence is obtained, and the time lag corresponding to the peak value of the cross-correlation function is used as the pressure transmission delay.

4. The computer-aided simulation method for groundwater level and soil deformation according to claim 1, characterized in that, The method for obtaining the pulsation amplitude includes: The average amplitude of the surface elevation tidal response sequence is obtained, and the average amplitude is normalized to obtain the pulsating amplitude.

5. The computer-aided simulation method for groundwater level and soil deformation according to claim 1, characterized in that, The method for obtaining the projection features includes: The theoretical surface response features are mapped into multiple data points in a two-dimensional parameter space, and the two-dimensional surface formed by the data points is the theoretical surface. The two dimensions of the two-dimensional parameter space are pressure transmission delay and pulsation amplitude. The mapping points of the actual surface response features in the two-dimensional parameter space are taken as actual points. The data point closest to the actual point on the theoretical surface is taken as the projection point of the actual point, and the pressure transmission delay and pulsation amplitude corresponding to the projection point are taken as the projection features.

6. The computer-aided simulation method for groundwater level and soil deformation according to claim 1, characterized in that, The methods for obtaining the geological parameter deterioration index include: The geological parameter deterioration index includes the siltation degree index and the air resistance degree index; The siltation index is obtained by the difference between the soil permeability coefficient in the projection feature and the maximum soil permeability coefficient under healthy conditions. The gas resistance index is obtained by the difference between the gas saturation in the projected features and the minimum gas saturation under healthy conditions.

7. The computer-aided simulation method for groundwater level and soil deformation according to claim 5, characterized in that, The deviation distance is the distance between the actual point and the projected point in the two-dimensional parameter space.

8. The computer-aided simulation method for groundwater level and soil deformation according to claim 6, characterized in that, The geological parameter simulation unit for calibrating the initial simulation model based on the geological parameter deterioration index includes: After mapping and normalizing the negative correlation of the siltation degree index, the soil permeability coefficient adjustment index is obtained. The initial soil permeability coefficient in the geological parameter simulation unit is multiplied by the soil permeability coefficient adjustment index to obtain the soil permeability coefficient after adjustment in the geological parameter simulation unit. After normalizing the gas resistance index, add it to the positive integer 1 to obtain the gas saturation adjustment index. Multiply the initial gas saturation in the geological parameter simulation unit by the gas saturation adjustment index to obtain the adjusted gas saturation in the geological parameter simulation unit.

9. The computer-aided simulation method for groundwater level and soil deformation according to claim 1, characterized in that, The step of calibrating the constitutive complexity of the initial simulation model based on the deviation distance includes: After normalizing the deviation distance, add it to the positive integer 1 to obtain the complexity adjustment index. Multiply the initial constitutive relation complexity in the initial simulation model by the complexity adjustment index to obtain the adjusted constitutive relation complexity of the initial simulation model.

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