Composite pavement structure design system for soft soil treatment

Abstract

The invention relates to the technical field of civil engineering, soft soil mechanics and intelligent design, in particular to a soft soil treatment composite pavement structure design system, which comprises a data acquisition and reference reconstruction module, an ideal stress tensor field and an ideal elastic strain field which are used as reference data; the rheological characteristic calculation module is used for mapping the ideal stress tensor field into a theoretical rheological deviation tensor containing time correlation; the double-track differential verification module is used for resolving a spatial topology coherence coefficient and generating a rheological risk prompt signal or a risk elimination signal; the self-adaptive iteration correction module is used for generating a corrected structural layer design modulus and feeding back the corrected structural layer design modulus to the data acquisition and reference reconstruction module to trigger a new round of calculation; according to the method, accurate separation and quantitative diagnosis of harmful settlement caused by soft soil rheology are realized, and the technical problem that instantaneous settlement and rheological settlement cannot be quantitatively stripped in a traditional design is effectively solved.

Description

Technical Field

[0001] This invention relates to the fields of civil engineering, soft soil mechanics and intelligent design technology, specifically a composite pavement structure design system for soft soil treatment. Background Technology

[0002] In the current design and analysis environment of soft soil subgrade pavement engineering, the pavement structure is under the complex coupling effect of all environmental factors such as vehicle axle load, temperature field and pore water pressure for a long time, and the underlying soft soil layer has significant rheological characteristics that develop over time. For pavement structure design and settlement control, existing solutions generally adopt a design evaluation model that focuses on total settlement. This involves directly calculating the stress deformation of pavement materials and the consolidation settlement of the foundation using a combination of commercial finite element software or empirical formulas. While this approach has a certain macroscopic quantitative capability in conventional evaluations, it lacks a decoupling mechanism for the physical sources of deformation. It cannot quantitatively separate the elastic compression determined by the stiffness of the pavement material itself from the harmful settlement caused by the rheological mechanism of soft soil. This makes it difficult to accurately identify the pathological attributes of settlement during the design process, easily leading to over-design and wasted resources due to confusion between instantaneous settlement and rheological characteristics, or to missed safety hazards due to failure to identify hidden rheological risks. Therefore, it is necessary to establish a physical model to accurately decouple the total settlement of the pavement structure into non-time-dependent instantaneous settlement and time-dependent rheological settlement. Thus, how to construct an absolutely rigid reference system under complex environmental loads to achieve accurate separation and quantitative diagnosis of harmful settlement caused by soft soil rheology, and to automatically correct the structural layer modulus accordingly, has become an urgent technical problem to be solved. Summary of the Invention

[0003] To solve the above-mentioned technical problems, the present invention provides a composite pavement structure design system for soft soil treatment. Specifically, the technical solution of the present invention includes: The data acquisition and benchmark reconstruction module is used to acquire geological survey data and proposed pavement structure schemes for pavement engineering, establish a finite element mesh model based on the proposed pavement structure scheme, and perform elastic field calculations on the finite element mesh model while ignoring the influence of the time dimension, generating an ideal stress tensor field and an ideal elastic strain field as benchmark data. The rheological characteristic calculation module is used to map the ideal stress tensor field into a theoretical rheological deviation tensor containing time correlation based on the viscoelastic relationship defined by the Burger rheological model. The theoretical rheological deviation tensor characterizes the hypothetical deformation distribution caused only by the rheological mechanism of soft soil. The dual-track differential verification module is used to obtain the full strain field considering the influence of all environmental factors. It obtains the actual deviation tensor by calculating the difference between the full strain field and the ideal elastic strain field, and performs spatial geometric similarity analysis on the actual deviation tensor and the theoretical rheological deviation tensor to calculate the spatial topological coherence coefficient. Based on the spatial topological coherence coefficient, it generates rheological risk warning signals or risk elimination signals. The adaptive iterative correction module, in response to the rheological risk warning signal, calculates the correction magnitude of the structural layer modulus based on the spatial topological coherence coefficient, generates the corrected structural layer design modulus, and feeds it back to the data acquisition and benchmark reconstruction module to trigger a new round of calculation.

[0004] Preferably, the specific process for performing elastic field calculations on a finite element mesh model while ignoring the influence of the time dimension includes: A virtual transient equilibrium calculation environment is constructed, in which the permeability coefficient parameter of the soft soil layer is forcibly set to zero to eliminate the consolidation effect, and the constitutive model of the pavement material is locked as an isotropic linear elastic model. Using the generalized Hooke's law, the resilient modulus and Poisson's ratio from the geological survey data are taken as constant inputs. For each node of the finite element mesh model, the Cauchy stress tensor without time variables is calculated as the ideal stress tensor field, and the transient elastic strain tensor directly caused by the external load is calculated as the ideal elastic strain field.

[0005] Preferably, the rheological characteristic calculation module performs the following processing steps: Triaxial creep test data of soft soil layers were extracted from geological survey data. Curve fitting was performed on the triaxial creep test data to extract the Maxwell volume viscosity coefficient, Kelvin volume elastic modulus and Kelvin volume viscosity coefficient required for the Burger model. A creep compliance function under unit stress is constructed. The value of this function consists of two parts: the first part is the permanent settlement term that increases linearly with time based on the Maxwell volume viscosity coefficient, and the second part is the delayed rebound term that decreases exponentially with time based on the Kelvin volume parameters. Based on the principle of viscoelastic correspondence, the deviatoric stress components in the ideal stress tensor field are multiplied with the calculated value of the creep compliance function to generate the theoretical rheological deviation tensor.

[0006] Preferably, the specific generation logic of the theoretical rheological deviation tensor is as follows: For each node in the ideal stress tensor field, the hydrostatic pressure value is calculated and subtracted from the original stress tensor to obtain the ideal deviatoric stress tensor that only drives the shape change. Obtain the current design reference period time value, substitute it into the creep compliance function to calculate the current compliance scalar value; Multiplying each component of the ideal deviatoric stress tensor by the compliance scalar value and the preset coefficients yields the theoretical rheological deviation tensor at that node.

[0007] Preferably, the process of calculating the spatial topological homology coefficients by the dual-track differential verification module includes: Perform the first difference operation: subtract the strain value of the corresponding node in the ideal elastic strain field from the strain value of each node in the full strain field to obtain the reality deviation tensor characterizing the nonlinear environmental disturbance and rheological mixing features; Perform the second cohomology operation: traverse all grid nodes, calculate the tensor double dot product of the actual deviation tensor and the theoretical rheological deviation tensor at each node, and sum the calculation results of all nodes to obtain the morphological overlap value; Perform normalization operation: Calculate the sum of squares of the deformation energy intensity of the actual deviation tensor and the theoretical rheological deviation tensor at all nodes in the global space, respectively, perform square root operation on the two sums of squares, and finally multiply the two square root values ​​as the normalization base. Dividing the morphological overlap value by the normalized base, the quotient is the spatial topological coherence coefficient. This coefficient is used to quantify the similarity in spatial distribution between real-world deformation patterns and theoretical soft soil rheological patterns.

[0008] The preferred method for calculating deformation energy intensity is: Get all component elements of the corresponding tensor at a specific node; Squaring each component element and then summing them; The square root of the summation result is taken to obtain the Frobenius norm at the node, which is used as the deformation energy intensity at the node.

[0009] Preferably, the logic for generating rheological risk warning signals or risk exclusion signals based on spatial topological coherence coefficients is as follows: A preset cohomology threshold is used to determine rheological dominance; Compare the calculated spatial topological homology coefficients with the homology threshold. If the spatial topological coherence coefficient is greater than the coherence threshold, it is determined that the settlement in the current design scheme is mainly caused by soft soil rheology, and a rheological risk warning signal is output. If the spatial topological coherence coefficient is less than or equal to the coherence threshold, the deformation mode is determined to be mismatched, and a risk elimination signal is output.

[0010] Preferably, the process by which the adaptive iterative correction module calculates the corrected structural layer design modulus includes: Obtain the preset feedback gain coefficient and the ultimate tensile strain modulus value specified in the pavement design code; Calculate the deformation magnitude ratio: Calculate the global strength norm of the actual deviation tensor in the entire domain and divide it by the ultimate tensile strain modulus; Calculate the stiffness compensation factor: multiply the deformation magnitude ratio, spatial topological coherence coefficient, and feedback gain coefficient, and add the product to the numerical value. Calculate the new modulus: Multiply the original elastic modulus in the proposed pavement structure scheme by the stiffness compensation factor to obtain the corrected structural layer design modulus.

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. This system constructs an ideal elastic field that ignores the time dimension as an absolutely rigid reference system and uses a dual-track differential mechanism to successfully separate the pure instantaneous settlement in the full strain field that considers the influence of all environmental factors. For the first time, it has achieved accurate separation and quantitative diagnosis of harmful settlement caused by soft soil rheology, effectively solving the technical problem that traditional design cannot quantitatively separate the two types of settlement. 2. This system uses tensor double dot product and Frobenius norm normalization to calculate spatial topological homology coefficients, which are essentially cosine similarities between high-dimensional tensor fields. This enables the system to compare not only the magnitude of deformation, but also the shape and pattern of deformation. Even if the settlement is very small, as long as its spatial distribution pattern is highly consistent with the theoretical rheological pattern, the system can still keenly detect rheological risks and avoid missing safety hazards. 3. When the system determines that there is a rheological risk, it can automatically respond to the rheological risk warning signal. Based on the spatial topological coherence coefficient and the deformation magnitude ratio, the system calculates the correction range of the structural layer modulus by introducing a stiffness compensation factor. This correction algorithm has a high degree of targeting, realizes reinforcement on demand, and avoids waste caused by over-design or blindly increasing the amount of material due to confusion between elastic compression and rheological settlement. 4. This system transforms complex tensor analysis results into binary risk signals, which can directly drive subsequent automated correction processes, greatly improving the automation level of the design; by transforming rheological laws into vector features with spatial directionality and strictly quantifying the similarity of deformation modes, it ensures the scientific nature of pavement design and the long-term operational safety of the project. Attached Figure Description

[0012] The present invention will be further explained below with reference to the accompanying drawings and embodiments: Figure 1 This is a structural diagram of the system of the present invention. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0014] Example 1: Please see Figure 1 A composite pavement structure design system for soft soil treatment, comprising: The data acquisition and benchmark reconstruction module is used to acquire geological survey data and proposed pavement structure schemes for road engineering. Based on the proposed pavement structure scheme, a finite element mesh model is established, and elastic field calculations are performed on the finite element mesh model, ignoring the influence of the time dimension, to generate an ideal stress tensor field and an ideal elastic strain field as benchmark data. That is, the instantaneous settlement is calculated through the ideal elastic strain field. Rheological settlement is calculated using the rheological deviation tensor obtained from the rheological characteristic calculation module. This achieves control over the total settlement. Precise separation; The rheological characteristic calculation module is used to map the ideal stress tensor field into a theoretical rheological deviation tensor containing time correlation based on the viscoelastic relationship defined by the Burger rheological model. The theoretical rheological deviation tensor characterizes the hypothetical deformation distribution caused only by the rheological mechanism of soft soil. The dual-track differential verification module is used to obtain the full strain field considering the influence of all environmental factors. It obtains the actual deviation tensor by calculating the difference between the full strain field and the ideal elastic strain field, and performs spatial geometric similarity analysis on the actual deviation tensor and the theoretical rheological deviation tensor to calculate the spatial topological coherence coefficient. Based on the spatial topological coherence coefficient, it generates rheological risk warning signals or risk elimination signals. The adaptive iterative correction module, in response to the rheological risk warning signal, calculates the correction magnitude of the structural layer modulus based on the spatial topological coherence coefficient, generates the corrected structural layer design modulus, and feeds it back to the data acquisition and benchmark reconstruction module to trigger a new round of calculation.

[0015] This embodiment provides a composite pavement structure design system for soft soil treatment; the system aims to solve the technical problem in traditional design that it is impossible to quantitatively separate the harmful settlement caused by soft soil rheology from the elastic compression of the pavement material itself; Data acquisition and benchmark reconstruction module: The main function of this module is to establish a physically absolute rigid reference system. In this embodiment, the system acquires geological survey data of the road engineering, including soil parameters, groundwater level, and proposed road structure scheme. Subsequently, a finite element mesh model is established based on the proposed road structure scheme, and elastic field calculation is performed on the model ignoring the influence of the time dimension. The purpose of this calculation is to generate an ideal stress tensor field, denoted as the baseline data. And the ideal elastic strain field, denoted as The ideal here refers to a physical state in which all viscous effects and plastic damage that develop over time are eliminated, and only the intrinsic stiffness of the material is retained, in a hypothetical transient equilibrium environment. Rheological Feature Calculation Module: This module projects the rheological laws over time onto the stress distribution in space. Based on the viscoelastic relationship defined by the Burger rheological model, it maps the aforementioned ideal stress tensor field into a theoretical rheological deviation tensor that includes time dependence, denoted as... ; Theoretical rheological deviation tensor It is a specially constructed fault model that characterizes the deformation distribution pattern that should be presented under the current stress level, assuming that the deformation is caused entirely by the rheological mechanism of soft soil. Dual-track differential verification module: This module is the core decision unit of this system; it acquires the full strain field, denoted as... The full strain field is a real deformation field calculated by commercial finite element software, taking into account all environmental factors, such as vehicle axle load, temperature field, pore water pressure, etc. The actual deviation tensor is obtained by calculating the difference between the total strain field and the ideal elastic strain field, denoted as . This tensor strips away pure instantaneous settling; Module for Reality Deviation Tensor With respect to theoretical rheological deviation tensor Perform spatial geometric similarity analysis to calculate the spatial topological homology coefficient, denoted as . Based on this coefficient, the system automatically generates a rheological risk warning signal or a risk elimination signal. Adaptive Iterative Correction Module: This module is used to achieve automated optimization of the design. In response to the rheological risk warning signal, it calculates the correction magnitude of the structural layer modulus based on the spatial topological coherence coefficient, generates the corrected structural layer design modulus and feeds it back to the data acquisition and benchmark reconstruction module, thereby triggering a new round of benchmark reconstruction and verification until the risk signal is eliminated or the maximum number of iterations preset by the system is reached. This embodiment successfully achieves pathological diagnosis of pavement settlement properties by constructing an ideal elastic field as an absolute reference system and utilizing a dual-track differential mechanism. Compared with traditional design methods that only focus on total settlement, this system can accurately identify risks caused by soft soil rheology, avoiding over-design or missed safety hazards caused by confusing elastic compression with rheological settlement.

[0016] Example 2: The specific process of performing elastic field calculations on a finite element mesh model while ignoring the effects of the time dimension includes: A virtual transient equilibrium calculation environment is constructed, in which the permeability coefficient parameter of the soft soil layer is forcibly set to zero to eliminate the consolidation effect, and the constitutive model of the pavement material is locked as an isotropic linear elastic model. Using the generalized Hooke's law, the resilient modulus and Poisson's ratio from the geological survey data are taken as constant inputs. For each node of the finite element mesh model, the Cauchy stress tensor without time variables is calculated as the ideal stress tensor field, and the transient elastic strain tensor directly caused by the external load is calculated as the ideal elastic strain field.

[0017] This embodiment is a specific implementation of the elastic field calculation process performed by the data acquisition and benchmark reconstruction module in Embodiment 1; To construct clean baseline data, this embodiment employs the following steps to perform elastic field calculations that ignore the influence of the time dimension: Constructing a Virtual Transient Equilibrium Calculation Environment: The system constructs a physically non-existent but mathematically rigorous virtual environment within the finite element solver; within this environment, the system performs two key mandatory settings: Eliminating consolidation effects: The permeability coefficient parameter of the soft soil layer... Forced to be set to zero, This operation mathematically cuts off the dissipation path of pore water pressure, thus completely eliminating the consolidation settlement that occurs over time in the calculation. Eliminating plastic damage: The constitutive model of the pavement material is locked as an isotropic linear elastic model, rather than the complex elastoplastic model used in actual engineering. Field quantity calculation based on generalized Hooke's law: The system uses generalized Hooke's law as the governing equation; the input material parameters are limited to the resilient modulus from geological survey data. Compared with Poisson These two parameters are considered constants that do not change over time in this step; For each node of the finite element mesh model, the system calculates the Cauchy stress tensor, which is independent of time variables, as the ideal stress tensor field. And calculate the transient elastic strain tensor directly caused by external loads, such as standard axle loads, as the ideal elastic strain field. ; By forcibly setting the permeability coefficient to zero and locking the linear elastic model, this embodiment successfully constructed a zero-interference background plate; this reference field completely eliminates all nonlinear and time-dependent factors, providing a unique mathematical zero point for subsequent precise extraction of pure rheological features through differential operations.

[0018] Example 3: The rheological characteristic calculation module performs the following processing steps: Triaxial creep test data of soft soil layers were extracted from geological survey data. Curve fitting was performed on the triaxial creep test data to extract the Maxwell volume viscosity coefficient, Kelvin volume elastic modulus and Kelvin volume viscosity coefficient required for the Burger model. A creep compliance function under unit stress is constructed. The value of this function consists of two parts: the first part is the permanent settlement term that increases linearly with time based on the Maxwell volume viscosity coefficient, and the second part is the delayed rebound term that decreases exponentially with time based on the Kelvin volume parameters. Based on the principle of viscoelastic correspondence, the deviatoric stress components in the ideal stress tensor field are multiplied with the calculated value of the creep compliance function to generate the theoretical rheological deviation tensor. The specific generation logic of the theoretical rheological deviation tensor is as follows: For each node in the ideal stress tensor field, the hydrostatic pressure value is calculated and subtracted from the original stress tensor to obtain the ideal deviatoric stress tensor that only drives the shape change. Obtain the current design reference period time value, substitute it into the creep compliance function to calculate the current compliance scalar value; Multiplying each component of the ideal deviatoric stress tensor by the compliance scalar value and the preset coefficients yields the theoretical rheological deviation tensor at that node.

[0019] This embodiment is a concretization of the rheological feature calculation module in Embodiment 1, and details how to generate the theoretical rheological deviation tensor based on the Burger model; The process consists of the following three core steps: The system extracts triaxial creep test data of soft soil layers from geological survey data; by performing nonlinear curve fitting on the test data, specifically using the Levenberg-Marquardt nonlinear least squares algorithm, with the objective function of minimizing the mean square error between the test data points and the model calculation values, iteratively solves the problem to extract the three key rheological parameters required by the Burger model: Maxwell viscosity coefficient : Determines the permanent settlement rate; Kelvin's bulk modulus : Determines the stiffness of the delayed elasticity; Kelvin's volume viscosity coefficient : Determines the rate of delayed rebound; To describe the material's ability to flow over time, this embodiment constructs a creep compliance function. It should be noted that the creep compliance function constructed in this embodiment... The Maxwell spring term (1 / EM) representing instantaneous elasticity in the Burger model was deliberately removed because the instantaneous elastic deformation of the road material has already been calculated using an ideal elastic field in the data acquisition and benchmark reconstruction module. Removing this term here is to avoid duplicate inclusion of the elastic component during superposition calculations. Its calculation formula is as follows:

[0020] in, : This is the current design reference period time value, in seconds, given by the design specifications; The value of this function consists of two parts: the first part It is the permanent settlement term that increases linearly with time, determined based on Maxwell's volume viscosity coefficient; Part Two It is a delayed rebound term that decays exponentially over time, determined based on Kelvin volume parameters; The system is based on the principle of viscoelastic correspondence, mapping the compliance properties of the time dimension to a spatial tensor. The specific generation logic is as follows: Step A: Calculate the ideal deviatoric stress tensor; for the ideal stress tensor field For each node in the calculation, calculate its hydrostatic pressure value. Subtracting this from the original stress tensor yields the ideal deviatoric stress tensor that only drives shape change. :

[0021] in, For the ideal stress tensor, This is the hydrostatic pressure value. For Kroneck symbol, when The value is 1 if the condition is met, and 0 otherwise. Step B: Calculate the compliance scalar value; obtain the time value of the current design reference period. Substituting the above The formula calculates the current scalar value of the flexibility. Step C: Tensor product operation; multiply each component of the ideal deviatoric stress tensor by the compliance scalar value and a preset coefficient. Based on viscoelasticity, the coefficient is usually taken as... The coefficient The selection criteria are based on von Mises' flow law and the assumption of volume incompressibility; since the aforementioned triaxial creep test measures the axial creep compliance. In a three-dimensional tensor field, the shear creep compliance drives shape changes. Assuming that the volume of soft soil remains constant during pure creep, i.e., Poisson's ratio. If the value approaches 0.5, then there is a relationship between shear compliance and axial compliance. The relationship between the deviatoric stress tensor and the shear stress tensor is also related in the definition of tensors. Based on the above physical relationships, the conversion factor is set as follows: This allows for the accurate mapping of one-dimensional experimental data into three-dimensional shear deformation characteristics; the resulting value is the theoretical rheological deviation tensor at that node. :

[0022] This embodiment creatively transforms the one-dimensional burger rheological properties into a three-dimensional tensor field. This processing transforms rheology from a scalar value into a vector feature with spatial directionality. This enables the system to compare not only the magnitude of the deformation but also its shape and pattern, thereby greatly improving the accuracy of recognition.

[0023] Example 4: The process of calculating the spatial topological homology coefficients by the dual-track differential verification module includes: Perform the first difference operation: subtract the strain value of the corresponding node in the ideal elastic strain field from the strain value of each node in the full strain field to obtain the reality deviation tensor characterizing the nonlinear environmental disturbance and rheological mixing features; Perform the second cohomology operation: traverse all grid nodes, calculate the tensor double dot product of the actual deviation tensor and the theoretical rheological deviation tensor at each node, and sum the calculation results of all nodes to obtain the morphological overlap value; Perform normalization operation: Calculate the sum of squares of the deformation energy intensity of the actual deviation tensor and the theoretical rheological deviation tensor at all nodes in the global space, respectively. Perform square root operation on the two sums of squares, and finally multiply the two square root values ​​as the normalization base. This calculation logic follows the denominator construction form of the Cauchy-Schwarz inequality to ensure that the final coefficients are strictly distributed in the interval [-1,1]. Dividing the morphological overlap value by the normalized base, the quotient is the spatial topological coherence coefficient, which is used to quantify the similarity in spatial distribution between the deformation patterns in reality and the theoretical soft soil rheological patterns. The method for calculating deformation energy intensity is as follows: Get all component elements of the corresponding tensor at a specific node; Squaring each component element and then summing them; The square root of the summation result is taken to obtain the Frobenius norm at the node, which is used as the deformation energy intensity at the node.

[0024] This embodiment details the process of calculating the spatial topological homology coefficients by the dual-track differential verification module, as well as the method for calculating the deformation energy intensity involved therein; Spatial topological homology coefficients This is the core indicator of the present invention used to quantify the spatial similarity between real-world deformation patterns and theoretical soft soil rheological patterns; its calculation process includes: Before performing the differential calculation, it is necessary to ensure the data isomorphism between the full strain field and the ideal elastic strain field. Specifically, when commercial finite element software calculates the full strain field, it is essential to import a finite element mesh topology file that is completely identical to that in the data acquisition and benchmark reconstruction module, containing the same node numbers and element connection relationships. For loading all environmental elements, the specific execution method is as follows: the temperature field data obtained from geological surveys is mapped to the steady-state thermal load of each node, and the pore water pressure field data is mapped to the effective stress reduction factor or nodal permeability of each element. The system will then load the full strain field containing all environmental elements. The strain values ​​at each node, minus the ideal elastic strain field. The strain values ​​at the corresponding nodes are used to obtain the actual deviation tensor. :

[0025] This tensor It characterizes the actual inelastic deformation that combines nonlinear environmental disturbances with potential rheological features; For comparison With respect to theoretical rheological deviation tensor Geometric similarity, the system traverses all mesh nodes, let the total number of nodes be . Calculate the tensor double dot product of the two at each node, and sum the calculation results of all nodes to obtain the morphological overlap value. The calculation formula is as follows:

[0026] The symbol : represents the tensor double dot product operation, that is, the summation of corresponding components; To eliminate the influence of the absolute magnitude of deformation and focus only on the spatial distribution pattern, the system calculates separately. and Deformation energy intensity across the entire spatial domain; The deformation energy intensity is calculated using the Frobenius norm; for a tensor at a specific node, the system obtains all its component elements, squares each component element, sums them, and then takes the square root of the sum.

[0027] The system multiplies the global deformation energy intensity values ​​of the two and sums them up as the normalization base. Dividing the morphological overlap value by the normalized base, the quotient is the spatial topological coherence coefficient. ; By introducing tensor double dot product and Frobenius norm normalization, the homology coefficients calculated in this embodiment Essentially, it is the cosine similarity between two high-dimensional tensor fields; this means that even if the actual settlement is very small, as long as its spatial distribution pattern, such as the orientation of the shear zone, is highly consistent with the theoretical rheological pattern, the system can still keenly detect the risk; conversely, if it is simply large-area compaction settlement, the system can also correctly eliminate the rheological risk.

[0028] Example 5: The logic for generating rheological risk warning signals or risk exclusion signals based on spatial topological coherence coefficients is as follows: A preset cohomology threshold is used to determine rheological dominance; Compare the calculated spatial topological homology coefficients with the homology threshold. If the spatial topological coherence coefficient is greater than the coherence threshold, it is determined that the settlement in the current design scheme is mainly caused by soft soil rheology, and a rheological risk warning signal is output. If the spatial topological coherence coefficient is less than or equal to the coherence threshold, the deformation mode is determined to be mismatched, and a risk elimination signal is output.

[0029] This embodiment describes the application of spatial topological homology coefficients. The specific logic for generating the signal; To achieve automated decision-making, the system presets a cohomology threshold for determining rheological dominance. In this embodiment, the value is preferably set to 0.85, which is determined based on the statistical significance of historical engineering big data. The specific statistical determination steps are as follows: collect historical settlement monitoring data and corresponding design models of no less than 50 completed soft soil pavement projects; mark samples whose actual long-term differential settlement exceeds the allowable value of the specification by 20% as rheological failures, and mark the rest as non-rheological failures; and use this system to backtrack and calculate the spatial topological coherence coefficient of all samples. ; Traverse the threshold in the interval [0,1] with a step size of 0.05, and calculate the classification F1 score under different thresholds; Select the value corresponding to the maximum F1 score. The value is used as the baseline coherence threshold for this system, and in the dataset of this embodiment, this value is 0.85; The system will calculate and Perform a comparison; like This illustrates the reality bias tensor. Principal components and rheological characteristics of soft soil Highly isomorphic; the system determines that the settlement in the current design scheme is mainly caused by soft soil rheology and outputs a rheological risk warning signal. like This indicates that the deformation modes of the two are mismatched, for example, the deformation is mainly caused by packing compaction or numerical oscillation; the system determines that there is no significant rheologically dominant risk and outputs a risk elimination signal; This logic transforms complex tensor analysis results into simple binary signals, enabling the system to directly drive subsequent automated correction processes without manual intervention.

[0030] Example 6: The process by which the adaptive iterative correction module calculates the corrected structural layer design modulus includes: Obtain the preset feedback gain coefficient and the ultimate tensile strain modulus value specified in the pavement design code; Calculate the deformation magnitude ratio: Calculate the global strength norm of the actual deviation tensor in the entire domain and divide it by the ultimate tensile strain modulus; Calculate the stiffness compensation factor: multiply the deformation magnitude ratio, spatial topological coherence coefficient, and feedback gain coefficient, and add the product to the numerical value. Calculate the new modulus: Multiply the original elastic modulus in the proposed pavement structure scheme by the stiffness compensation factor to obtain the corrected structural layer design modulus.

[0031] This embodiment is a specific implementation of the adaptive iterative correction module in claim 1, and details how to quantitatively calculate the corrected structural layer design modulus after receiving a rheological risk warning signal. This correction process incorporates the concept of proportional control from automatic control theory. The calculation steps are as follows: The system obtains the preset feedback gain coefficient. In this embodiment, the value is set to 1.5 to control the convergence speed. This coefficient is determined based on a variant of the Ziegler-Nichols tuning method: In the simulation environment, the initial settings are... =0, gradually increase Until numerical oscillations occur in the calculated structural layer modulus after correction, the critical oscillation gain Ku is recorded; take =0.45Ku was used as the working gain to ensure that the closed-loop correction process reaches a steady state without overshoot within 3-5 iterations; under the typical soft soil condition in this embodiment, after calibration... The value is set to 1.5; and the ultimate tensile strain modulus value specified in the pavement design code is obtained. ; Calculate the deformation magnitude ratio: Calculate the global strength norm of the actual deviation tensor across the entire domain. Divide by the ultimate tensile strain modulus The global intensity norm over the entire domain is defined as follows: ; The system calculates the actual deviation tensor. Global intensity norm within the entire domain The formula for calculating the global strength norm is as follows: obtain the Frobenius norm of the actual deviation tensor of all grid nodes in the global domain, sum the squares of the norms of all nodes, and take the square root of the summation result, i.e., the global L2 norm, and divide it by the ultimate tensile strain modulus value to obtain the deformation magnitude ratio; this ratio reflects the severity of the current risk deformation relative to the allowable value of the specification. To comprehensively consider both the pattern similarity and deformation severity of the risks, a stiffness compensation factor is systematically constructed. The calculation formula is as follows:

[0032] in, These are the spatial topological homology coefficients calculated in the preceding steps; The system will determine the original elastic modulus in the proposed pavement structure scheme. Multiply by stiffness compensation factor The corrected structural layer design modulus was obtained. :

[0033] The correction algorithm in this embodiment is highly targeted; the stiffness compensation factor depends not only on the magnitude of the deformation but also on the rheological risk confidence level. The weighted adjustment means that the more obvious the rheological characteristics or the more severe the deformation, the greater the reinforcement of the system, thus achieving reinforcement on demand, which ensures safety and avoids the waste caused by blindly increasing the amount of material used.

[0034] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A composite pavement structure design system for soft soil treatment, characterized in that, include: The data acquisition and benchmark reconstruction module is used to acquire geological survey data and proposed pavement structure schemes for pavement engineering, establish a finite element mesh model based on the proposed pavement structure scheme, and perform elastic field calculations on the finite element mesh model while ignoring the influence of the time dimension, generating an ideal stress tensor field and an ideal elastic strain field as benchmark data. The rheological characteristic calculation module is used to map the ideal stress tensor field into a theoretical rheological deviation tensor containing time correlation based on the viscoelastic relationship defined by the Burger rheological model. The theoretical rheological deviation tensor characterizes the hypothetical deformation distribution caused only by the rheological mechanism of soft soil. The dual-track differential verification module is used to obtain the full strain field considering the influence of all environmental factors. It obtains the actual deviation tensor by calculating the difference between the full strain field and the ideal elastic strain field, and performs spatial geometric similarity analysis on the actual deviation tensor and the theoretical rheological deviation tensor to calculate the spatial topological coherence coefficient. Based on the spatial topological coherence coefficient, it generates rheological risk warning signals or risk elimination signals. The adaptive iterative correction module, in response to the rheological risk warning signal, calculates the correction magnitude of the structural layer modulus based on the spatial topological coherence coefficient, generates the corrected structural layer design modulus, and feeds it back to the data acquisition and benchmark reconstruction module to trigger a new round of calculation.

2. The soft soil treatment composite pavement structure design system according to claim 1, characterized in that, The specific process of performing elastic field calculations on a finite element mesh model while ignoring the effects of the time dimension includes: A virtual transient equilibrium calculation environment is constructed, in which the permeability coefficient parameter of the soft soil layer is forcibly set to zero to eliminate the consolidation effect, and the constitutive model of the pavement material is locked as an isotropic linear elastic model. Using the generalized Hooke's law, the resilient modulus and Poisson's ratio from the geological survey data are taken as constant inputs. For each node of the finite element mesh model, the Cauchy stress tensor without time variables is calculated as the ideal stress tensor field, and the transient elastic strain tensor directly caused by the external load is calculated as the ideal elastic strain field.

3. The soft soil treatment composite pavement structure design system according to claim 1, characterized in that, The rheological characteristic calculation module performs the following processing steps: Triaxial creep test data of soft soil layers were extracted from geological survey data. Curve fitting was performed on the triaxial creep test data to extract the Maxwell volume viscosity coefficient, Kelvin volume elastic modulus and Kelvin volume viscosity coefficient required for the Burger model. A creep compliance function under unit stress is constructed. The value of this function consists of two parts: the first part is the permanent settlement term that increases linearly with time based on the Maxwell volume viscosity coefficient, and the second part is the delayed rebound term that decreases exponentially with time based on the Kelvin volume parameters. Based on the principle of viscoelastic correspondence, the deviatoric stress components in the ideal stress tensor field are multiplied with the calculated value of the creep compliance function to generate the theoretical rheological deviation tensor.

4. The soft soil treatment composite pavement structure design system according to claim 3, characterized in that, The specific generation logic of the theoretical rheological deviation tensor is as follows: For each node in the ideal stress tensor field, the hydrostatic pressure value is calculated and subtracted from the original stress tensor to obtain the ideal deviatoric stress tensor that only drives the shape change. Obtain the current design reference period time value, substitute it into the creep compliance function to calculate the current compliance scalar value; Multiplying each component of the ideal deviatoric stress tensor by the compliance scalar value and the preset coefficients yields the theoretical rheological deviation tensor at that node.

5. The soft soil treatment composite pavement structure design system according to claim 1, characterized in that, The process of calculating the spatial topological homology coefficients by the dual-track differential verification module includes: Perform the first difference operation: subtract the strain value of the corresponding node in the ideal elastic strain field from the strain value of each node in the full strain field to obtain the reality deviation tensor characterizing the nonlinear environmental disturbance and rheological mixing features; Perform the second cohomology operation: traverse all grid nodes, calculate the tensor double dot product of the actual deviation tensor and the theoretical rheological deviation tensor at each node, and sum the calculation results of all nodes to obtain the morphological overlap value; Perform normalization operation: Calculate the sum of squares of the deformation energy intensity of the actual deviation tensor and the theoretical rheological deviation tensor at all nodes in the global space, respectively, perform square root operation on the two sums of squares, and finally multiply the two square root values ​​as the normalization base. Dividing the morphological overlap value by the normalized base, the quotient is the spatial topological coherence coefficient. This coefficient is used to quantify the similarity in spatial distribution between real-world deformation patterns and theoretical soft soil rheological patterns.

6. The soft soil treatment composite pavement structure design system according to claim 5, characterized in that, The method for calculating deformation energy intensity is as follows: Get all component elements of the corresponding tensor at a specific node; Squaring each component element and then summing them; The square root of the summation result is taken to obtain the Frobenius norm at the node, which is used as the deformation energy intensity at the node.

7. The soft soil treatment composite pavement structure design system according to claim 5, characterized in that, The logic for generating rheological risk warning signals or risk exclusion signals based on spatial topological coherence coefficients is as follows: A preset cohomology threshold is used to determine rheological dominance; Compare the calculated spatial topological homology coefficients with the homology threshold. If the spatial topological coherence coefficient is greater than the coherence threshold, it is determined that the settlement in the current design scheme is mainly caused by soft soil rheology, and a rheological risk warning signal is output. If the spatial topological coherence coefficient is less than or equal to the coherence threshold, the deformation mode is determined to be mismatched, and a risk elimination signal is output.

8. The soft soil treatment composite pavement structure design system according to claim 1, characterized in that, The process by which the adaptive iterative correction module calculates the corrected structural layer design modulus includes: Obtain the preset feedback gain coefficient and the ultimate tensile strain modulus value specified in the pavement design code; Calculate the deformation magnitude ratio: Calculate the global strength norm of the actual deviation tensor in the entire domain and divide it by the ultimate tensile strain modulus; Calculate the stiffness compensation factor: multiply the deformation magnitude ratio, spatial topological coherence coefficient, and feedback gain coefficient, and add the product to the numerical value. Calculate the new modulus: Multiply the original elastic modulus in the proposed pavement structure scheme by the stiffness compensation factor to obtain the corrected structural layer design modulus.

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