Construction method of one-side formwork covering soil and reverse pressure of outer hanging plate

Abstract

This invention provides a construction method for single-sided formwork with external cladding and soil backfilling, relating to the field of deep foundation pit support technology. This method includes S1: constructing a three-dimensional geological model based on geotechnical investigation data, determining critical excavation parameters through numerical analysis, and generating an excavation safety threshold report; S2: based on the excavation safety threshold report, designing a lightweight formwork system using a structural optimization algorithm, and installing a reinforcing layer to enhance interface bonding, forming a high-precision formwork system that meets verticality control standards. By constructing a three-dimensional geological model based on geotechnical investigation data and determining excavation parameters using numerical analysis, the support structure design accurately matches geological conditions, avoiding redundancy or inadequacy in support caused by empiricism. The use of a structural optimization algorithm to design a lightweight formwork system and pre-install a reinforcing layer improves the formwork stiffness and interface bonding strength, ensuring the morphological stability of the single-sided formwork under soil backfilling conditions.

Description

Technical Field

[0001] This invention relates to the field of deep foundation pit support technology, specifically to the construction method of single-sided formwork with external hanging plate and soil backfilling. Background Technology

[0002] The field of deep foundation pit support technology involves systematic methods for maintaining the stability of pit walls during underground engineering excavation. The core of this field lies in balancing earth pressure, controlling deformation, and preventing damage to the surrounding environment. This area encompasses support structure design (such as pile banks, diaphragm walls, and internal support systems), groundwater control (dewatering, cutoff walls), and deformation monitoring and early warning technologies. It requires the comprehensive application of geotechnical mechanics, structural engineering, and construction machinery. Among these, the single-sided formwork with backfill and counter-pressure construction method refers to a foundation pit support construction method that uses a single-sided formwork system installed on the side of the support piles, utilizing in-situ pre-reserved soil to form a counter-pressure backfill by layered compaction, thereby balancing the lateral pressure of concrete pouring. This method is used to replace traditional internal support systems and solve the problem of formwork deformation control during the pouring of concrete outer walls in deep foundation pits.

[0003] Existing technologies rely on empirical formulas to determine excavation parameters, resulting in poor adaptability to geological conditions and a high risk of support structure instability or over-design. The formwork system lacks structural optimization and interface reinforcement measures, making it prone to excessive deformation under backfill pressure, leading to insufficient flatness of the concrete walls. Direct backfilling in situ without soil property improvement results in significant strength dispersion after compaction, making it difficult to form a uniform and stable counter-pressure body. Fixed backfill thickness in layers fails to dynamically respond to different soil layer characteristics, causing uneven pressure distribution after compaction and resulting in localized bulging of the formwork. Concrete temperature control relies on manual experience, leading to inconsistent crack control and frequent repairs that prolong the construction period. The lack of targeted reinforcement in stress concentration areas of the formwork allows for cumulative deformation in high lateral pressure areas, triggering a chain reaction of failures. The monitoring of backfill pressure and formwork deformation is disconnected, lacking a rapid compensation mechanism when displacement exceeds limits, resulting in significant lag in deformation control. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a construction method for single-sided formwork with external cladding panels and soil backfilling and counter-pressure. This method solves the problems of existing technologies relying on empirical formulas to determine excavation parameters, poor adaptability to geological conditions, easy instability or over-design of support structures, lack of structural optimization and interface reinforcement measures for the formwork system, and easy excessive deformation under soil backfilling and counter-pressure, resulting in insufficient flatness of the concrete wall.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a construction method for single-sided formwork with soil backing and counter-pressure on external cladding panels, comprising the following steps:

[0006] S1: Construct a three-dimensional geological model based on geotechnical investigation data, determine critical excavation parameters through numerical analysis methods, and generate an excavation safety threshold report;

[0007] S2: Based on the excavation safety threshold report, a lightweight template system is designed using a topology optimization algorithm. The template is installed using a laser positioning system, and an reinforcement layer is configured to form a high-precision template system that meets the verticality and stiffness control standards.

[0008] S3: Based on the characteristics of the reserved soil, a cementitious improvement material is prepared and uniformly mixed to generate activated soil with a predetermined strength;

[0009] S4: Based on the high-precision template system and activated soil, the layered backfill thickness is dynamically set through the prediction model, and the backfill is compacted to the target compaction degree by the navigation compaction equipment, generating a compaction degree distribution map that reflects the pressure balance state;

[0010] S5: Based on the pre-embedded temperature monitoring network in the compaction distribution map, an adaptive control algorithm is used to regulate the cooling system to generate low-heat-damage concrete that meets the crack control requirements;

[0011] S6: Based on the stress distribution of the template, locate key areas, apply prestress calculated according to the stress ratio, and generate a tension matrix that can offset part of the concrete lateral pressure.

[0012] S7: Based on the compaction distribution map and tension matrix, the displacement is verified through a coupled analysis model, and a counter-pressure performance report that meets the deformation control requirements is generated in real time.

[0013] S8: Based on the temperature change law of the low heat hazard concrete, a prediction algorithm is used to determine the curing parameters and generate a strength growth curve that reflects the strength development law;

[0014] S9: Based on the strength growth curve, remove the overburden according to the segmented excavation strategy, and generate an acceptance report for the support structure that meets the flatness standard through three-dimensional scanning.

[0015] Preferably, step S1 includes the following steps:

[0016] S101: Based on borehole data from geotechnical exploration, a stratigraphic interface distribution model is generated using the Kriging spatial interpolation algorithm, and a geological spatial surface model is generated.

[0017] S102: Based on the geological space surface model, the soil shear strength parameters are calculated using the finite element strength reduction method to generate a set of soil strength parameters;

[0018] S103: Based on the soil strength parameter set, the critical excavation depth is solved using the slope stability numerical simulation method, and an excavation stability assessment report is generated.

[0019] S104: Based on the excavation stability assessment report, the deformation control threshold is determined by the Monte Carlo risk analysis method, and an excavation safety threshold report is generated.

[0020] Preferably, step S2 includes the following steps:

[0021] S201: Based on the excavation safety threshold report, a topology optimization algorithm is used to design the spatial configuration of the template ribs and generate a rib topology configuration diagram;

[0022] S202: Based on the topological configuration diagram of the rib plate, a positioning and calibration template system is generated by installing template units pre-embedded with geosynthetic materials through a laser positioning system.

[0023] S203: Based on the aforementioned positioning and calibration template system, the template support spacing is dynamically adjusted using strain energy density analysis to achieve stiffness enhancement and generate a stiffness-enhanced support system.

[0024] S204: Based on the aforementioned stiffness-enhanced support system, a high-precision template system is generated by verifying the template verticality error according to the standard of ≤2‰ using an inclination sensing device.

[0025] Preferably, step S3 includes the following steps:

[0026] S301: Based on the physical properties of the reserved soil, the particle size distribution analysis method is used to determine the soil composition characteristics and generate the soil distribution characteristic curve.

[0027] S302: Based on the soil gradation characteristic curve, the cementitious material mixing ratio is calculated by response surface optimization method to generate an activator mixing scheme;

[0028] S303: Based on the activator formulation scheme, the improved soil is mixed using a mechanical forced mixing process, and a mixing uniformity test report is generated;

[0029] S304: Based on the aforementioned mixing uniformity test report, the engineering performance of the soil is verified by the standard compaction test method to generate activated soil.

[0030] Preferably, step S4 includes the following steps:

[0031] S401: Based on the compaction characteristics of the activated soil, a long short-term memory neural network model is used to predict compaction parameters and generate a dynamic layer thickness control table.

[0032] S402: Based on the dynamic layer thickness control table, the compaction path planning is performed by the augmented reality navigation device to generate a mechanical compaction trajectory log;

[0033] S403: Based on the mechanical compaction trajectory log, the pressure monitoring data is analyzed using a kernel density estimation algorithm to generate a real-time pressure distribution map;

[0034] S404: Based on the real-time pressure distribution map, the compaction parameters are dynamically adjusted by the programmable logic controller to generate a compaction degree distribution map.

[0035] Preferably, step S5 includes the following steps:

[0036] S501: Based on the compaction distribution map, deploy a distributed optical fiber temperature sensing network to generate a temperature monitoring network system.

[0037] S502: Based on the data from the temperature monitoring network system, a proportional-integral-derivative fuzzy adaptive algorithm is used to generate control commands and a dynamic temperature control command set is generated.

[0038] S503: Based on the dynamic temperature control instruction set, maintain the temperature field balance through the variable frequency hydraulic control system and generate a temperature field balance verification report.

[0039] S504: Based on the temperature field balance verification report, a pouring speed optimization model is used to control the concrete pouring process to generate low-heat-damage concrete.

[0040] Preferably, step S6 includes the following steps:

[0041] S601: Based on template strain monitoring data, the principal stress trace analysis method is used to identify high stress areas and generate a stress concentration area distribution map.

[0042] S602: Based on the stress concentration zone distribution map, install the anchor cable guide device using spatial positioning technology to generate the anchor cable sleeve positioning matrix;

[0043] S603: Based on the anchor sleeve positioning matrix, a steel strand pre-tensioning system is established using a graded tensioning process to generate a prestressed initial tensioning system;

[0044] S604: Based on the prestressed initial tensioning system, proportional prestress is applied through a hydraulic synchronous control algorithm to generate a tensioning matrix.

[0045] Preferably, step S7 includes the following steps:

[0046] S701: Based on the compaction distribution map and tension matrix, the theoretical displacement is calculated using a soil-structure coupled numerical model to generate a theoretical displacement field cloud map;

[0047] S702: Based on the theoretical displacement field cloud map, actual displacement data is collected through the total station monitoring system to generate a measured displacement dataset;

[0048] S703: Based on the measured displacement dataset, the least squares model verification method is used to analyze the displacement error and generate displacement error correction coefficients;

[0049] S704: Based on the displacement error correction coefficient, a verification conclusion is generated through a threshold determination mechanism, and a counter-pressure performance evaluation report is generated.

[0050] Preferably, step S8 includes the following steps:

[0051] S801: Based on the temperature data of the low-heat-hazard concrete, the support vector machine regression algorithm is used to predict the development law of hydration heat and generate a hydration heat peak prediction report.

[0052] S802: Based on the hydration heat peak prediction report, a maintenance strategy is formulated through a fuzzy decision model to generate a dynamic maintenance control scheme;

[0053] S803: Based on the dynamic maintenance control scheme, a wireless sensor network is used to monitor the surface humidity status and generate a humidity maintenance status record.

[0054] S804: Based on the humidity maintenance status record, the intensity development law is calculated using the maturity theory model, and an intensity growth curve is generated.

[0055] Preferably, step S9 includes the following steps:

[0056] S901: Based on the intensity growth curve, the piecewise function optimization method is used to determine the excavation strategy and generate a skip-cell excavation zoning plan.

[0057] S902: Based on the skip-cell excavation zoning plan, the overburden is removed by mechanized layered excavation process to generate an earthwork excavation progress control table.

[0058] S903: Based on the earthwork excavation progress control table, use three-dimensional laser scanning technology to collect structural surface data and generate a structural surface point cloud model.

[0059] S904: Based on the point cloud model of the structure surface, the flatness deviation is calculated using the minimum distance algorithm, and an acceptance report for the support structure is generated.

[0060] This invention provides a construction method for single-sided formwork with soil backing and counter-pressure on external cladding panels. It has the following beneficial effects:

[0061] This invention constructs a three-dimensional geological model based on geotechnical investigation data and uses numerical analysis methods to determine excavation parameters, enabling the support structure design to accurately match geological conditions and avoiding redundancy or inadequacy in support due to empiricism. It employs structural optimization algorithms to design a lightweight formwork system with pre-installed reinforcement layers, improving formwork stiffness and interface bonding strength, ensuring the morphological stability of the single-sided formwork under backfill pressure conditions. Material ratio optimization methods improve soil engineering properties, enhancing the shear strength and compaction efficiency of the backfill, forming a stable and reliable backfill medium. A predictive model dynamically sets the layered backfill thickness, and navigation compaction technology achieves pressure balance control. This significantly improves the accuracy of concrete lateral pressure offsetting, embeds a temperature monitoring network and applies an adaptive control strategy to regulate hydration temperature rise, effectively suppressing the formation of temperature cracks. It applies proportional prestress based on the stress distribution of the formwork, and forms a composite bearing system in conjunction with the backfill counterpressure, reducing the risk of local stress concentration. It uses coupled analysis of backfill pressure and prestress data to verify displacement, monitors deformation development in real time, ensures controllable deformation of the support system, predicts strength development based on the concrete temperature change law, guides the selection of formwork removal timing and adjustment of curing strategies, accelerates construction progress, and uses three-dimensional scanning technology to quantify the structural appearance quality, realizing the digitalization and standardization of support structure acceptance. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of the main steps of the present invention;

[0063] Figure 2 This is a detailed schematic diagram of S1 of the present invention;

[0064] Figure 3 This is a detailed schematic diagram of S2 of the present invention;

[0065] Figure 4 This is a detailed schematic diagram of S3 of the present invention;

[0066] Figure 5 This is a detailed schematic diagram of S4 of the present invention;

[0067] Figure 6 This is a detailed schematic diagram of S5 of the present invention;

[0068] Figure 7 This is a detailed schematic diagram of S6 of the present invention;

[0069] Figure 8 This is a detailed schematic diagram of S7 of the present invention;

[0070] Figure 9 This is a detailed schematic diagram of S8 of the present invention;

[0071] Figure 10 This is a detailed schematic diagram of S9 of the present invention. Detailed Implementation

[0072] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0073] Example:

[0074] like Figure 1-10 As shown in the figure, this invention provides a construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels, including the following steps:

[0075] Design phase;

[0076] S1: Construct a three-dimensional geological model based on geotechnical investigation data, determine critical excavation parameters through numerical analysis methods, and generate an excavation safety threshold report;

[0077] A three-dimensional geological model is constructed based on geotechnical investigation data. Critical excavation parameters (such as safe slope ratio and support stiffness) are determined through numerical analysis, and an excavation safety threshold report is generated.

[0078] S2: Based on the excavation safety threshold report, a lightweight template system is designed using a structural optimization algorithm, and an enhanced layer with an enhanced interface is installed to form a high-precision template system that meets the verticality control standard.

[0079] Based on the safety threshold report, a lightweight template system is designed using a structural optimization algorithm, and a reinforcing layer (such as geosynthetic material or fiber-reinforced composite material) is installed to enhance the interface bonding, forming a high-precision template system that meets the verticality control standard.

[0080] The reinforcing layer is made of geosynthetic material, high-strength polyester grid + anti-aging coating, with tensile strength ≥50kN / m and elongation ≤5%; fiber-reinforced composite material, carbon fiber / glass fiber cloth + epoxy resin, with interlaminar shear strength ≥20MPa and thickness 0.5–2mm. Cementitious base: silicate cement (40–60%), active admixtures: fly ash (20–30%), slag powder (10–20%), activator: water glass modulus 1.8–2.2 (dosage 3–8%).

[0081] Construction preparation and implementation phase;

[0082] S3: Based on the characteristics of the reserved soil, a cementitious improvement material is prepared and uniformly mixed to generate activated soil with a predetermined strength;

[0083] Based on the characteristics of the reserved soil, a cementitious amendment material (such as a silicate cement-based cementitious system) is prepared and uniformly mixed to generate activated soil with a predetermined strength.

[0084] S4: Based on a high-precision template system and activated soil, the backfill thickness is dynamically set through a prediction model, and then compacted to the target compaction degree by a navigation compaction device, generating a compaction degree distribution map that reflects the pressure balance state;

[0085] Based on a high-precision template system and activated soil, the backfill thickness is dynamically set by a prediction model, and then compacted to the target compaction degree by a navigation compaction device, generating a compaction degree distribution map.

[0086] S5: Based on the compaction distribution map and the embedded temperature monitoring network, an adaptive control algorithm is used to regulate the cooling system to generate low-heat-damage concrete that meets the crack control requirements.

[0087] Based on the compaction distribution map and the embedded temperature monitoring network, an adaptive control algorithm is used to regulate the cooling system and generate low-heat-damage concrete.

[0088] S6: Based on the stress distribution of the template, locate key areas, apply prestress calculated according to the stress ratio, and generate a tension matrix that can offset part of the concrete lateral pressure.

[0089] Prestress is applied simultaneously during concrete pouring. By monitoring the stress distribution of the formwork in real time, the tension is adjusted in stages (for example, applying 50% initial prestress when the concrete is poured to 30% height, supplementing to 80% when it is poured to 70% height, and adjusting to 100% after final setting). The application of prestress must match the concrete setting process to avoid excessive tension in the early stage, which could lead to structural damage.

[0090] Real-time monitoring phase;

[0091] S7: Based on the compaction distribution map and tension matrix, the displacement is verified through a coupled analysis model, and a counter-pressure performance report that meets the deformation control requirements is generated in real time.

[0092] Maintenance and acceptance phase;

[0093] S8: Based on the temperature change law of low heat hazard concrete, a prediction algorithm is used to determine the curing parameters and generate a strength growth curve that reflects the strength development law;

[0094] S9: Based on the strength growth curve, the overburden is removed according to the segmented excavation strategy, and a support structure acceptance report that meets the flatness standard is generated by three-dimensional scanning.

[0095] S1 includes the following steps:

[0096] S101: Based on borehole data from geotechnical exploration, a stratigraphic interface distribution model is generated using the Kriging spatial interpolation algorithm, and a geological spatial surface model is generated.

[0097] Based on the coordinate locations and corresponding elevation data of multiple exploration boreholes, a geological spatial surface model is constructed using the Kriging spatial interpolation algorithm. This algorithm involves calculating the spatial variability function, including setting the range parameter, nugget value, and sill value (exemplary values ​​can be 50m, 0.2, and 1.5, respectively), and determining the grid point weight coefficients through a semivariogram model. The algorithm then interpolates the surface model across a preset grid area (exemplary grid size is 10m × 10m, and the number of output grid points can be up to 200). It is adaptable to different geological conditions: for sandy soil strata, the range parameter can be increased based on permeability to reflect homogeneity; for clay strata, the nugget value can be adjusted to handle local variations; for composite strata, a layered interpolation strategy is adopted to independently handle the interfaces of each sub-stratum. The grid size and variability function parameters can be dynamically optimized based on stratigraphic complexity, for example, reducing the grid size in composite strata to improve resolution.

[0098] S102: Based on the geological space surface model, the soil shear strength parameters are calculated by the finite element strength reduction method to generate a set of soil strength parameters;

[0099] A three-dimensional finite element mesh model is established based on a geological spatial surface model. Initial soil shear strength parameters (such as cohesion and internal friction angle) are assigned, and the strength reduction method is applied iteratively until the critical state is reached, generating a set of soil strength parameters. This includes setting an initial reduction coefficient and gradually adjusting it (the exemplary reduction coefficient F starts from 1.0), and recording the reduced parameters. This step can be adapted to different foundation pit depths: for shallow foundation pits (e.g., 5m), the mesh cell size can be simplified (the exemplary size of 1m×1m can be optimized to a larger size to accelerate the calculation); for medium-depth foundation pits (e.g., 10m), the mesh needs to be refined and the number of iteration steps increased; for deep foundation pits (e.g., 15m), the initial parameters are adjusted in conjunction with a creep model or heterogeneous soil. For different geological conditions, the initial φ value of sandy soil strata can be optimized based on standard tests, while composite strata need to be assigned parameters layer by layer and reduced independently.

[0100] S103: Based on the soil strength parameter set, the critical excavation depth is solved using the slope stability numerical simulation method, and an excavation stability assessment report is generated.

[0101] Based on the soil strength parameter set, under a preset excavation slope, a slope stability numerical simulation method (such as the circular arc sliding method) is used to calculate the safety factor, and an iterative algorithm (such as the bisection method) is used to solve for the critical excavation depth, generating an assessment report (including the calculation of reserved earthwork volume). This includes setting a safety factor threshold and adjusting the excavation depth (exemplary depth values ​​such as 4.0m or 5.0m). This step can be adapted to different foundation pit depths: for a 5m shallow foundation pit, the iteration step size can be increased to simplify the calculation; for a 10m medium foundation pit, the step size needs to be reduced and combined with a groundwater influence model; for a 15m deep foundation pit, the finite element limit equilibrium method or multi-sliding surface search is introduced. For different geological conditions, the sliding surface algorithm can be optimized for sandy soil strata to reflect high permeability, and for composite strata, the slope setting and earthwork volume formula need to be adjusted (the exemplary formula V=0.5×H×L can be extended to nonlinear calculation).

[0102] S104: Based on the excavation stability assessment report, the deformation control threshold is determined by the Monte Carlo risk analysis method, and an excavation safety threshold report is generated.

[0103] Based on the critical excavation depth, a probability distribution of soil strength parameters is defined (e.g., a normal distribution). Multiple sets of parameter samples are randomly generated using the Monte Carlo method to simulate excavation conditions and statistically analyze the probability of displacement exceeding limits. The displacement threshold is iteratively adjusted to determine the warning value, generating a safety threshold report. This process includes sample generation and probability statistics (e.g., 1000 samples). This step is adaptable to different excavation depths: for a 5m excavation, the number of samples can be reduced to improve efficiency; for 10m or 15m deep excavations, the number of samples is increased and a time-dependent deformation model is introduced. For different geological conditions, the displacement threshold can be adjusted based on permeability for sandy soil strata; for clay strata, a non-normal distribution (e.g., log-normal) needs to be considered; for composite strata, layered probability analysis is implemented, and the influence of the support structure is integrated to expand the protection range.

[0104] Preferably, S2 includes the following steps:

[0105] S201: Based on the excavation safety threshold report, a topology optimization algorithm is used to design the spatial configuration of the template ribs and generate a rib topology configuration diagram;

[0106] Based on the critical excavation depth and reserved earthwork volume data, within the preset template design domain (the exemplary size can be a rectangular area), a variable density topology optimization algorithm is adopted, with maximizing stiffness as the objective function and material volume fraction as the constraint condition (the exemplary upper limit can be 0.4). Through finite element mesh generation and element pseudo-density iterative calculation, a spatial configuration diagram of the rib plate is generated (the exemplary configuration is a honeycomb distribution). In sandy soil strata, due to the smaller lateral pressure, the upper limit of the volume fraction can be reduced to optimize the material usage; in clay soil strata, the rib plate density needs to be increased to resist creep deformation; in composite strata, a zonal optimization strategy is adopted to independently enhance the rib plate thickness for weak sub-layers; for 5m shallow foundation pits, the number of meshes can be simplified (the exemplary 12,000 elements can be reduced); for 10m medium foundation pits, the minimum rib plate thickness needs to be increased (the exemplary 12mm can be increased); for 15m deep foundation pits, multi-objective optimization is introduced (taking into account both stiffness and fatigue resistance).

[0107] S202: Based on the topological configuration diagram of the rib plate, a positioning and calibration template system is generated by installing template units pre-embedded with geosynthetic materials through a laser positioning system.

[0108] Based on the coordinate data of the rib openings, a laser positioning device (such as a total station) is used to generate benchmark points. Geosynthetic materials (exemplarily biaxially oriented polypropylene geogrids) are pre-embedded into the template units. Through real-time coordinate deviation measurement and adjustment (exemplary deviation threshold ≤ 1mm), multi-unit assembly is completed to form a calibration system. Due to the tendency of sandy soil layers to collapse holes, the tensile strength of the geogrid needs to be increased (exemplary 50kN / m can be increased) and the opening spacing needs to be reduced. For clay soil layers, the geogrid pretension can be optimized to compensate for shrinkage deformation. For composite strata, a layered embedding strategy is adopted, matching differentiated geogrid parameters for different lithological areas. For 5m foundation pits, the number of positioning control points can be reduced. For 10m foundation pits, the cumulative error threshold needs to be reduced (exemplary 1.8mm needs to be strictly controlled). For 15m deep foundation pits, dynamic calibration of the BIM model is introduced, and a temperature deformation compensation algorithm is added.

[0109] S203: Based on the aforementioned positioning and calibration template system, the template support spacing is dynamically adjusted using strain energy density analysis to achieve stiffness enhancement and generate a stiffness-enhanced support system.

[0110] Apply a load (exemplary uniformly distributed load value) to the template system, calculate the regional strain energy density distribution, and iteratively adjust the spacing between the primary and secondary supports by comparing with a preset threshold (exemplary Uth value) until the stiffness requirement (exemplary system stiffness value) is met. For sandy soil strata, due to the dispersed load transfer, the secondary support spacing threshold can be increased; for clay soil strata, the primary support spacing threshold needs to be reduced to resist local settlement; for composite strata, implement zoned control, and independently densify the supports in high strain energy areas. For 5m foundation pits, the load conditions can be simplified (exemplary single condition can be expanded into a combination of multiple conditions); for 10m foundation pits, the stiffness target value needs to be increased (exemplary 2.6kN / mm can be increased); for 15m deep foundation pits, prestressed supports are introduced and coupled with a groundwater pressure model.

[0111] S204: Based on the aforementioned stiffness-enhanced support system, a high-precision template system is generated by verifying the template verticality error according to the standard of ≤2‰ using an inclination sensing device.

[0112] Inclination sensors (5 sensors in an example) are deployed at key nodes of the support system to measure multi-dimensional inclination data. The deviation values ​​are corrected to within a preset threshold (θmax = 0.1° in an example) by an adjustment device (slanted bracing screw in an example). The system outputs a high-precision system with verticality meeting the standard. For sandy soil layers, the sensor sampling frequency needs to be increased to cope with vibration interference. For clay soil layers, a creep inclination compensation algorithm is introduced. For composite strata, a differential threshold strategy is adopted to set more stringent verticality requirements for the boundary area. The number of sensors can be reduced for 5m foundation pits. For 10m foundation pits, the angle-displacement conversion coefficient needs to be optimized (0.005mm / ° in an example, which can be dynamically adjusted). For 15m deep foundation pits, an AI prediction model is integrated to pre-adjust support parameters based on historical data to suppress cumulative deviations.

[0113] S3 includes the following steps:

[0114] S301: Based on the physical properties of the reserved soil, the particle size distribution analysis method is used to determine the soil composition characteristics and generate the soil distribution characteristic curve.

[0115] Sampling and sieving of the reserved soil in the foundation pit (exemplary screen aperture sequence) is performed to calculate the particle size passing rate and gradation parameters (such as the coefficient of uniformity Cu and the coefficient of curvature Cc), generating characteristic curves. For sandy soil layers, sieving can be extended to finer particle sizes (such as 0.05 mm) to reflect the silt content; clay soil layers require the addition of a clay content detection module; composite strata are subjected to layered sieving, and gradation curves for each sublayer are generated independently. For 5m foundation pits, the number of sieving grades can be reduced; for 10m foundation pits, gradation parameters need to be optimized by combining in-situ permeability tests; for 15m deep foundation pits, a probabilistic statistical model is introduced to handle the spatial variability of the soil.

[0116] S302: Based on the soil gradation characteristic curve, the mixing ratio of cementitious materials is calculated by response surface optimization method to generate an activator ratio scheme;

[0117] Using gradation parameters as input variables, a multi-factor, multi-level test (exemplary: three-factor, three-level) is designed to establish a strength response equation and solve for the optimal mix ratio. For sandy soil strata, the proportion of alkali activator needs to be increased to enhance cementation; for clay soil strata, the water-solid ratio can be reduced to control shrinkage; for composite strata, a zonal mix ratio strategy is adopted, and different lithological areas are optimized independently. For 5m foundation pits, the number of test groups can be simplified; for 10m foundation pits, the frequency of strength verification needs to be increased; for 15m deep foundation pits, durability indicators (such as freeze-thaw cycles) are coupled to expand the objective function.

[0118] S303: Based on the activator ratio scheme, the improved soil is mixed using a mechanical forced mixing process, and a mixing uniformity test report is generated;

[0119] Feed materials according to the specified ratio and set the mixing parameters (exemplary speed and time). Detect the uniformity of component distribution (e.g., relative standard deviation of chloride ion content, RSD) through multi-point sampling. For sandy soil layers, the mixing time needs to be shortened to prevent segregation; for clay soil layers, the mixing intensity can be increased to break down the aggregate structure; for composite strata, a segmented feeding process is adopted, prioritizing the mixing of weak sublayers. For 5m foundation pits, the number of sampling points can be reduced; for 10m foundation pits, the uniformity threshold needs to be increased (exemplary RSD ≤ 5%, which can be strictly controlled to ≤ 3%); for 15m deep foundation pits, real-time spectral analysis technology is integrated for dynamic monitoring.

[0120] S304: Based on the mixing uniformity test report, the engineering performance of the soil is verified by the standard compaction test method to generate activated soil.

[0121] Based on uniformity data, multi-moisture-content compaction tests are conducted to determine the optimum moisture content and maximum dry density, and to verify unconfined strength. High moisture-content test points can be omitted for sandy soil strata; creep compression tests need to be added for clay strata; layered compaction is implemented for composite strata, and the compaction characteristics of each sub-layer are independently evaluated. Light compaction standards are used for 5m foundation pits; CBR tests are required for 10m foundation pits; and dynamic compaction simulation is introduced for 15m deep foundation pits to match the working conditions of heavy equipment.

[0122] S4 includes the following steps:

[0123] S401: Based on the compaction characteristics of activated soil, a long short-term memory neural network model is used to predict compaction parameters and generate a dynamic layer thickness control table.

[0124] Using soil parameters as input features, a neural network is used to predict the layered compaction thickness (exemplary output of clay / sand thickness). For sandy soil layers, permeability features are added as input; for clay soil layers, the plasticity index is introduced as a hidden layer node; for composite strata, a multi-model parallel architecture is used to process heterogeneous data. For 5m foundation pits, the number of network layers can be reduced; for 10m foundation pits, the training dataset needs to be expanded; and for 15m deep foundation pits, real-time feedback from ground-penetrating radar is coupled to optimize prediction accuracy.

[0125] S402: Based on the dynamic layer thickness control table, the compaction path planning is performed through augmented reality navigation equipment to generate mechanical compaction trajectory logs;

[0126] Based on layer thickness data, AR devices are used to project compaction paths, record trajectory deviations, and generate logs. Sandy soil layers require denser path guidance points to control loosening; clay soil layers can increase wheel track spacing to prevent wheel sticking; composite strata implement zoned path planning, setting compaction modes according to lithological differences; 5m foundation pits use single-device navigation; 10m foundation pits require multi-device collaborative positioning; and 15m deep foundation pits integrate BeiDou differential positioning technology to suppress cumulative errors.

[0127] S403: Based on the mechanical compaction trajectory log, the kernel density estimation algorithm is used to analyze the pressure monitoring data and generate a real-time pressure distribution map;

[0128] By fusing trajectory coordinates and pressure sensor data, the pressure density distribution is calculated using kernel functions. For sandy soil strata, the kernel bandwidth needs to be reduced to capture local variations; for clay strata, a time decay factor can be added to handle creep effects; for composite strata, an adaptive kernel function is used for partitioned fitting. For 5m foundation pits, the number of sensors can be reduced; for 10m foundation pits, the bandwidth parameters need to be optimized; and for 15m deep foundation pits, three-dimensional kernel density estimation is introduced to handle the layered pressure field.

[0129] S404: Based on the real-time pressure distribution map, the compaction parameters are dynamically adjusted by the programmable logic controller to generate a compaction degree distribution map.

[0130] By comparing the target pressure range, the number of compaction passes is dynamically adjusted through the PID control algorithm. For sandy soil layers, the proportional coefficient needs to be increased to accelerate the response; for clay soil layers, the integral time can be increased to suppress overshoot; for composite soil layers, a domain-independent control strategy is implemented. For 5m foundation pits, a single threshold control is used; for 10m foundation pits, multi-threshold graded adjustment is required; and for 15m deep foundation pits, the vibration frequency variable is coupled to expand the control dimension.

[0131] S5 includes the following steps:

[0132] S501: Based on the compaction distribution map, a distributed optical fiber temperature sensing network is deployed to generate a temperature monitoring network system.

[0133] Temperature measurement points are densely deployed according to the compaction distribution (0.3m spacing in high-density areas for example), and a fiber optic sensing network is constructed. For sandy soil layers, the vertical deployment ratio needs to be increased to monitor seepage; for clay soil layers, surface temperature measurement can be emphasized to prevent cracking; for composite soil layers, a heterogeneous network is used for layered monitoring, with a single layer deployment for 5m foundation pits; a three-dimensional grid deployment is required for 10m foundation pits; and fiber optic grating technology is introduced for 15m deep foundation pits to enhance anti-interference capabilities.

[0134] S502: Based on temperature monitoring network system data, a proportional-integral-derivative fuzzy adaptive algorithm is used to generate control commands and generate a dynamic temperature control command set.

[0135] The temperature difference data is analyzed by fuzzy PID algorithm, and the cooling parameter adjustment command is output. For sandy soil, the water flow increment needs to be reduced to prevent scouring; for clay soil, the integral weight can be increased to suppress temperature fluctuations; for composite soil, the membership function is dynamically reconstructed. The 5m foundation pit adopts single-input single-output control; the 10m foundation pit requires multi-variable collaborative regulation; and the 15m deep foundation pit is optimized by coupling the phase change material model to optimize the thermal balance equation.

[0136] S503: Based on the dynamic temperature control instruction set, it maintains the temperature field balance through the variable frequency hydraulic control system and generates a temperature field balance verification report.

[0137] Adjust the frequency converter according to the instructions (exemplary water pump frequency) to verify whether the temperature difference reaches the threshold. For sandy soil layers, the verification cycle needs to be shortened to cope with rapid heat dissipation; for clay soil layers, the temperature holding time can be extended; for composite soil layers, a zoned and timed verification strategy is adopted. For 5m foundation pits, simple harmonic frequency conversion is used; for 10m foundation pits, pulse frequency conversion is required to prevent resonance; and for 15m deep foundation pits, digital twin technology is integrated to preview the control effect.

[0138] S504: Based on the temperature field equilibrium verification report, a pouring speed optimization model is used to control the concrete pouring process and generate low-heat-damage concrete.

[0139] A pouring speed model (with stiffness parameters) is established based on temperature difference data to dynamically adjust the pouring rate. For sandy soil layers, the pouring speed can be increased to utilize heat dissipation; for clay soil layers, the speed needs to be reduced to prevent temperature accumulation; for composite soil layers, a gradient speed strategy is implemented. A linear speed model is used for 5m foundation pits; nonlinear segmented control is required for 10m foundation pits; and for 15m deep foundation pits, a coupled shrinkage stress model is used to suppress temperature cracks.

[0140] S6 includes the following steps:

[0141] S601: Based on template strain monitoring data, the principal stress trace analysis method is used to identify high stress areas and generate a stress concentration area distribution map.

[0142] Principal stresses are calculated using strain values, and high-stress zones are marked by comparison with threshold values. For sandy soil strata, the threshold needs to be lowered to reflect low constraint; for clay soil strata, the threshold can be increased to adapt to creep relaxation; for composite strata, anisotropic stress criteria are used, and the elastic modulus value is simplified for 5m foundation pits; for 10m foundation pits, elastoplastic correction needs to be considered; and for 15m deep foundation pits, a damage mechanics model is introduced to identify hidden damage.

[0143] S602: Based on the stress concentration zone distribution map, an anchor cable guiding device is installed using spatial positioning technology to generate an anchor cable sleeve positioning matrix;

[0144] The guide casing is positioned based on the coordinates of the high stress point, and the dip angle is adjusted according to the principal stress trajectory angle. For sandy soil strata, the casing diameter needs to be increased to prevent collapse holes; for clay soil strata, the dip angle can be reduced to compensate for creep; for composite strata, multi-directional casing is used to adapt to complex stress fields. For 5m foundation pits, manual positioning is used; for 10m foundation pits, a robotic arm is required; and for 15m deep foundation pits, an inertial navigation system is integrated to suppress angle drift.

[0145] S603: Based on the anchor sleeve positioning matrix, a graded tensioning process is used to establish a steel strand pre-tensioning system and generate a prestressed initial tensioning system.

[0146] The steel strands are loaded to the design tension in stages to verify the elongation deviation. In sandy soil strata, the holding time needs to be shortened to prevent relaxation; in clay soil strata, the number of loading stages can be increased; in composite strata, differential tension is used to match the stratum stiffness. A two-stage loading is used for a 5m foundation pit; a four-stage loading is required for a 10m foundation pit; and for a 15m deep foundation pit, acoustic emission technology is coupled to monitor micro-damage in real time.

[0147] S604: Based on the prestressed initial tensioning system, proportional prestress is applied through a hydraulic synchronous control algorithm to generate a tensioning matrix.

[0148] Tension force is distributed according to the stress distribution ratio of the template, and synchronization is achieved through hydraulic closed-loop control. The ratio coefficient is reduced in sandy soil to prevent over-tension; the coefficient can be increased in clay soil to compensate for creep loss; a dynamic weight distribution strategy is adopted for composite soil; open-loop control is used for 5m foundation pits; pressure-displacement dual feedback is required for 10m foundation pits; and digital hydraulic cylinders are introduced for 15m deep foundation pits to achieve nanometer-level precision.

[0149] S7 includes the following steps:

[0150] S701: Based on the compaction distribution map and tension matrix, the theoretical displacement is calculated using a soil-structure coupled numerical model to generate a theoretical displacement field cloud map.

[0151] Based on soil compaction parameters and anchor cable tension data, a soil-structure coupled finite element model is established. Through constitutive relation transformation (such as the ratio between elastic modulus and compaction value) and boundary load mapping, the displacement field is solved and a cloud map is generated. The Drucker-Prager criterion is used for sandy soil strata to reflect the dilatation effect; a creep constitutive model is introduced for clay strata to handle time-varying deformation; for composite strata, zonal constitutive assignment is implemented, and softening parameters are set independently for weak interlayers. The mesh size can be simplified for 5m foundation pits (0.2m is an example and can be increased); groundwater seepage-stress coupling needs to be considered for 10m foundation pits; and 15m deep foundation pits are extended to dynamic analysis models and coupled with seismic load conditions.

[0152] S702: Based on the theoretical displacement field cloud map, actual displacement data is collected through the total station monitoring system to generate a measured displacement dataset;

[0153] Based on the theoretical high-risk areas of displacement, monitoring points are set up, and spatial coordinate changes are collected using a total station. The displacement vector is calculated and a dataset is generated. For sandy soil strata, the density of horizontal displacement monitoring points needs to be increased to capture lateral displacement trends. For clay soil strata, the focus is on vertical displacement monitoring and the observation period is extended. For composite strata, a three-dimensional cross-point layout strategy is adopted, and monitoring is densified at the lithological boundary. For 5m foundation pits, single-station unidirectional observation is used. For 10m foundation pits, multi-station joint measurement is required to suppress errors. For 15m deep foundation pits, GNSS positioning technology is integrated to achieve millimeter-level precision control.

[0154] S703: Based on the measured displacement dataset, the least squares model verification method is used to analyze the displacement error and generate displacement error correction coefficients;

[0155] By comparing measured and theoretical displacement sequences, an error statistical model (such as a linear regression function) is constructed, and correction coefficients are solved to calibrate theoretical values. For sandy soil strata, an exponential correction function is used to adapt to nonlinear deformation; for clay strata, a time lag correction term needs to be introduced to handle creep delay; for composite strata, a zonal correction strategy is implemented, with coefficients independently fitted to different lithological regions. For 5m foundation pits, static correction coefficients are used; for 10m foundation pits, rolling time-domain correction (updated every 24 hours) is required; and for 15m deep foundation pits, a Kalman filter algorithm is coupled to achieve real-time dynamic correction.

[0156] S704: Based on the displacement error correction coefficient, a verification conclusion is generated through a threshold determination mechanism, and a back pressure performance evaluation report is generated.

[0157] The theoretical displacement values ​​are processed using correction coefficients, and the structural safety is determined by comparing them with preset displacement thresholds (including safety margin coefficients). A quantitative assessment report is generated. For sandy soil strata, the displacement threshold is lowered (e.g., 0.6 times the design value) to reflect deformation sensitivity; for clay soil strata, the threshold can be increased (e.g., 1.2 times) to adapt to long-term stability characteristics; for composite strata, a variable threshold strategy is adopted, and strict standards are set separately for high-risk substrata. A single fixed threshold is used for 5m foundation pits; a three-level warning threshold (warning / alert / danger) is required for 10m foundation pits; and for 15m deep foundation pits, reliability theory is introduced, and the failure probability is calculated based on Monte Carlo simulation.

[0158] S8 includes the following steps:

[0159] S801: Based on the temperature data of low-heat-hazard concrete, the support vector machine regression algorithm is used to predict the development law of hydration heat and generate a hydration heat peak prediction report.

[0160] Support vector machine regression models are trained using temperature time-series data, and kernel function parameters and penalty weights are optimized to predict peak temperature and timing. For sandy soil strata, environmental wind speed features need to be added as input to reflect heat dissipation differences. For clay soil strata, a humidity compensation factor is introduced to suppress the effect of drying shrinkage. For composite strata, an integrated learning framework is used to fuse multi-source data. For 5m foundation pits, the kernel function type can be simplified. For 10m foundation pits, feature selection is required to optimize the model input. For 15m deep foundation pits, a hybrid prediction architecture is constructed by coupling a finite element heat conduction model.

[0161] S802: Based on the peak hydration heat prediction report, a maintenance strategy is formulated through a fuzzy decision model to generate a dynamic maintenance control scheme;

[0162] Based on peak temperature grading and multi-index fuzzy inference (including temperature rise rate and ambient temperature), the system outputs instructions to adjust maintenance parameters such as spray frequency and cover thickness. For sandy soil layers, the focus is on spray frequency control to compensate for rapid evaporation; for clay soil layers, the cover thickness needs to be increased to prevent surface cracking; for composite soil layers, a differentiated maintenance strategy is implemented based on the region. A two-level control strategy is adopted for 5m foundation pits; a four-stage maintenance sequence is required for 10m foundation pits; and for 15m deep foundation pits, a reinforcement learning algorithm is introduced to optimize the instruction set in real time.

[0163] S803: Based on a dynamic maintenance control scheme, a wireless sensor network is used to monitor the surface humidity status and generate a humidity maintenance status record.

[0164] Wireless sensor network nodes are deployed to determine the surface humidity status based on benchmarked humidity data and deviation ranges. Sandy soil layers need to shorten the sampling cycle to cope with sudden drops in humidity; clay soil layers can relax the deviation threshold to adapt to slow changes; composite soil layers use cluster analysis to identify abnormal working conditions; 5m foundation pits use ZigBee short-range networking; 10m foundation pits require LoRa wide-area coverage; and 15m deep foundation pits deploy 5G edge computing nodes to achieve millisecond-level response.

[0165] S804: Based on humidity maintenance records, the intensity development law is calculated using a maturity theory model to generate an intensity growth curve.

[0166] Correction coefficients are set according to humidity conditions. The temperature-time series is integrated to generate maturity curves and divide the intensity development intervals. A linear maturity model is used to match the fast hardening characteristics of sandy soil strata. A logarithmic model is needed to fit the slow hardening process of clay strata. Multi-model weighted fusion is implemented for composite strata. The correction coefficient rules are simplified for 5m foundation pits. The cross-sectional size effect correction needs to be considered for 10m foundation pits. For 15m deep foundation pits, a microcrack evolution model is coupled to optimize the intensity prediction.

[0167] S9 includes the following steps:

[0168] S901: Based on the intensity growth curve, the piecewise function optimization method is used to determine the excavation strategy and generate a skip-cell excavation zoning plan.

[0169] Construction periods are divided according to the intensity growth rate, excavation priorities are matched, and the sequence of skip-section construction and zoning thresholds are planned. Sandy soil strata can be excavated earlier to take advantage of early strength characteristics; clay soil strata need to extend the curing period to wait for full hardening; composite strata adopt dynamic zoning with strength-permeability dual indicators, and 5m foundation pits adopt two-section skip construction; 10m foundation pits need four-section rotation to control exposure risk; 15m deep foundation pits are coupled with the support removal sequence to carry out four-dimensional progress planning.

[0170] S902: Based on the skip-excavation zoning plan, the overburden is removed through mechanized layered excavation process, and an earthwork excavation progress control table is generated.

[0171] Based on the soil density classification, the mechanical efficiency coefficient is adjusted, the operation time is calculated layer by layer and a progress plan is generated. For sandy soil layers, the excavation rate coefficient is increased to compensate for the loose characteristics; for clay soil layers, auxiliary soil loosening equipment is added to break the compaction; for composite soil layers, a multi-machine collaborative strategy is adopted to deal with the sudden change in lithology. For 5m foundation pits, a single-layer excavation is adopted to simplify the process; for 10m foundation pits, a three-layer stepped excavation is required; and for 15m deep foundation pits, BIM 4D simulation is integrated to achieve visual management of the progress.

[0172] S903: Based on the earthwork excavation progress control table, three-dimensional laser scanning technology is used to collect structural surface data and generate a structural surface point cloud model.

[0173] The scanning scheme is set according to the excavation progress. The surface zoning and continuity assessment are carried out based on the point cloud height difference. For sandy soil strata, the point cloud density needs to be reduced to suppress noise interference; for clay soil strata, multiple scans can be increased to improve the average accuracy; for composite strata, multi-view point cloud fusion is used to reconstruct complex structural surfaces. A handheld laser scanner is used for 5m foundation pits; a fixed full-station scanning system is required for 10m foundation pits; and for 15m deep foundation pits, UAV-borne lidar is deployed to achieve large-scale data acquisition.

[0174] S904: Based on the point cloud model of the structural surface, the flatness deviation is calculated by the minimum distance algorithm, and the support structure acceptance report is generated.

[0175] The minimum distance from the point cloud to the design surface is calculated, and the pass rate is statistically analyzed according to the multi-level threshold interval and a quantitative report is generated. The threshold for the over-limit area is relaxed for sandy soil strata to adapt to the easily disturbed characteristics; local curvature analysis is required to detect potential voids for clay soil strata; a regional weighted judgment strategy is adopted for composite strata; manual re-inspection is used for 5m foundation pits; repair plans are automatically generated and coordinates are output for 10m foundation pits; and risk classification is performed by coupling the structural safety margin model for 15m deep foundation pits.

[0176] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A construction method for single-sided formwork backfilling and counter-pressure of external cladding panels, characterized in that: Includes the following steps: S1: Construct a three-dimensional geological model based on geotechnical investigation data, determine critical excavation parameters through numerical analysis methods, and generate an excavation safety threshold report; S2: Based on the excavation safety threshold report, a lightweight template system is designed using a topology optimization algorithm. The template is installed using a laser positioning system, and an reinforcement layer is configured to form a high-precision template system that meets the verticality and stiffness control standards. S3: Based on the characteristics of the reserved soil, a cementitious improvement material is prepared and uniformly mixed to generate activated soil with a predetermined strength; S4: Based on the high-precision template system and activated soil, the layered backfill thickness is dynamically set through the prediction model, and the backfill is compacted to the target compaction degree by the navigation compaction equipment, generating a compaction degree distribution map that reflects the pressure balance state; S5: Based on the pre-embedded temperature monitoring network in the compaction distribution map, an adaptive control algorithm is used to regulate the cooling system to generate low-heat-damage concrete that meets the crack control requirements; S6: Based on the stress distribution of the template, locate key areas, apply prestress calculated according to the stress ratio, and generate a tension matrix that can offset part of the concrete lateral pressure. S7: Based on the compaction distribution map and tension matrix, the displacement is verified through a coupled analysis model, and a counter-pressure performance report that meets the deformation control requirements is generated in real time. S8: Based on the temperature change law of the low heat hazard concrete, a prediction algorithm is used to determine the curing parameters and generate a strength growth curve that reflects the strength development law; S9: Based on the strength growth curve, remove the overburden according to the segmented excavation strategy, and generate an acceptance report for the support structure that meets the flatness standard through three-dimensional scanning.

2. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S1 includes the following steps: S101: Based on borehole data from geotechnical exploration, a stratigraphic interface distribution model is generated using the Kriging spatial interpolation algorithm, and a geological spatial surface model is generated. S102: Based on the geological space surface model, the soil shear strength parameters are calculated using the finite element strength reduction method to generate a set of soil strength parameters; S103: Based on the soil strength parameter set, the critical excavation depth is solved using the slope stability numerical simulation method, and an excavation stability assessment report is generated. S104: Based on the excavation stability assessment report, the deformation control threshold is determined by the Monte Carlo risk analysis method, and an excavation safety threshold report is generated.

3. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S2 includes the following steps: S201: Based on the excavation safety threshold report, a topology optimization algorithm is used to design the spatial configuration of the template ribs and generate a rib topology configuration diagram; S202: Based on the topological configuration diagram of the rib plate, a positioning and calibration template system is generated by installing template units pre-embedded with geosynthetic materials through a laser positioning system. S203: Based on the aforementioned positioning and calibration template system, the template support spacing is dynamically adjusted using strain energy density analysis to achieve stiffness enhancement and generate a stiffness-enhanced support system. S204: Based on the aforementioned stiffness-enhanced support system, a high-precision template system is generated by verifying the template verticality error according to the standard of ≤2‰ using an inclination sensing device.

4. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S3 includes the following steps: S301: Based on the physical properties of the reserved soil, the particle size distribution analysis method is used to determine the soil composition characteristics and generate the soil distribution characteristic curve. S302: Based on the soil gradation characteristic curve, the cementitious material mixing ratio is calculated by response surface optimization method to generate an activator mixing scheme; S303: Based on the activator formulation scheme, the improved soil is mixed using a mechanical forced mixing process, and a mixing uniformity test report is generated; S304: Based on the aforementioned mixing uniformity test report, the engineering performance of the soil is verified by the standard compaction test method to generate activated soil.

5. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S4 includes the following steps: S401: Based on the compaction characteristics of the activated soil, a long short-term memory neural network model is used to predict compaction parameters and generate a dynamic layer thickness control table. S402: Based on the dynamic layer thickness control table, the compaction path planning is performed by the augmented reality navigation device to generate a mechanical compaction trajectory log; S403: Based on the mechanical compaction trajectory log, the pressure monitoring data is analyzed using a kernel density estimation algorithm to generate a real-time pressure distribution map; S404: Based on the real-time pressure distribution map, the compaction parameters are dynamically adjusted by the programmable logic controller to generate a compaction degree distribution map.

6. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S5 includes the following steps: S501: Based on the compaction distribution map, deploy a distributed optical fiber temperature sensing network to generate a temperature monitoring network system. S502: Based on the data from the temperature monitoring network system, a proportional-integral-derivative fuzzy adaptive algorithm is used to generate control commands and a dynamic temperature control command set is generated. S503: Based on the dynamic temperature control instruction set, maintain the temperature field balance through the variable frequency hydraulic control system and generate a temperature field balance verification report. S504: Based on the temperature field balance verification report, a pouring speed optimization model is used to control the concrete pouring process to generate low-heat-damage concrete.

7. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S6 includes the following steps: S601: Based on template strain monitoring data, the principal stress trace analysis method is used to identify high stress areas and generate a stress concentration area distribution map. S602: Based on the stress concentration zone distribution map, install the anchor cable guide device using spatial positioning technology to generate the anchor cable sleeve positioning matrix; S603: Based on the anchor sleeve positioning matrix, a steel strand pre-tensioning system is established using a graded tensioning process to generate a prestressed initial tensioning system; S604: Based on the prestressed initial tensioning system, proportional prestress is applied through a hydraulic synchronous control algorithm to generate a tensioning matrix.

8. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S7 includes the following steps: S701: Based on the compaction distribution map and tension matrix, the theoretical displacement is calculated using a soil-structure coupled numerical model to generate a theoretical displacement field cloud map; S702: Based on the theoretical displacement field cloud map, actual displacement data is collected through the total station monitoring system to generate a measured displacement dataset; S703: Based on the measured displacement dataset, the least squares model verification method is used to analyze the displacement error and generate displacement error correction coefficients; S704: Based on the displacement error correction coefficient, a verification conclusion is generated through a threshold determination mechanism, and a counter-pressure performance evaluation report is generated.

9. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S8 includes the following steps: S801: Based on the temperature data of the low-heat-hazard concrete, the support vector machine regression algorithm is used to predict the development law of hydration heat and generate a hydration heat peak prediction report. S802: Based on the hydration heat peak prediction report, a maintenance strategy is formulated through a fuzzy decision model to generate a dynamic maintenance control scheme; S803: Based on the dynamic maintenance control scheme, a wireless sensor network is used to monitor the surface humidity status and generate a humidity maintenance status record. S804: Based on the humidity maintenance status record, the intensity development law is calculated using the maturity theory model, and an intensity growth curve is generated.

10. The construction method for single-sided formwork backfilling and counter-pressure construction of external cladding panels according to claim 1, characterized in that: S9 includes the following steps: S901: Based on the intensity growth curve, the piecewise function optimization method is used to determine the excavation strategy and generate a skip-cell excavation zoning plan. S902: Based on the skip-cell excavation zoning plan, the overburden is removed by mechanized layered excavation process to generate an earthwork excavation progress control table. S903: Based on the earthwork excavation progress control table, use three-dimensional laser scanning technology to collect structural surface data and generate a structural surface point cloud model. S904: Based on the point cloud model of the structure surface, the flatness deviation is calculated using the minimum distance algorithm, and an acceptance report for the support structure is generated.

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