Calculation method of dynamic earth pressure of deep soft soil foundation pit considering time-space effect

Abstract

This invention provides a method for calculating dynamic earth pressure in foundation pits in deep soft soil strata, considering spatiotemporal effects. It relates to the field of earth pressure calculation technology. The method includes: establishing an initial geological model; digitizing the foundation pit construction plan and dividing it into multiple spatiotemporal units; constructing a dynamic earth pressure calculation numerical model, introducing a soft soil rheological constitutive model and stratum parameters, activating excavation and support steps, and incorporating the rheological effect of the soil in each calculation step; collecting real-time monitoring data; comparing the earth pressure and deformation calculation results with the monitoring data at corresponding locations, establishing an objective function, using an optimization algorithm to invert and correct key parameters, and updating the earth pressure calculation for the next construction step; outputting dynamic earth pressure values ​​at each construction stage and depth based on the corrected model; and issuing an early warning message and guiding appropriate on-site measures when the calculated earth pressure exceeds a preset warning value. This invention enables accurate dynamic prediction and proactive early warning of foundation pit earth pressure.

Description

Technical Field

[0001] This invention relates to the field of earth pressure calculation technology, specifically to a method for calculating dynamic earth pressure in foundation pits in deep soft soil strata that takes into account spatiotemporal effects. Background Technology

[0002] Accurate calculation of earth pressure is fundamental to ensuring the safety of the support structure and the stability of the surrounding environment during deep foundation pit excavation in thick soft soil strata. Existing earth pressure calculation methods mainly fall into two categories: one is the "standard method" or "empirical coefficient method" based on Rankine or Coulomb theory, which calculates active and passive earth pressure based on the soil shear strength index and then multiplies it by an empirical coefficient for reduction; the other is to use numerical simulation methods such as finite element method, selecting conventional constitutive models such as Mohr-Coulomb or modified Cambridge, and activating elements step by step according to the construction steps to simulate earth pressure and deformation during the excavation process.

[0003] However, all of the aforementioned existing methods have significant technical shortcomings. The traditional empirical coefficient method treats earth pressure as a static constant, completely ignoring the creep and stress relaxation rheological effects of soft soil after excavation and unloading. It fails to reflect the dynamic evolution of earth pressure over time and the impact of construction procedures such as "layering, segmentation, and time-limited" construction, leading to significant deviations between calculated results and actual measured values. While conventional numerical simulation methods can simulate the construction process step by step, their constitutive models are not coupled with a soft soil rheology module, and their parameters largely rely on uncalibrated laboratory tests. Furthermore, they lack a mechanism for dynamic integration with real-time on-site monitoring data, failing to form an information-based closed loop of "model prediction - measured feedback - parameter correction." Both of these methods cannot predict the dynamic changes of earth pressure in deep soft soil foundation pits in real time and accurately, making it difficult to meet the actual needs of information-based construction and safety early warning. Summary of the Invention

[0004] To address the problems in related technologies, this invention provides a method for calculating dynamic earth pressure in foundation pits in deep soft soil strata that considers spatiotemporal effects.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for calculating dynamic earth pressure in foundation pits in deep soft soil strata, considering spatiotemporal effects, includes the following steps:

[0007] Step S1: Based on the engineering survey report and soft soil rheological test data, establish an initial geological model that considers the rheological properties of soft soil;

[0008] Step S2: Digitize the foundation pit construction plan and divide the foundation pit into multiple spatiotemporal units according to the principle of layering and segmentation. Each spatiotemporal unit contains spatial location information, excavation time information, support erection time information, and geometric dimension information.

[0009] Step S3: Construct a dynamic earth pressure calculation numerical model that includes the retaining structure and internal support system. Introduce the soft soil rheological constitutive model and stratum parameters from the initial geological model into the model. Activate the excavation step and the support step step step in the order of the spatiotemporal units. In each step of the calculation, the rheological effect of the soil is taken into account to obtain the earth pressure and deformation calculation results for each construction stage.

[0010] Step S4: During the construction of the foundation pit, collect real-time monitoring data on the deep horizontal displacement of the retaining wall, the axial force of the support, the groundwater level outside the pit, and the settlement of the columns, and preprocess the monitoring data.

[0011] Step S5: Compare the calculated earth pressure and deformation results with the preprocessed monitoring data at the corresponding locations, establish the objective function, use the optimization algorithm to invert and correct the key parameters, substitute the corrected parameters back into the numerical model, update the earth pressure calculation for the next construction step, and form a closed-loop dynamic update of calculation-monitoring-correction-prediction.

[0012] Step S6: Output the dynamic earth pressure values ​​at each construction stage and depth location based on the corrected model. When the calculated earth pressure exceeds the preset warning value, issue a warning message and guide the site to take corresponding measures.

[0013] Optionally, in step S1, establishing an initial geological model considering the rheological properties of soft soil includes:

[0014] Obtain the physical and mechanical parameters of the strata within the influence range of the foundation pit, including the specific gravity. Initial porosity Compression modulus coefficient of lateral pressure at rest Cohesion and internal friction angle ;

[0015] For deep soft soil layers, the parameters of the soft soil rheological constitutive model are determined by indoor creep tests or empirical data. The soft soil rheological constitutive model is a model that can describe the creep and stress relaxation behavior of soft soil.

[0016] Optionally, the rheological constitutive model of the soft soil is the Burgers model, whose creep equation is expressed as:

[0017]

[0018] In the formula, for Adaptability at all times For initial stress, For instantaneous elastic modulus, For the delayed elastic modulus, The instantaneous viscosity coefficient, The delayed viscosity coefficient, For time.

[0019] The parameters of the Burgers model were obtained by fitting triaxial creep test data. , , and .

[0020] Optionally, in step S2, digitizing the foundation pit construction plan and dividing the foundation pit into multiple spatiotemporal units according to the principles of layering and segmentation specifically includes:

[0021] The entire foundation pit is divided into multiple layers in the depth direction and multiple segments in the horizontal direction. Each segment and each layer corresponds to a spatiotemporal unit.

[0022] For each spatiotemporal unit, its spatial coordinates, excavation start and end times, support erection time, and unit geometry are encoded to form a construction schedule.

[0023] Optionally, the geometric dimensions of the spatiotemporal unit include layer height. and segment length The layer height is determined by the vertical spacing of the supports, and the segment length is determined by the horizontal support spacing or expansion joint division.

[0024] Optionally, in step S3, the dynamic earth pressure calculation numerical model is established using the finite element or finite difference method. The model includes a retaining structure and an internal support system, and assigns physical and mechanical parameters of each stratum and parameters of the soft soil rheological constitutive model.

[0025] According to the order of the spatiotemporal units, the soil of the corresponding unit is removed step by step in the excavation step, and the support step is activated to apply support and prestress.

[0026] In each step of the calculation, the soil rheological effect is considered simultaneously, and the creep deformation and stress relaxation within that step are calculated.

[0027] Optionally, the consideration of soil rheological effects in each calculation step includes calculating creep deformation using the creep equation of the Burgers model.

[0028] Optionally, in step S4, the preprocessing includes removing outliers and data smoothing filtering, and calculating the changes of each monitoring point at different times.

[0029] Optionally, in step S5, comparing the calculated earth pressure and deformation results with the preprocessed monitoring data at the corresponding locations, establishing an objective function, and using an optimization algorithm to invert and correct key parameters specifically involves:

[0030] The objective function is constructed based on the difference between the calculated and measured values;

[0031] The objective function is optimized using an optimization algorithm, and the corrected key parameters are obtained by inversion.

[0032] The key parameters include soft soil rheological parameters.

[0033] Optionally, the key parameters also include the initial stress field or lateral pressure coefficient of the soil, and the stiffness reduction coefficient of the support structure; the optimization algorithm is a genetic algorithm or a Kalman filter algorithm.

[0034] Beneficial effects:

[0035] 1. First, the method of this invention can accurately reflect the rheological effects of soft soil, overcoming the fundamental deficiency of traditional methods that ignore the time dimension. Specifically, this invention establishes an initial geological model considering the rheological properties of soft soil, introduces rheological constitutive models such as Burgers, and gradually incorporates the creep deformation and stress relaxation behavior of the soil in the numerical calculation, enabling the calculation model to simulate the dynamic evolution of earth pressure in soft soil after excavation and unloading, which continues to increase over time. Compared with the calculation logic of traditional methods based on the assumption of "instantaneous stability," this invention fundamentally eliminates the inherent drawbacks of overly risky predictions in the early stages of excavation and overly conservative predictions in the long term, making the earth pressure calculation results closer to the field measured values.

[0036] Secondly, the method of this invention can accurately simulate the spatiotemporal effects of construction and quantify the impact of construction procedures on earth pressure distribution. Specifically, this invention digitizes actual construction schemes such as "layering, segmentation, and time-limited" into spatiotemporal units with spatial coordinates, excavation time, support erection time, and geometric dimensions. In the numerical model, excavation and support operations are executed sequentially according to these spatiotemporal units, ensuring strict synchronization between the calculation process and the on-site construction progress. This transforms the construction rhythm into quantifiable and analyzable mechanical parameters, realistically reproducing the physical mechanism by which soil stress release paths are controlled by construction procedures. This solves the technical problem of traditional methods treating earth pressure as a static final value unrelated to the construction process and failing to reflect the differentiated impact of different construction rhythms on earth pressure.

[0037] Third, the method of this invention can construct a closed-loop feedback mechanism for calculation and monitoring, realizing dynamic calibration of information-based construction. Specifically, this invention collects real-time monitoring data such as deep horizontal displacement of the retaining wall and axial force of the support during construction, compares the calculation results with the measured data, constructs an objective function, and uses optimization algorithms to inversely correct key parameters such as soft soil rheological parameters, initial stress conditions, and stiffness of the support structure. The corrected parameters are then substituted back into the model to predict the earth pressure in the next construction step, forming a closed-loop dynamic update of "calculation-monitoring-correction-prediction". This breaks the traditional disconnect between design calculation, on-site monitoring, and risk warning, allowing model parameters to be continuously calibrated by measured data, and improving prediction accuracy as construction progresses.

[0038] Fourth, the method of this invention enables a leap from passive verification to proactive early warning, improving the safety and economy of foundation pit engineering. Specifically, this invention outputs dynamic earth pressure values ​​at each construction stage and depth location based on the corrected model, and proactively issues an early warning when the calculated value exceeds a preset warning value, guiding corresponding measures on site. This transforms earth pressure calculation from a mere post-construction design verification tool into a decision support method with rolling prediction capabilities and advanced risk assessment capabilities as construction progresses. Accurately grasping the dynamic changes in earth pressure helps optimize the timing and magnitude of support axial force application, avoiding engineering waste caused by overly conservative design, and simultaneously identifying abnormal deformation trends in advance, ensuring the safety of the foundation pit and its surrounding environment.

[0039] Fifth, this invention provides a complete implementation process from geological modeling, spatiotemporal unit division, rheological coupling numerical calculation, monitoring data preprocessing, parameter inversion and correction to dynamic early warning output. Each step is strictly connected in terms of data transfer and parameter inheritance, and the technical path is clear and explicit. The method of this invention is not only applicable to foundation pit engineering in deep soft soil areas, but can also be extended to underground engineering in other soft soil and soft rock strata with significant rheological characteristics, demonstrating broad engineering applicability.

[0040] 2. Other beneficial effects or advantages of the present invention will be described in detail in the specific embodiments. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments 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.

[0042] in:

[0043] Figure 1 and Figure 2This is a flowchart illustrating the steps of a method for calculating dynamic earth pressure in deep soft soil foundation pits that considers spatiotemporal effects, provided by an exemplary embodiment of the present invention.

[0044] Figure 3 This is a flowchart of the steps of a method for calculating dynamic earth pressure in deep soft soil foundation pits that takes into account spatiotemporal effects, provided by an exemplary embodiment of the present invention.

[0045] Figure 4 This is a schematic diagram of the Burgers rheological constitutive model of soft soil provided in an exemplary embodiment of the present invention;

[0046] Figure 5 This is a schematic diagram of the spatiotemporal unit division of the foundation pit provided in an exemplary embodiment of the present invention. Detailed Implementation

[0047] To facilitate a clearer and more accurate understanding of the technical solutions of this invention by those skilled in the art, the existing related technologies and their technical problems will be described in more detail below.

[0048] In municipal and construction engineering, deep foundation pit excavation is often required in soft soil layers for the construction of underground stations, tunnels, and other underground structures. Thick soft soil layers are widely distributed in coastal areas such as the Yangtze River Delta and Pearl River Delta in my country. Typical soft soil layers, such as silty clay and silty clay, have high water content, high compressibility, low shear strength, and significant rheological properties. During excavation in these layers, the removal of soil disrupts the original stress balance, causing soil on the outside of the pit to move inwards, thus generating lateral pressure on the supporting structures (such as diaphragm walls and pile banks). Accurate calculation of this lateral pressure is crucial for determining the dimensions of the retaining structure, the number of supports, the axial force of the supports, and even the safety of the entire foundation pit. Underestimating the value may lead to the failure of the support system or even the collapse of the foundation pit; overestimating the value will result in an overly conservative design, significantly increasing project costs.

[0049] Currently, the methods used in the engineering field to calculate this lateral pressure can be mainly divided into two categories, and their respective implementation paths and technical essence are as follows:

[0050] The first category is the traditional empirical method based on Rankine or Coulomb theories. This method first obtains the physical and mechanical parameters of soil samples from various strata through site surveys, such as soil weight, internal friction angle, and cohesion. Then, based on the classical earth pressure theory formulas, the active and passive earth pressures at which the soil reaches its limit equilibrium state are calculated separately. Given the complexity of soft soil areas, practitioners will introduce a fixed "empirical earth pressure coefficient" or "safety factor" based on local engineering experience or industry standards to reduce or amplify the theoretically calculated values, thus using this as the final design earth pressure. This process essentially simplifies an extremely complex, time-varying mechanical process into a static solution based on the limit equilibrium assumption, and then uses a single envelope value to cover the entire construction cycle.

[0051] The second category is numerical simulation methods based on continuum mechanics. With the development of computer technology, researchers often use finite element method (FEM) software (such as Abaqus) or finite difference method (FEM) software (such as FLAC) to construct two-dimensional or three-dimensional models of the excavation pit. This method can establish a complete geometric model including soil layers, retaining structures, and internal support systems. Based on a pre-planned construction sequence, it uses the "element birth and death" technique to remove soil from the pit one by one and activate supports one by one, simulating the physical process of excavation and unloading in a step-by-step calculation. To describe the stress-strain relationship of the soil, a constitutive model, such as the Mohr-Coulomb model or the modified Cambridge model, is usually assigned to the model. The initial intention of this approach was to compensate for the shortcomings of traditional methods in considering the construction sequence.

[0052] Although the two methods mentioned above have been widely used, they both face insurmountable technical gaps when dealing with deep soft soil strata, specifically manifested in the following three intertwined and profound technical problems:

[0053] First, a core blind spot in understanding this phenomenon is the neglect of the time-dependent mechanical behavior of soft soil, namely, the rheological effect. Classical earth pressure theory and the constitutive models used in conventional numerical simulations are both based on the assumption that "soil deformation is instantaneous and immediately stabilizes after being subjected to force." However, the physical nature of deep soft soil is that it is a porous medium rich in bound water and possessing colloidal properties; its deformation after unloading is not instantaneous. At the moment of unloading, the soil immediately undergoes elastic recovery due to the reduction in effective stress; but subsequently, under constant load, the soil particle skeleton will undergo continuous and irreversible creep deformation over time, i.e., "creep." Macroscopically, this manifests as the retaining wall continuing to shift into the pit several days or even months after excavation, and the axial force of the support continuing to slowly increase. This phenomenon of stress continuously shifting and redistributing to the support structure due to structural creep of the soil is a fundamental blind spot in the understanding of the mechanism by traditional methods. This makes it impossible for any calculation based on the assumption of "instantaneous stability" to predict the "climbing effect" of earth pressure dynamically increasing over time. The calculated value may be too dangerous in the early stage of excavation, but too conservative in the long term.

[0054] Secondly, a common practical bias is the neglect of the spatiotemporal effects of construction and their coupling with rheological effects. Experienced engineers know that "layered, segmented, and time-limited" excavation of soft soil foundation pits is a fundamental principle for controlling deformation, but the underlying mechanical mechanisms are not quantitatively reflected in traditional design. The essence of the spatiotemporal effect is that the release path, release rate, and release degree of soil stress depend not only on the final geometry of the excavation but also, more strictly, on the "procedures" and "time" of construction. For example, if a small section of soil is quickly excavated at a certain depth and supports are erected promptly, the unloading path of the soil at that location is quickly cut off, the exposure time is short, creep deformation does not have time to fully develop, and the displacement of the retaining wall and the increase in soil pressure are effectively suppressed. Conversely, if supports are not erected promptly after excavation, a time window is left for creep development, and displacement and pressure will increase significantly. Traditional empirical methods treat the entire excavation process as a static endpoint without a time concept. While conventional finite element step-by-step simulation can geometrically represent "layering and segmentation," without embedding rheological constitutive models, it merely reenacts the instantaneous loading-unloading sequence in the finite element model. It cannot quantify the substantial impact of the "16-hour time difference between each small step of excavation and support" on the redistribution of earth pressure, making it difficult to scientifically optimize and guide the construction rhythm.

[0055] Finally, a key missing mechanism is the "open-loop" relationship between the computational model and the measured field data, failing to form a closed-loop feedback loop. Currently, almost all standards emphasize "information-based construction," with numerous inclinometers, axial force gauges, and other sensors deployed at the foundation pit site, generating massive amounts of real-time, continuous data. However, traditional computational models are used only once: parameters are input and results are obtained during the design phase, and during the construction phase, measured values ​​are used only to passively verify whether limits are exceeded. Once a deviation occurs between the measured and calculated values, there is a lack of an automated and efficient technical means to use measured deformation and force data to deduce the most uncertain soft soil rheological parameters and initial stress field from the model, and to make rolling predictions of earth pressure development in the next stage. This results in the three core links of "design calculation," "on-site monitoring," and "risk early warning" being technically isolated, with information flowing in one direction and unable to empower each other, thus failing to truly achieve proactive and dynamic risk management.

[0056] In summary, the shortcomings of existing technologies can be attributed to two factors: one ignores the "time" dimension, and the other fixes the influence of the "process," neither of which can be integrated with "actual measurements." Therefore, there is an urgent need for a dynamic earth pressure calculation method that can integrate the rheological properties of soft soil, construction time and space procedures, and on-site monitoring feedback to scientifically solve the safety and economic balance problem in deep soft soil foundation pit engineering.

[0057] In view of this, the present invention provides a novel solution: a dynamic earth pressure calculation method for deep soft soil foundation pits that considers spatiotemporal effects. The technical concept of this invention lies in addressing the shortcomings of traditional methods that neglect the time effects of soft soil and the construction process by constructing a three-in-one dynamic earth pressure calculation closed loop encompassing "mechanism-process-data". Specifically, firstly, at the mechanism layer, the Burgers rheological model is introduced to endow the soil with the "time memory" capability of continuous creep and stress relaxation after excavation and unloading. Secondly, at the process layer, construction procedures such as "layering, segmentation, and time-limited" are digitized into computational units with spatiotemporal attributes, enabling the numerical model to accurately reproduce the "process path" of stress release and its coupling mechanism with rheological effects. Finally, at the data layer, a real-time inversion channel is established between the model and measured data such as field inclinometer readings and axial forces. Key uncertainties such as rheological parameters are dynamically corrected through optimization algorithms, and the corrected model is used to predict the earth pressure for the next construction condition. In this way, the traditional static, open-loop earth pressure calculation is transformed into a dynamic method that continuously evolves with the construction process and possesses self-calibration and predictive capabilities.

[0058] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0059] like Figures 1 to 3 As shown in the figure, this embodiment provides a method for calculating dynamic earth pressure in deep soft soil foundation pits that considers spatiotemporal effects, including the following steps:

[0060] Step S1: Based on the engineering survey report and soft soil rheological test data, establish an initial geological model that considers the rheological properties of soft soil;

[0061] Step S2: Digitize the foundation pit construction plan and divide the foundation pit into multiple spatiotemporal units according to the principle of layering and segmentation. Each spatiotemporal unit contains spatial location information, excavation time information, support erection time information, and geometric dimension information.

[0062] Step S3: Construct a dynamic earth pressure calculation numerical model that includes the retaining structure and internal support system. Introduce the soft soil rheological constitutive model and stratum parameters from the initial geological model into the model. Activate the excavation step and the support step step in the order of spatiotemporal units, and take into account the rheological effect of the soil in each step of the calculation to obtain the earth pressure and deformation calculation results for each construction stage.

[0063] Step S4: During the construction of the foundation pit, collect real-time monitoring data on the deep horizontal displacement of the retaining wall, the axial force of the support, the groundwater level outside the pit, and the settlement of the columns, and preprocess the monitoring data.

[0064] Step S5: Compare the earth pressure and deformation calculation results with the preprocessed monitoring data at the corresponding locations, establish the objective function, use the optimization algorithm to invert and correct the key parameters, substitute the corrected parameters back into the numerical model, update the earth pressure calculation for the next construction step, and form a closed-loop dynamic update of calculation-monitoring-correction-prediction.

[0065] Step S6: Output the dynamic earth pressure values ​​at each construction stage and depth location based on the corrected model. When the calculated earth pressure exceeds the preset warning value, issue a warning message and guide the site to take corresponding measures.

[0066] Through the above technical solution, firstly, the method of the present invention can give earth pressure calculation a "time dimension," thereby solving the fundamental defect of traditional methods that ignore the rheological effect of soft soil. Specifically, step S1 of the present invention establishes an initial geological model that considers the rheological characteristics of soft soil, and step S3 incorporates the rheological effect of the soil in each excavation calculation. In this way, the calculation model can simulate the creep deformation and stress relaxation behavior of soft soil after excavation and unloading, reflecting the dynamic evolution law of earth pressure continuously increasing over time, and avoiding the inherent drawbacks of traditional static methods that are too risky in the early stage of excavation and too conservative in long-term predictions.

[0067] Secondly, the method of this invention can give earth pressure calculation a "process dimension," thereby solving the problem that traditional methods cannot quantify the impact of construction procedures. Specifically, step S2 of this invention digitizes the actual construction scheme such as "layering, segmentation, and time-limited" into spatiotemporal units with time and geometric attributes. Step S3 strictly follows the sequence of these spatiotemporal units to gradually activate excavation and support. In this way, the calculation process can be synchronized with the on-site construction progress, and the physical mechanism of soil stress release path controlled by the construction rhythm can be realistically reproduced, making the earth pressure calculation results more consistent with the actual engineering situation.

[0068] Third, the method of this invention can construct a data-driven dynamic correction closed loop, thereby solving the problem of the disconnect between traditional models and monitoring data. Specifically, step S4 of this invention collects real-time monitoring data such as the deep horizontal displacement of the retaining wall and the axial force of the supports; step S5 compares the calculation results with the measured data, and corrects key parameters and updates the model through algorithm optimization, forming a closed-loop mechanism of "calculation-monitoring-correction-prediction". In this way, the model parameters can be continuously calibrated by measured data during construction, continuously improving the prediction accuracy and providing technical support for information-based construction.

[0069] Fourth, the method of this invention can achieve a leap from passive verification to proactive early warning. Specifically, step S6 of this invention outputs dynamic earth pressure values ​​at each construction stage and depth location based on the corrected model, and issues a warning and guides measures when the calculated value exceeds the warning value. In this way, earth pressure calculation is no longer just a tool for post-construction design verification, but has the ability to predict and identify risks in advance as construction progresses, providing dynamic and forward-looking technical protection for foundation pit safety.

[0070] In one embodiment of the present invention, step S1 involves establishing an initial geological model that considers the rheological properties of soft soil, including:

[0071] Obtain the physical and mechanical parameters of the strata within the influence range of the foundation pit, including the specific gravity. Initial porosity Compression modulus coefficient of lateral pressure at rest Cohesion and internal friction angle ;

[0072] For deep soft soil layers, the parameters of the soft soil rheological constitutive model are determined by indoor creep tests or empirical data. The soft soil rheological constitutive model is a model that can describe the creep and stress relaxation behavior of soft soil.

[0073] In this embodiment, firstly, the physical and mechanical parameters of the strata within the influence range of the foundation pit are defined, specifically including the density. Initial porosity Compression modulus coefficient of lateral pressure at rest Cohesion and internal friction angle These parameters are not arbitrarily selected, but constitute a basic index system describing the mechanical behavior of soft soil strata. Among them, the density of soil... and initial porosity The compressibility modulus reflects the physical state and density of the soil. Characterizing the compressibility of soil under load, the coefficient of lateral pressure at rest Determines the initial stress state and cohesion in the strata before excavation. and internal friction angle These are the core indicators for controlling the shear strength of soil. By obtaining these parameters, the initial geological model can describe the initial stress field and strength characteristics of the strata, making the strata parameters of the numerical model in the subsequent step S3 based on evidence and avoiding calculation distortion caused by missing parameters or arbitrary assumptions.

[0074] Secondly, conventional geological models only include the aforementioned physical and mechanical parameters, essentially treating the soil as a time-independent medium, failing to reflect the rheological characteristics of soft soil undergoing continuous deformation after excavation and unloading. This implementation method, however, requires the addition of rheological parameters during the initial geological model establishment stage, enabling the model to possess "time memory" capabilities from the outset (i.e., the ability to characterize the creep behavior of soil strain increasing over time under constant load, and the relaxation behavior of stress decreasing over time under constant deformation). This provides a parameter basis for "incorporating the rheological effects of the soil into each calculation step" in step S3, ensuring that subsequent numerical simulations no longer remain in a hypothetical, instantaneously stable state, but rather realistically reproduce the physical process of the dynamic evolution of earth pressure over time after the excavation of a soft soil foundation pit.

[0075] In one embodiment of the present invention, the rheological constitutive model for soft soil is the Burgers model. (See also...) Figure 4 , Figure 4 This is a schematic diagram of Burgers' rheological constitutive model for soft soil, whose creep equation is expressed as:

[0076]

[0077] In the formula, for Adaptability at all times For initial stress, For instantaneous elastic modulus, For the delayed elastic modulus, The instantaneous viscosity coefficient, The delayed viscosity coefficient, For time;

[0078] The parameters of the Burgers model were obtained by fitting triaxial creep test data. , , and .

[0079] In this embodiment... This term characterizes instantaneous elastic deformation, that is, the elastic recovery of the soil immediately upon unloading. The term characterizes steady-state viscous flow, which is the irreversible viscous deformation of the soil skeleton that occurs continuously over time at a constant rate. Characterizing delayed elastic deformation, i.e., the viscoelastic creep process in which the deformation rate gradually decays over time. These three terms correspond to the deformation components of soft soil at different time scales after excavation and unloading, fully depicting the entire process of "instantaneous response - decaying creep - steady-state creep".

[0080] In one embodiment of the present invention, in step S2, the foundation pit construction plan is digitized, and the foundation pit is divided into multiple spatiotemporal units according to the principles of layering and segmentation. (See also...) Figure 5 , Figure 5 This is a schematic diagram of the spatiotemporal unit division of the foundation pit, which may specifically include:

[0081] The entire foundation pit is divided into multiple layers in the depth direction and multiple segments in the horizontal direction. Each segment and each layer corresponds to a spatiotemporal unit.

[0082] For each spatiotemporal unit, its spatial coordinates, excavation start and end times, support erection time, and unit geometry are encoded to form a construction schedule.

[0083] In this implementation, firstly, the entire foundation pit is divided into multiple layers along the depth direction and multiple segments along the horizontal direction. The intersection of each segment and each layer corresponds to a spatiotemporal unit. This allows the construction plan, originally existing in text and drawing form, to be systematically deconstructed into a set of discrete, well-defined basic computational units. Compared to the traditional method of treating the entire foundation pit as a single, coarse-grained calculation, this discretization process breaks down the continuous excavation process into an ordered sequence of units. This provides a directly usable geometric structure and execution sequence for the subsequent step S3, "gradually activating the excavation and support steps according to the spatiotemporal unit sequence," thus establishing a seamless connection between the construction plan and numerical calculations at the operational level.

[0084] Second, the information to be encoded for each spatiotemporal unit includes spatial coordinates, excavation start and end times, support erection time, and unit geometric dimensions, thus forming a construction schedule. Encoding the "excavation start and end times" and "support erection time" is a key difference from traditional static models. This ensures a clear time interval between the soil removal time and the support activation time for each unit; this time interval is precisely the "time window" for the free creep development of soft soil in an unsupported state. By incorporating this time window information into the construction schedule, step S3 can accurately reproduce the rhythmic effect of "layered, segmented, and time-limited" construction in the numerical model (units with short time windows are constrained before creep deformation has fully developed, resulting in a smaller increase in earth pressure; units with long time windows have fully developed creep, resulting in a larger increase in earth pressure). Thus, the time control requirements in the construction plan are no longer merely at the management level but are transformed into quantifiable mechanical analysis parameters.

[0085] It should be noted that, Figure 5 This is a schematic diagram of the spatiotemporal unit division of the foundation pit. It is used to show the division of the foundation pit in the depth direction (layers) and the horizontal direction (segments), and to mark the spatiotemporal attributes of each unit (excavation time, support time, etc.).

[0086] In one embodiment of the present invention, the geometric dimensions of the spatiotemporal unit include the layer height. and segment length The layer height is determined by the vertical spacing of the supports, and the segment length is determined by the horizontal support spacing or expansion joint division.

[0087] In this implementation, firstly, the layer height The segment length is determined by the vertical spacing of the supports. The spatial and temporal units are determined by the spacing of horizontal supports or expansion joints. This ensures that the geometric scale of the spatiotemporal units is no longer an arbitrarily set value, but directly derived from the layout scheme of the foundation pit support structure. The vertical spacing of the supports determines the depth of each excavation layer (i.e., after excavating to a certain design elevation of a support, that support must be erected promptly); the horizontal spacing of the supports or expansion joints determines the horizontal range of each excavation segment. Thus, a strict correspondence is established between the division of the spatiotemporal units and the support structure system. Each spatiotemporal unit corresponds precisely to a piece of soil "between two adjacent supports" or "between two adjacent expansion joints." This ensures that the actions of "removing soil" and "activating supports" in subsequent step S3 have a clear mechanical correspondence in spatial scope, ensuring that the geometric framework of the numerical simulation is consistent with the actual engineering structure.

[0088] Secondly, the degree of soil stress release during foundation pit excavation is closely related to the geometric range of each exposure. That is, the greater the layer height, the greater the single unloading amount, and the more significant the stress release; the longer the segment length, the larger the exposed area, and the weaker the spatiotemporal effect's control over deformation. This implementation method binds the layer height to the vertical spacing of the supports and the segment length to the horizontal support spacing or expansion joint, meaning that the size of the spatiotemporal unit precisely reflects the soil exposure range of each excavation in actual construction (which is the basic unit of measurement for stress release). Thus, when the excavation calculation is performed step by step according to such a spatiotemporal unit in step S3, the unloading amount and exposed surface range simulated in each step match the actual situation on the construction site. This allows for the accurate reproduction of the spatiotemporal effect mechanism that "small layer height results in small single stress release, and short segment length results in a short creep development time window," providing a calculation granularity that conforms to engineering reality for the parameter inversion based on measured data in the subsequent step S5.

[0089] In one embodiment of the present invention, in step S3, the dynamic earth pressure calculation numerical model is established using the finite element or finite difference method. The model includes a retaining structure and an internal support system, and assigns physical and mechanical parameters of each stratum and parameters of the soft soil rheological constitutive model.

[0090] Following the order of the spatiotemporal units, the soil of the corresponding unit is removed step by step in the excavation process, and the support step is activated to apply support and prestress.

[0091] In each step of the calculation, the soil rheological effect is considered simultaneously, and the creep deformation and stress relaxation within that step are calculated.

[0092] In this embodiment, firstly, the finite element method or finite difference method is a mature numerical means for dealing with complex geotechnical engineering problems, which can discretize the continuous medium and solve the stress-strain field; the model explicitly includes the retaining structure and internal support system, which means that the calculation object can completely cover all the stress-bearing components of the foundation pit support system, rather than just performing isolated analysis on the soil; by assigning physical and mechanical parameters and rheological constitutive model parameters to each stratum, the model can be transformed from a geometric framework into a mechanical model with material constitutive properties.

[0093] Second, following the spatiotemporal unit sequence, the soil in the corresponding unit is removed step by step during excavation, and the support step is activated to apply support and prestress. This sequence of operations is an accurate reproduction of the physical process of foundation pit excavation in the numerical model (i.e., removing soil simulates the unloading process of the original stress boundary on the excavation surface being released after the soil in the pit is excavated); activating support and applying prestress simulates the mechanical behavior of applying constraint reaction force to the retaining structure after the support is erected, limiting its further deformation. Since the spatiotemporal unit has been encoded with the excavation start and end time and support erection time in step S2, the sequential execution here naturally introduces the time interval between the two events, making the time difference between each excavation step and the support step in the model consistent with the time limit requirements of on-site construction, and providing the correct time boundary conditions for the development of rheological effects during the unsupported exposure period.

[0094] Third, in conventional finite element step-by-step excavation simulations, each step only solves for the instantaneous stress-strain equilibrium, and then proceeds to the next construction step. The stress state after the previous excavation step is considered static and does not change over time. This implementation, however, requires that the creep deformation and stress relaxation of the soil within each step be calculated simultaneously. Thus, during the time interval between two successive construction events, the model is not in a static waiting state, but continuously performs creep calculations (the soil continues to deform over time within this time window, and the stress field is redistributed accordingly). Therefore, the development of earth pressure no longer depends solely on the excavated geometry, but also on the duration of each excavation step; that is, the mechanical effects of "time-limited" construction are quantified in the numerical simulation. Through this coupling mechanism, the numerical calculation results can capture the dynamic behavior of the continuous increase of earth pressure in soft soil foundation pits over time, fundamentally different from the traditional numerical simulation logic where earth pressure reaches its final value at the instant of excavation.

[0095] In one embodiment of the invention, soil rheological effects are considered simultaneously in each calculation step, including calculating creep deformation using the creep equation of the Burgers model.

[0096] The creep equation of the Burgers model, described in detail above, comprises instantaneous elastic terms, steady-state viscous flow terms, and delayed elastic terms. These three parts collectively characterize the entire process of deformation of soft soil under constant stress over time. By applying this equation to the time step after each excavation step, the additional deformation caused by creep within that step can be numerically obtained, and the corresponding stress increment can then be solved using the stiffness matrix. Thus, the inclusion of rheological effects is no longer an abstract functional description, but rather a standardized computational operation that can be called step-by-step and repeatedly executed within the numerical computation framework.

[0097] In one embodiment of the present invention, in step S4, the preprocessing includes removing outliers and data smoothing filtering, and calculating the change of each monitoring point at different times.

[0098] In this embodiment, firstly, the monitoring environment at the foundation pit construction site is complex. Sensors are subjected to harsh conditions such as high humidity, strong electromagnetic interference, and construction vibration for extended periods. The raw data inevitably contains outliers caused by factors such as momentary sensor malfunctions, signal transmission interruptions, or accidental collisions during construction, as well as high-frequency fluctuations due to environmental noise. If this unprocessed raw data is directly used for comparison and inversion with calculated values ​​in step S5, outliers will distort the optimization direction of the objective function, causing the inverted parameters to deviate from the true physical state. High-frequency noise will obscure the true trend of soil pressure evolution over time, making it difficult for the inversion algorithm to capture the systematic laws of creep development. In this embodiment, two preprocessing operations are performed: outlier removal and smoothing filtering. The former eliminates discrete erroneous data points with amplitudes significantly deviating from the normal range, while the latter suppresses random noise and extracts trend components from the data. Together, these two operations ensure that the monitoring data entering step S5 accurately reflects the mechanical response characteristics of the support structure under soft soil rheological action, providing a reliable data foundation for subsequent objective function construction and parameter inversion.

[0099] Secondly, the monitoring sensors directly output absolute readings at each moment, such as the cumulative value of wall displacement or the current value of support axial force. However, for the comparison of calculated and measured values ​​step by step in step S5, what is truly meaningful is the change caused by the excavation and rheological effects within a specific construction step (i.e., the increment of the current construction step's end time relative to the previous construction step's end time). In this embodiment, calculating the change at each monitoring point at different times transforms the original time-series data into an incremental sequence corresponding to the construction step sequence. This transformation has two technical implications: First, the change is stripped of the influence of initial readings and previous accumulated deformation, focusing on the net response generated by the current construction step, making the comparison benchmark physically aligned with the incremental results calculated step by step in step S3 according to spatiotemporal units; second, the change sequence more sensitively reflects the differences between each excavation step, facilitating the inversion algorithm in step S5 to identify which parameters play a dominant role in the mechanical response of the current working condition, thereby improving the targeting and convergence efficiency of parameter correction.

[0100] In one embodiment of the present invention, in step S5, the calculated results of earth pressure and deformation are compared with the preprocessed monitoring data at the corresponding locations to establish an objective function, and key parameters are inverted and corrected using an optimization algorithm, specifically as follows:

[0101] The objective function is constructed based on the difference between the calculated and measured values;

[0102] The objective function is optimized using an optimization algorithm, and the corrected key parameters are obtained by inversion.

[0103] Key parameters include soft soil rheological parameters.

[0104] In this implementation, firstly, in traditional methods, when the calculation results deviate from the monitoring data, engineers typically adjust the parameters manually based on experience and repeat the calculations. This method is not only inefficient, but also lacks objective criteria for the direction and magnitude of adjustments, making it difficult to converge to the globally optimal parameter combination. In this implementation, however, the deviation is quantified into a clear mathematical function, transforming the parameter correction problem into a standard optimization problem (the optimization algorithm automatically searches the parameter space for the parameter combination that minimizes the objective function). This not only eliminates the arbitrariness and subjectivity of manual intervention but also makes the inversion process reproducible and convergent, providing an automated and objective execution method for closed-loop dynamic updates.

[0105] Secondly, in step S1, the rheological parameters (such as those in the Burgers model) , , and The rheological parameters of soft soil are determined through indoor creep tests or empirical data. However, indoor test samples are inevitably affected by sampling disturbances, size effects, and differences between test conditions and field conditions. The obtained parameters often fail to accurately represent the rheological properties of the in-situ soil, making this the link with the greatest parameter uncertainty in the entire calculation chain. Simultaneously, soft soil rheological parameters directly control the calculation results of creep deformation and stress relaxation in step S3; even small deviations can lead to significant deviations in the predicted earth pressure over time. This implementation method includes soft soil rheological parameters as the object of inversion correction. This means using macroscopic response data such as retaining wall displacement and support axial force measured in the field to inversely calibrate these microscopic rheological parameters that are difficult to measure directly and accurately. This makes the corrected parameters closer to the actual rheological behavior of the soil in the field, thereby fundamentally improving the accuracy of predictions in subsequent construction steps and allowing the closed-loop update mechanism to truly play its calibration and optimization role.

[0106] In one embodiment of the present invention, the key parameters also include the initial stress field or lateral pressure coefficient of the soil, and the stiffness reduction coefficient of the support structure; the optimization algorithm is a genetic algorithm or a Kalman filter algorithm.

[0107] In this embodiment, firstly, the above-described implementation has included soft soil rheological parameters as the inversion object, thus solving the problem of inaccurate rheological properties. However, the factors affecting the deviation between calculated results and measured values ​​are not limited to rheological parameters. The initial stress field or lateral pressure coefficient of the soil can also play a role. This determines the in-situ stress state in the strata before excavation, serving as the initial condition for all subsequent unloading calculations. If The values ​​deviate from the actual stress state of the strata. Even if the rheological parameters are accurate, the calculated earth pressure baseline will still be offset. Similarly, during construction, the actual stiffness of the support structure may be lower than the design value due to factors such as concrete cracking and loose joints. If this is not corrected, the calculated support axial force and wall displacement will have systematic differences from the measured values. This implementation method includes these two types of parameters in the inversion range. In this way, step S5 can simultaneously use monitoring data to calibrate the uncertainties in the three dimensions of rheological parameters, initial stress conditions, and structural stiffness in the same optimization process. This effectively avoids the risk of incorrect compensation of the inversion results when only one type of parameter is corrected while other parameters still have deviations. This makes the corrected model closer to the actual field conditions in many aspects, thereby improving the accuracy and reliability of the prediction in the next construction step.

[0108] Secondly, the genetic algorithm is a global optimization method based on the principle of natural selection. It does not rely on the gradient information of the objective function and can effectively avoid getting trapped in local optima. It is well-suited for the complex inversion problem in this scheme, where multiple parameters, such as rheological parameters and initial stress, are coupled, and the objective function may have multiple local extrema. The Kalman filter algorithm, on the other hand, is a recursive optimal estimation method that can sequentially update parameter estimates as new monitoring data arrives, without needing to re-access all historical data each time. It has high computational efficiency and is particularly suitable for the scenario required in step S5, where parameters are updated continuously as construction progresses. Both algorithms have their own strengths and weaknesses, providing practical engineering applications with optimization methods that can be flexibly selected based on the characteristics of on-site data and computational resources, ensuring that the inversion correction steps are feasible and computationally efficient under different engineering conditions.

[0109] The technical solution of the present invention will be further described below with reference to an exemplary embodiment.

[0110] I. Relevant technical specifications.

[0111] Accurate calculation of earth pressure is crucial for ensuring the safety of the support structure and the stability of the surrounding environment during deep foundation pit excavation in thick soft soil strata. Traditional earth pressure calculation methods (such as Rankine's earth pressure theory and Coulomb's earth pressure theory) are mainly based on the assumption of rigid retaining walls and are suitable for sandy soils or stiff clay. Their basic assumptions are that the soil is an ideal elastic-plastic material, deformation is instantaneous, and time effects are not considered. However, in soft soil areas, due to the high compressibility, significant rheological properties, and low shear strength of soft soil, traditional methods are unable to reflect the dynamic distribution of earth pressure with excavation depth, support structure deformation, construction procedures (layered, segmented, time-limited), and time.

[0112] Currently, the commonly used methods in engineering are the "standard method" or the "empirical coefficient method." This involves calculating the active and passive earth pressures using Rankine or Coulomb formulas based on soil parameters provided in the survey report (such as the internal friction angle φ, cohesion c, and unit weight γ), and then multiplying these by an empirical coefficient (such as the empirical earth pressure coefficient K) or a safety factor to obtain the design earth pressure. For soft soil areas, sometimes a regional correction factor is introduced, referencing similar engineering experience. This method is simple to calculate and widely used in design institutes and construction units.

[0113] However, this method has the following drawbacks:

[0114] 1. Ignoring the rheological properties of soft soil. Creep and stress relaxation of soft soil cause soil pressure to change over time. Traditional methods completely ignore the time factor, and the calculated soil pressure may be too small in the early stage of excavation and too large in the later stage, making it impossible to accurately predict the long-term stress state of the support structure.

[0115] 2. Failure to reflect the impact of the construction process. Foundation pit excavation is a "layered, segmented, and time-limited" construction process. The excavation sequence of each layer of soil, the length of each segment, and the time of support erection all affect the stress release path and soil pressure distribution. Traditional methods treat soil pressure as a static value and cannot simulate this dynamic evolution.

[0116] 3. Disconnection from monitoring data. On-site monitoring (such as inclinometer and axial force gauge) has acquired a large amount of valuable data, but traditional calculations are only used for "verification" or "checking". There is a lack of a mechanism to feed this real-time data back to the calculation model, which makes it impossible to achieve truly information-based construction and dynamic early warning.

[0117] 4. Poor adaptability. For deep soft soil strata, especially in complex geological conditions such as confined water and underground streams, the calculation results of traditional methods often deviate significantly from the measured values, leading to overly conservative or dangerous designs.

[0118] In recent years, some researchers have attempted to use finite element method (FEM) software to simulate foundation pit excavation. They select appropriate soil constitutive models (such as the Mohr-Coulomb model and the modified Cambridge model), activate elements step by step according to the construction process, and calculate earth pressure and deformation. This method can simulate the excavation process, but it usually uses an ideal elastoplastic model, does not introduce a soft soil rheology module, and the calculation parameters are mostly taken from the survey report, lacking dynamic correction based on field measurement data.

[0119] However, this method also has the following drawbacks:

[0120] 1. Uncoupled rheological models. Although they can simulate construction steps, commonly used constitutive models (such as Mohr-Coulomb) cannot describe the creep and relaxation behavior of soft soil. The calculated earth pressure tends to stabilize after excavation, which does not match the actual long-term changes.

[0121] 2. High parameter uncertainty. The calculated parameters mainly rely on indoor geotechnical tests, but sampling disturbances, size effects, etc., cause the parameters to differ from the actual field conditions, and there is a lack of effective means to calibrate the parameters during construction.

[0122] 3. Insufficient computational efficiency and real-time performance. Detailed numerical simulations are time-consuming and difficult to update in real time on the construction site, failing to meet the needs of rapid decision-making.

[0123] II. Specific solutions of this exemplary implementation method.

[0124] 1. Step 1: Establish an initial geological model that takes into account the rheological properties of soft soil.

[0125] Based on the engineering survey report, the physical and mechanical parameters of the strata within the influence range of the foundation pit were obtained, including the unit weight. Initial porosity Compression modulus coefficient of lateral pressure at rest Cohesion and internal friction angle wait.

[0126] For deep soft soil layers (such as silty clay and silty clay), supplementary indoor creep tests or reference empirical data are used to determine the parameters of the soft soil rheological constitutive model. Using the Burgers model to describe its creep characteristics, its creep equation can be expressed as:

[0127]

[0128] In the formula, for Adaptability at all times For initial stress, For instantaneous elastic modulus, For the delayed elastic modulus, The instantaneous viscosity coefficient, The delayed viscosity coefficient, The time is used; the above parameters were obtained by fitting triaxial creep test data.

[0129] 2. Step Two: Digitize the construction plan and establish a "spatiotemporal unit" division.

[0130] The entire foundation pit was divided into multiple spatiotemporal units according to the principle of "layering and segmentation". Each unit contains the following information:

[0131] ① Spatial coordinates: Unit location (mileage range, depth range);

[0132] ② Excavation time: The start and end time of excavation for this unit of soil;

[0133] ③ Support erection time: The time corresponding to the completion of support installation and the application of prestress;

[0134] ④ Unit dimensions: layer height (usually determined by the vertical spacing of the supports, such as 3 to 3.5m), segment length (usually divided by the horizontal support spacing or expansion joint).

[0135] Taking the deep foundation pit excavation project of the open-cut section between Kexiang and Xiangjiang as an example, the excavation depth is 17.18 to 18.58 meters, and it is divided into 5 to 6 layers. Each layer is about 3 meters thick, and each section is 6 meters long. The excavation and support of each small section is limited to 16 hours. This information is coded into a construction schedule.

[0136] 3. Step 3: Construct a numerical model for calculating dynamic earth pressure.

[0137] A two-dimensional or three-dimensional numerical model of the foundation pit is established using the finite element or finite difference software Abaqus. The model includes the retaining structure (diaphragm wall, SMW method piles), internal support system (concrete supports, steel supports), and column piles.

[0138] The soft soil rheological constitutive model determined in step one is introduced into the model, and parameters are assigned to each stratum.

[0139] Following the spatiotemporal unit sequence determined in step two, the excavation step and the support activation step are activated step by step. In each excavation step, the soil of the corresponding unit is removed and support is applied (for steel supports, prestress is applied simultaneously).

[0140] In each step of the calculation, the soil rheological effect is considered, that is, the creep deformation and stress relaxation of the soil within the calculation step.

[0141] 4. Step Four: Real-time monitoring data acquisition and processing.

[0142] During the foundation pit construction process, the following data were collected according to the monitoring plan:

[0143] ① Horizontal displacement of the deep layers of the retaining wall (inclination measurement);

[0144] ② Support axial force (concrete support reinforcement gauge, steel support axial force gauge);

[0145] ③ Groundwater level outside the pit;

[0146] ④ Column settlement, etc.

[0147] The monitoring data is preprocessed to remove outliers, smooth the data, and calculate the changes at each monitoring point at different times.

[0148] 5. Step Five: Dynamic Inversion and Model Correction Based on Monitoring Data.

[0149] The earth pressure and deformation calculated in step three are compared with the corresponding location data measured in step four to establish the objective function. Key parameters are then retrieved using an optimization algorithm, including:

[0150] ① Rheological parameters of soft soil;

[0151] ② Initial stress field or lateral pressure coefficient of the soil;

[0152] ③ Stiffness reduction factor of the support structure, etc.

[0153] Substitute the inverted parameters into the model from step three to recalculate the earth pressure for the next construction step, thus achieving a closed-loop dynamic update of "calculation-monitoring-correction-prediction".

[0154] 6. Step Six: Dynamic Earth Pressure Output and Early Warning.

[0155] Based on the revised model, the dynamic earth pressure values ​​at each construction stage and depth are output. When the calculated earth pressure approaches or exceeds the design warning value, an early warning message is issued to guide the on-site implementation of corresponding measures, such as re-prestressing or suspending excavation.

[0156] Thus, based on the above exemplary embodiments, the following effects can be achieved:

[0157] First, it can accurately reflect the rheological effects of soft soil. By introducing rheological constitutive models such as Burgers, it is possible to simulate the creep and stress relaxation behavior of soft soil after excavation and unloading, making the calculated earth pressure closer to the measured value and avoiding the safety hazards caused by neglecting the time effect in traditional methods.

[0158] Secondly, it can accurately simulate the spatiotemporal effects of construction. By digitizing information such as layering, segmentation, and time limits in the actual construction plan, the calculation model can be synchronized with the on-site construction progress, and can realistically reproduce the dynamic evolution of earth pressure with each excavation step.

[0159] Third, it enables a closed-loop information-based construction process. By dynamically retrieving and correcting model parameters using real-time on-site monitoring data, it not only improves calculation accuracy but also achieves a virtuous cycle of "theory guiding construction and construction feedback correction," providing a scientific basis for dynamic design and risk warning.

[0160] Fourth, it can improve the safety and economy of foundation pit engineering. Accurately grasping the changes in earth pressure helps to optimize the timing and magnitude of the application of axial force on the supports, avoids overly conservative design, and can provide early warning of abnormal deformation, ensuring the safety of the foundation pit and its surrounding environment.

[0161] Fifth, it has wide applicability. This invention is not only applicable to the deep soft soil strata of this project, but can also be extended to other soft soil and soft rock foundation pit projects with obvious rheological properties.

[0162] In this invention, it should also be noted that:

[0163] First, for rheological constitutive models, in addition to the Burgers model, the Nishihara model, the modified Merchant model, and fractional derivative rheological models can also be used. Rheological properties can also be directly embedded into the modified Cambridge model or the hardened soil model to form a coupled model.

[0164] Second, in terms of numerical calculation methods, in addition to the finite element / finite difference method, the material point method (MPM) or smooth particle hydrodynamics (SPH) can also be used to simulate large deformation problems; for the need for rapid early warning, simplified analytical models can be developed and combined with neural networks for rapid prediction.

[0165] Third, for data inversion algorithms, in addition to genetic algorithms and Kalman filtering, machine learning methods such as Bayesian inversion, support vector regression (SVR), and long short-term memory neural networks (LSTM) can be used to learn the mapping relationship between model parameters and earth pressure from historical monitoring data.

[0166] Fourth, for real-time data fusion, a digital twin platform can be built to connect BIM models, IoT sensor data and numerical models in real time, enabling visualized dynamic display and early warning.

[0167] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for calculating dynamic earth pressure of deep soft soil stratum foundation pit considering space-time effect, characterized in that, Includes the following steps: Step S1: Based on the engineering survey report and soft soil rheological test data, establish an initial geological model that considers the rheological properties of soft soil; Step S2: Digitize the foundation pit construction plan and divide the foundation pit into multiple spatiotemporal units according to the principle of layering and segmentation. Each spatiotemporal unit contains spatial location information, excavation time information, support erection time information, and geometric dimension information. Step S3: Construct a dynamic earth pressure calculation numerical model that includes the retaining structure and internal support system. Introduce the soft soil rheological constitutive model and stratum parameters from the initial geological model into the model. Activate the excavation step and the support step step step in the order of the spatiotemporal units. In each step of the calculation, the rheological effect of the soil is taken into account to obtain the earth pressure and deformation calculation results for each construction stage. Step S4: During the construction of the foundation pit, collect real-time monitoring data on the deep horizontal displacement of the retaining wall, the axial force of the support, the groundwater level outside the pit, and the settlement of the columns, and preprocess the monitoring data. Step S5: Compare the calculated earth pressure and deformation results with the preprocessed monitoring data at the corresponding locations, establish the objective function, use the optimization algorithm to invert and correct the key parameters, substitute the corrected parameters back into the numerical model, update the earth pressure calculation for the next construction step, and form a closed-loop dynamic update of calculation-monitoring-correction-prediction. Step S6: Output the dynamic earth pressure values ​​at each construction stage and depth location based on the corrected model. When the calculated earth pressure exceeds the preset warning value, issue a warning message and guide the site to take corresponding measures.

2. The method for calculating dynamic soil pressure of deep soft soil foundation pit considering time-space effect according to claim 1, characterized in that, In step S1, establishing an initial geological model considering the rheological properties of soft soil includes: Obtain the physical and mechanical parameters of the strata within the influence range of the foundation pit, including the specific gravity. Initial porosity Compression modulus coefficient of lateral pressure at rest Cohesion and internal friction angle ; For deep soft soil layers, the parameters of the soft soil rheological constitutive model are determined by indoor creep tests or empirical data. The soft soil rheological constitutive model is a model that can describe the creep and stress relaxation behavior of soft soil.

3. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 2, characterized in that, The rheological constitutive model for the soft soil is the Burgers model, and its creep equation is expressed as follows: In the formula, for Adaptability at all times For initial stress, For instantaneous elastic modulus, For the delayed elastic modulus, The instantaneous viscosity coefficient, The delayed viscosity coefficient, For time; The parameters of the Burgers model were obtained by fitting triaxial creep test data. , , and .

4. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 1, characterized in that, In step S2, digitizing the foundation pit construction plan and dividing the foundation pit into multiple spatiotemporal units according to the principles of layering and segmentation specifically includes: The entire foundation pit is divided into multiple layers according to depth and multiple segments according to horizontal direction. Each segment and each layer corresponds to a spatiotemporal unit. For each spatiotemporal unit, its spatial coordinates, excavation start and end times, support erection time, and unit geometry are encoded to form a construction schedule.

5. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 4, characterized in that, The geometric dimensions of the spatiotemporal unit include the layer height. and segment length The layer height is determined by the vertical spacing of the supports, and the segment length is determined by the horizontal support spacing or expansion joint division.

6. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 1, characterized in that, In step S3, the dynamic earth pressure calculation numerical model is established using the finite element or finite difference method. The model includes a retaining structure and an internal support system, and assigns physical and mechanical parameters to each stratum and parameters to the soft soil rheological constitutive model. According to the order of the spatiotemporal units, the soil of the corresponding unit is removed step by step in the excavation step, and the support step is activated to apply support and prestress. In each calculation step, the soil rheological effect is considered simultaneously, and the creep deformation and stress relaxation within the corresponding time step of the construction step are calculated.

7. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 6, characterized in that, The calculation process simultaneously considers soil rheological effects, including calculating creep deformation using the creep equation of the Burgers model.

8. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 1, characterized in that, In step S4, the preprocessing includes removing outliers and data smoothing filtering, and calculating the changes of each monitoring point at different times.

9. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 1, characterized in that, In step S5, the calculated earth pressure and deformation results are compared with the preprocessed monitoring data at the corresponding locations to establish an objective function. An optimization algorithm is then used to invert and correct key parameters. Specifically: The objective function is constructed based on the difference between the calculated and measured values; The objective function is optimized using an optimization algorithm, and the corrected key parameters are obtained by inversion. The key parameters include soft soil rheological parameters.

10. The method for calculating dynamic earth pressure in deep soft soil foundation pits considering spatiotemporal effects according to claim 9, characterized in that, The key parameters also include the initial stress field or lateral pressure coefficient of the soil, and the stiffness reduction coefficient of the support structure; the optimization algorithm is a genetic algorithm or a Kalman filter algorithm.

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