Substrate soil deformation prediction method, equipment and medium

Abstract

The embodiment of the invention discloses a foundation soil deformation prediction method and device and a medium. The method comprises the steps that a computational grid and soil parameters of a water-rich stratum foundation pit engineering numerical model are obtained; carrying out numerical calculation on the computational grid to obtain distribution conditions of stress and a seepage field; calculating a compression coefficient in the current soil body state; calculating dynamic pore water pressure and steady-state pore water pressure; and predicting soil deformation according to the compression coefficient, the dynamic pore water pressure and the steady-state pore water pressure. According to the embodiment, the soil deformation in the complex construction process can be accurately predicted.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of civil engineering data processing, and in particular to a method, device and medium for predicting deformation of a base soil. Background Art

[0002] Water-rich strata refer to those strata with high groundwater levels, high water content, and free flow or infiltration of water. Affected by precipitation, topography and other factors, the dynamic changes of groundwater in water-rich strata are relatively large. Deep foundation pits refer to foundation pits with an excavation depth of more than 5 meters (including 5 meters), or projects with particularly complex geological conditions, surrounding environment and underground pipelines, although the excavation depth does not exceed 5 meters.

[0003] Dynamic control technology refers to the real-time monitoring of foundation pit settlement, combined with geological survey data and hydrological conditions, to dynamically adjust support structures and groundwater control measures to ensure stability and safety during foundation pit excavation. It aims to promptly detect and deal with abnormal settlement conditions, and effectively prevent and control the occurrence of foundation pit settlement.

[0004] During the construction process of excavating foundation pits in water-rich strata, it is necessary to pay close attention to the changes in groundwater levels, soil deformation, etc., and adjust the construction plan in a timely manner to achieve dynamic control of the settlement of foundation pit projects in water-rich strata. The primary key to achieving this goal is to accurately predict soil deformation during complex construction processes, providing a basis for dynamically controlling the settlement of underground space.

[0005] In the prior art, patent CN109537569A provides a method for predicting the large deformation settlement process of multi-layer horizontal vacuum reinforced soft fill, and patent CN114781035A provides a method for calculating the degree of consolidation of foundation, but both cannot solve the above technical problems. In view of this, the present invention is proposed. Summary of the invention

[0006] The embodiments of the present invention provide a method, device and medium for predicting deformation of a base soil mass to solve the above technical problems.

[0007] In a first aspect, an embodiment of the present invention provides a method for predicting deformation of a base soil, comprising:

[0008] Obtain the computational grid and soil parameters of the numerical model of foundation pit engineering in water-rich strata;

[0009] Performing numerical calculations on the computational grid to obtain distribution of stress and seepage field;

[0010] Calculate the compression coefficient under the current soil state;

[0011] Calculate dynamic pore water pressure and steady-state pore water pressure;

[0012] predicting soil deformation based on the compressibility, dynamic pore water pressure and steady-state pore water pressure;

[0013] Among them, soil state includes pore water pressure and effective stress;

[0014] The calculation of the compression coefficient under the current soil state includes:

[0015] According to the following formula, calculate the compression coefficient m under the current soil state:

[0016] (2)

[0017] in, represents the initial compression coefficient, which refers to the compression performance of soil under normal conditions; α represents the state sensitivity coefficient, which represents the sensitivity of the compression coefficient to the change of effective stress; It indicates the change in effective stress, which refers to the change in effective stress of soil after construction or water level change; It represents the pore water pressure sensitivity coefficient, which characterizes the response degree of the compressibility factor to the change of pore water pressure; It indicates the change in pore water pressure and refers to the effect of water content change on the compression capacity of soil.

[0018] In a second aspect, an embodiment of the present invention provides an electronic device, the electronic device comprising:

[0019] one or more processors;

[0020] a memory for storing one or more programs,

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the base soil deformation prediction method described in any embodiment.

[0022] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting base soil deformation described in any one of the embodiments.

[0023] Embodiments of the present invention This embodiment provides a method for predicting deformation of base soil, which accurately predicts soil deformation during complex construction processes through numerical simulation, and provides a basis for predicting and controlling the settlement of foundation pit projects in water-rich strata. Specifically, this embodiment introduces the current soil state in the calculation of the compression coefficient, accurately reflects the spatiotemporal changes in the hydraulic-mechanical properties of the soil during the consolidation process, and at the same time, constructs and uses a new state-dependent soil consolidation theoretical model, which can more accurately predict the settlement deformation of the foundation under complex working conditions than traditional models. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 is a flow chart of a method for predicting base soil deformation provided by an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0028] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0029] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0030] In actual engineering applications, water-rich strata can be judged by a variety of methods, such as judging based on stratum lithology, geological structure, on-site observation, historical hydrological data, or judging based on a groundwater level threshold and / or water content threshold greater than a set threshold. The reason for the settlement of the foundation pit engineering structure in the water-rich stratum is the consolidation deformation of the soil around the structure under the action of the upper engineering load, that is, the discharge and compression deformation of water in the soil. The deformation process is directly related to the permeability coefficient of the soil, and the final deformation is directly related to the compression coefficient / modulus. In the embodiment of the present invention, it is found that the state parameters of the on-site soil will continue to change during the complex construction process, and will affect the permeability coefficient and compression coefficient / modulus of the soil, and ultimately affect the consolidation deformation. In order to accurately predict the deformation of the soil during the construction process, a method for predicting the deformation of the base soil provided by the embodiment of the present invention introduces the on-site soil state in the calculation of the permeability coefficient and compression coefficient of the soil, and obtains a state-related permeability coefficient and compression coefficient of the soil, thereby improving the accuracy of the prediction of soil deformation. In order to illustrate the method, the calculation method of the permeability coefficient and the compression coefficient in the prior art is first introduced.

[0031] The soil permeability coefficient and compressibility coefficient in the prior art adopt a constant model or a linear model. Specifically, the permeability coefficient 𝑘 is a parameter that measures the ability of water to flow through soil or rock (permeability). The common expression is Darcy's law:

[0032] (S-1)

[0033] Where q is the flow rate (volume flow rate) through the soil, m³ / s; k is the permeability coefficient, m / s, usually obtained by measurement in the laboratory; A is the cross-sectional area of ​​the soil, m²; Δh is the head difference, m; and L is the length of the seepage path, m.

[0034] Compression factor It refers to the volume change of soil when pressure is applied (how easily the soil compresses under pressure), unit kPa -1 It is generally used to describe the characteristics of soil in a compression stage and is a simplified model of the relationship between pore water pressure and effective stress changes.

[0035] Constant compressibility model:

[0036] (S-2)

[0037] in, is the change in void ratio.

[0038] Linear compression coefficient model:

[0039] (S-3)

[0040] in, and Constants related to material properties, is the effective stress applied on the soil.

[0041] Soil confined deformation model E s The reciprocal of is called the volume compression coefficient of soil m v ,that is:

[0042] (S-4)

[0043] Units and compression factors same.

[0044] Based on the understanding of the above prior art, Figure 1 1 is a flow chart of a method for predicting soil deformation in a basement provided by an embodiment of the present invention. The method is applicable to numerical simulation of soil deformation in foundation pit excavation projects in water-rich strata. Figure 1 As shown, the method specifically includes:

[0045] S110. Obtain a numerical simulation model for a foundation pit excavation project in a water-rich stratum.

[0046] This embodiment targets a specific foundation pit excavation project in a water-rich stratum and adopts a numerical simulation model suitable for complex construction processes to realize the joint action analysis of the superstructure-foundation-base. The model conducts a coupling analysis of soil stress and seepage based on the basic theory of soil mechanics and foundation, and calculates the settlement of the existing underground space structure caused by the upper continued construction. Optionally, the model needs to clarify the geometric shape and material properties of the foundation, subgrade and superstructure, and perform meshing based on finite element analysis or other numerical methods. The numerical calculation will dynamically simulate the soil deformation in the foundation pit excavation project in a water-rich stratum based on the model.

[0047] Furthermore, the basic equation for the superstructure-soil-foundation interaction analysis is as follows:

[0048] (S-5)

[0049] Where [k] is the stiffness matrix of the foundation. If the foundation is a flat plate, it is the stiffness matrix of the foundation plate. If the foundation is a beam-slab type, the stiffness matrices of the beam and slab need to be superimposed. [k s ] is the stiffness matrix of the foundation; [k j ] is the stiffness matrix of the upper structure; [δ] is the deformation of the underlying soil; and [Q] is the load vector. This basic equation can be used to calculate the settlement of the existing underground space structure caused by the upper continued construction.

[0050] Based on the above basic equation, the layered summation method can be used in subsequent operations to calculate the deformation of the soil layer by layer, and finally sum to obtain the total settlement or compression. Specifically, the above basic equations for the analysis of the interaction of the superstructure-foundation-base and the layered summation method are both prior arts, and their basic principles are not repeated here. The following only takes a single layer as an example to illustrate the improved operation of this embodiment in each time step of the numerical simulation.

[0051] S120, generating a computational grid for the numerical simulation model, and setting soil parameters, initial groundwater level conditions, and construction load conditions.

[0052] S130, performing numerical calculations on the computational grid to obtain distribution conditions of stress and seepage field.

[0053] Based on soil mechanics and foundation, numerical calculations are performed on the computational grid to obtain the distribution of stress and seepage field, wherein the stress field includes the effective stress of the soil, and the seepage field includes the pore water pressure of the soil.

[0054] S140. Calculate the permeability coefficient and the compressibility coefficient under the current soil state.

[0055] Specifically, the soil state includes effective stress and pore water pressure. According to the distribution of stress and seepage field in S130, the change of the current soil state relative to the initial soil state can be obtained. This embodiment introduces the current soil state in the calculation of permeability coefficient and compressibility coefficient, and proposes a state-dependent soil hydraulic mechanical characteristics (field soil state) time-varying model, which is different from the traditional constant / linear model. The improved permeability coefficient formula is as follows:

[0056] (1)

[0057] Among them, k is the improved permeability coefficient (m / s), which represents the water permeability of the soil under given conditions; k0 is the initial permeability coefficient (m / s), which represents the permeability coefficient of the soil under standard hydraulic conditions (such as no external pressure and stable water level); α is the state sensitivity coefficient, which represents the sensitivity of the permeability coefficient to the change of effective stress (unitless); It refers to the change in effective stress (kPa), which refers to the change in effective stress of soil after construction or water level change; β is the moisture content sensitivity coefficient, which represents the sensitivity of permeability coefficient to moisture content change (unitless); Refers to the change in moisture content (%), which refers to the change in soil moisture content and can affect permeability.

[0058] The improved compression coefficient formula is as follows:

[0059] (2)

[0060] Where m represents the improved soil compression coefficient (m² / kN), which describes the deformation response capacity of the soil under load; Indicates the initial soil compression coefficient (m² / kN), which refers to the compression performance of the soil under normal conditions; represents the pore water pressure sensitivity coefficient, which characterizes the response of the compressibility factor to the change of pore water pressure (unitless); It represents the change in pore water pressure (kPa), which refers to the effect of water changes on soil compression capacity. The change in each parameter refers to the change at the current moment relative to the initial moment. α represents both the sensitivity of the permeability coefficient to the change in effective stress and the sensitivity of the compression coefficient to the change in effective stress, which are the same.

[0061] The above improved formula is highly nonlinear and naturally has the ability to describe the spatiotemporal variation of the on-site soil state. It has the following advantages: it takes into account the influence of multiple factors, such as the influence of effective stress, moisture content and pore water pressure on the permeability and compressibility coefficient, so that the model can more comprehensively reflect the state of the soil; it has nonlinear characteristics, and by introducing state sensitivity coefficients, it allows the formula to describe the nonlinear response of the soil under different states, providing more accurate simulation predictions; it has dynamic adaptability, and these improved formulas can be dynamically adjusted according to actual working conditions, thereby improving the accuracy and reliability of numerical simulations.

[0062] Furthermore, in the stage of establishing the numerical model, the initial values ​​of the soil permeability coefficient and the compressibility coefficient can be predefined, and the various sensitivity coefficients can be determined through experimental or field test data, or the permeability coefficient and the compressibility coefficient under different conditions can be determined for use in numerical calculations. Among them, the various sensitivity coefficients are related to the properties of the soil. For working conditions with similar soil properties, the same sensitivity coefficient or measurement parameters can be used.

[0063] S150, calculating the dynamic pore water pressure and the steady-state pore water pressure; and calculating the soil deformation according to the compression coefficient, the dynamic pore water pressure and the steady-state pore water pressure.

[0064] This embodiment uses the above improved formula and derives a state-dependent soil consolidation deformation theoretical model based on the mature Terzaghi framework, which truly reflects the soil loading and drainage compression process accompanied by soil state changes.

[0065] Specifically, dynamic pore water pressure The instantaneous pore water pressure (induced by loading, drainage or other external effects during the dynamic change of pore water) is described as follows:

[0066] (3)

[0067] in, represents the initial pore water pressure (kPa), is the coefficient of variation of pore water pressure (unitless), represents the current total stress (kPa), represents the initial total stress (kPa); A represents the time coefficient (1 / s), t represents the time (s); B represents the nonlinear exponent of the dynamic response (unitless).

[0068] Steady-state pore water pressure (The pore water pressure of the soil after it reaches a steady state or drainage equilibrium. This is the pore water pressure when the soil consolidates to a stable state after a period of time, reflecting the long-term response of the soil) is described as follows:

[0069] (4)

[0070] Where C is the stress nonlinearity exponent (unitless), which is used to control the effect of monotonically increasing stress on pore water pressure.

[0071] The soil deformation The description is as follows:

[0072] (5)

[0073] in, represents the initial strain of the soil, Indicates soil compression coefficient (m² / kN), represents the steady-state nonlinear response coefficient.

[0074] Applying formulas (3) and (4) to numerical simulation, the dynamic pore water pressure of soil can be calculated: and steady-state pore water pressure , and then use formula (5) to calculate the soil deformation.

[0075] S160. Perform consolidation analysis based on the permeability coefficient.

[0076] Taking the one-dimensional consolidation equation of soil consolidation process as an example, the equation can be expressed as follows:

[0077] (6)

[0078] Where, u represents pore water pressure; t represents time; It represents the unit weight of soil and is used to introduce gravity effect; Represents the vertical coordinate, referring to the depth in the soil.

[0079] By applying k calculated using the improved formula to this equation, a more accurate consolidation analysis can be achieved.

[0080] It should be noted that in practical applications, only one of the above improved formulas (1) and (2) can be used, or both can be used at the same time. When only one of them is used, the calculation related to the other improved formula in the numerical simulation can use a conventional permeability coefficient or compressibility coefficient, and the numerical simulation method formed thereby belongs to the protection scope of the embodiments of the present invention.

[0081] Furthermore, in order to improve the accuracy of numerical calculations, this embodiment also provides a method of adaptively adjusting the grid density according to the calculation results, using the node adaptive criterion to search in real time for locations such as structures and soil bodies that need to be encrypted, and increase the node density near them to solve highly nonlinear problems. In a specific implementation, in the calculation of each time step, S120 generates a preliminary calculation grid of the soil body of the foundation pit engineering in the water-rich stratum; S130 performs numerical calculations on the preliminary calculation grid to obtain the distribution of stress and seepage field; then after executing S140-S160, the following steps are also included:

[0082] Step 1. Evaluate the error of the numerical solution to determine whether grid adjustment is required. Optionally, if the current numerical calculation is the first calculation, it is assumed that grid adjustment is required. If the current numerical calculation is the second or more calculations, determine whether grid adjustment is required based on the error between the numerical solutions of the most recent calculations. Exemplarily, if the error is less than a set threshold, it indicates that the calculation result has stabilized and there is no need to adjust the grid; if the error is greater than the set threshold, it indicates that the calculation result can still be more accurate, and then proceed to the following steps 2 and 3.

[0083] Step 2: Increase the mesh density in areas where the numerical solution changes more than a certain threshold, and reduce the mesh density in areas where the numerical solution changes less than another threshold. Specifically, when the stress gradient or flow velocity in a certain area changes greatly (for example, greater than the first threshold), it indicates that the area requires more calculation accuracy, so the mesh in the area is encrypted; while in areas where the stress or flow velocity changes gently (for example, less than the second threshold) or is unimportant, the mesh density is reduced to optimize the use of computing resources. Among them, the first threshold is greater than the second threshold.

[0084] Optionally, the nodes can be encrypted by using isoparametric transformation based on the background unit, that is, the nodes are encrypted on the isoparametric unit, and then the newly added nodes are mapped to the original background unit. In order to improve the calculation efficiency, the head value of the original background unit vertex can be used to linearly assign values ​​to the newly added nodes, so as to continue the calculation of the current time step. At the same time, in order to reduce the bandwidth of the matrix to improve the calculation efficiency, the node numbering can be optimized so that the node numbers in the support domain of the calculation point are similar. Optionally, a reference point can be selected, and the distance from the reference point can be used as the basis for the size of the node number. In addition, it may be necessary to set an encrypted transition zone to avoid matrix singularity caused by disparity in node density.

[0085] Step 3: recalculate numerically based on the adjusted grid until the error of the numerical solution before and after the adjustment is less than the set threshold. Specifically, after completing the grid adaptive adjustment in step 2, return to S130 to recalculate numerically on the adjusted calculation grid, update the stress and seepage field, and re-execute S140-S160, as well as steps 1 to 3, and repeat this cycle until the error between the numerical solutions calculated in the most recent times is less than the set threshold.

[0086] The final calculation results can be used to perform the layered summation method to obtain the total soil settlement.

[0087] In summary, compared with the method of this embodiment, conventional soil stress-seepage coupling analysis is usually performed based on a fixed grid, which has the following main disadvantages:

[0088] 1) Fixed grid limitation: Once the grid is generated, the distribution distance and density of nodes will no longer change, which may lead to inaccurate calculations in some areas and over-calculation in other areas, resulting in a waste of resources.

[0089] 2) Low computational efficiency: Faced with complex nonlinear soil stress and water flow distribution, fixed grids can hardly capture important details and often require a higher number of nodes to improve accuracy, resulting in longer computational time.

[0090] 3) Insufficient support for complex geometry: When dealing with complex soils and boundary conditions, fixed grids are not flexible enough to adapt to changes in actual conditions.

[0091] The adaptive grid adjustment method in this embodiment has the following advantages:

[0092] 1) Improve calculation accuracy: By increasing the node density in areas with large changes in stress and flow velocity, important physical phenomena can be captured more accurately, thereby greatly reducing errors.

[0093] 2) Optimize computing resources: Reduce node density in unimportant areas to avoid unnecessary calculations, making more efficient use of computing resources and improving computing efficiency.

[0094] 3) Dynamic adaptability: This method can dynamically adjust the grid during the calculation process, so it can better adapt to the changes in soil and water flow. Especially when performing nonlinear analysis, it can continuously optimize the calculation area.

[0095] 4) Enhanced ability to handle complex problems: The adaptive grid method can more flexibly handle complex soil geometry, boundary conditions, and stress-seepage interactions, and is suitable for complex situations in actual engineering.

[0096] In summary, this embodiment provides a method for predicting deformation of base soil, which accurately predicts the consolidation deformation of soil in a complex construction process through numerical simulation, and provides a basis for predicting and controlling the settlement of foundation pit engineering in water-rich strata. Specifically, this embodiment can achieve the following beneficial effects:

[0097] 1) In the calculation of the permeability coefficient and the compressibility coefficient, this embodiment introduces the current soil state, accurately reflects the spatiotemporal changes of the hydraulic-mechanical properties of the soil during the consolidation process, and at the same time, constructs and uses a new state-dependent soil consolidation theoretical model, which can more accurately predict the settlement and deformation of the foundation under complex working conditions than the traditional model. The error of the entire construction process is within 4.0%, while the error of the traditional model can be as high as about 40%.

[0098] 2) This embodiment takes into account the temporal and spatial correlation of stratum water level changes and structural loads in numerical simulation, and realizes the stress-seepage analysis of existing underground space structures under the action of upper loads through the analysis method of superstructure-foundation-foundation interaction. In numerical calculation, the node adaptive grid adjustment method is introduced to improve the accuracy and speed of stress-seepage coupling analysis, and realize low-cost, high-efficiency and accurate calculation.

[0099] Furthermore, based on the prediction results provided by the above method, two aspects of construction measures can be implemented to dynamically control underground airborne settlement at the millimeter level.

[0100] On the one hand, the millimeter-level advanced combined lowering / water-stopping construction technology is used to control the settlement of underground space within the millimeter level before the construction load is applied. First, based on the precise positioning, installation and operation monitoring of water piles, the rough construction problems in the past are overcome, and the high-quality and non-broken construction of water-stop piles is ensured in water-rich strata in combination with post-grouting reinforcement and post-tensioning slow-setting main reinforcement.

[0101] On the other hand, through the millimeter-level water level-structural load synchronous lifting construction technology, the settlement of the underground space is controlled within the millimeter level during the application of the building load. First, through the construction load segmentation and layered unitization technology, the application of the building load is segmented and evenly spread to the existing underground space structure, and the application of the building load is layered. Through the prediction of the joint action analysis platform and on-site measurement, it is ensured that the settlement increment of the underground structure after each layer of load is applied is within the millimeter level. At the same time, through the graded water level dynamic feedback lifting technology, the water level is raised to a reasonable height before each layer of load is applied, and fine-tuned after each layer of load is applied. Similarly, through the prediction of the joint action analysis platform and on-site measurement, it is ensured that the total settlement caused by each layer of load is within the millimeter level and reaches stability.

[0102] Figure 2 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 2 As shown, the device includes a processor 60, a memory 61, an input device 62 and an output device 63; the number of processors 60 in the device can be one or more. Figure 2 A processor 60 is taken as an example; the processor 60, the memory 61, the input device 62 and the output device 63 in the device can be connected by a bus or other means. Figure 2 The example of connecting through bus is taken in the following.

[0103] The memory 61 is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the method for predicting deformation of base soil in the embodiment of the present invention. The processor 60 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 61, that is, realizing the above-mentioned method for predicting deformation of base soil.

[0104] The memory 61 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 61 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 61 may further include a memory remotely arranged relative to the processor 60, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0105] The input device 62 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 63 may include a display device such as a display screen.

[0106] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method for predicting base soil deformation of any embodiment is implemented.

[0107] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0108] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0109] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0110] Computer program code for performing the operation of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as C or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting deformation of a base soil, characterized in that: include: Obtain the computational grid and soil parameters of the numerical model of foundation pit engineering in water-rich strata; Performing numerical calculations on the computational grid to obtain distribution of stress and seepage field; Calculate the compression coefficient under the current soil state; Calculate dynamic pore water pressure and steady-state pore water pressure; predicting soil deformation based on the compressibility, dynamic pore water pressure and steady-state pore water pressure; Among them, soil state includes pore water pressure and effective stress; The calculation of the compression coefficient under the current soil state includes: According to the following formula, calculate the compression coefficient m under the current soil state: （2） in, represents the initial compression coefficient, which refers to the compression performance of soil under normal conditions; α represents the state sensitivity coefficient, which represents the sensitivity of the compression coefficient to the change of effective stress; It indicates the change in effective stress, which refers to the change in effective stress of soil after construction or water level change; It represents the pore water pressure sensitivity coefficient, which characterizes the response degree of the compressibility factor to the change of pore water pressure; It indicates the change in pore water pressure and refers to the effect of water content change on the compression capacity of soil.

2. The method according to claim 1, characterized in that The calculation of dynamic pore water pressure and steady-state pore water pressure includes: The dynamic pore water pressure is calculated according to the following formula: : （3） in, represents the initial pore water pressure, represents the coefficient of variation of pore water pressure, represents the current total stress, represents the initial total stress; A represents the time coefficient, t represents the time; B represents the nonlinear exponent of the dynamic response.

3. The method according to claim 1, characterized in that The calculation of dynamic pore water pressure and steady-state pore water pressure includes: The steady-state pore water pressure is calculated according to the following formula: : （4） in, represents the initial pore water pressure; C represents the stress nonlinearity index, which controls the influence of monotonically increasing stress on the pore water pressure; represents the current total stress, represents the initial total stress.

4. The method according to claim 1, characterized in that: The method of predicting soil deformation according to the compression coefficient, dynamic pore water pressure and steady-state pore water pressure includes: The soil deformation is predicted according to the following formula: : （5） in, represents the initial strain of the soil, represents the compression factor, represents the steady-state nonlinear response coefficient, represents the effective stress, represents the dynamic pore water pressure, Represents the steady-state pore water pressure.

5. The method according to claim 1, characterized in that: The method of obtaining the computational grid and soil parameters of the numerical model of the foundation pit engineering in the water-rich stratum comprises: obtaining the preliminary computational grid and soil parameters of the numerical model of the foundation pit engineering in the water-rich stratum; After predicting soil deformation according to the compression coefficient, dynamic pore water pressure and steady-state pore water pressure, the method further includes: determining whether grid adjustment is required based on an evaluation of the error of the numerical solution; if necessary, increasing the grid density in an area where the change in the numerical solution is greater than a first threshold, and reducing the grid density in an area where the change in the numerical solution is less than a second threshold, and re-performing numerical calculations based on the adjusted grid until the error in the numerical solution before and after the adjustment is less than a third threshold.

6. The method according to claim 1, characterized in that Also includes: Based on the prediction results, the settlement of underground space is controlled at millimeter level before the building load is applied.

7. The method according to claim 1, characterized in that Also includes: Based on the prediction results, the settlement of underground space is controlled at millimeter level during the application of building loads.

8. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the base soil deformation prediction method described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the method for predicting base soil deformation described in any one of claims 1-7 is implemented.

Images