A mass concrete pouring damage cracking prediction and grading evaluation method considering shrinkage effect

Abstract

The present application relates to the technical field of concrete structure engineering, and provides a mass concrete pouring damage cracking prediction and grading evaluation method considering shrinkage effect, comprising: layering modeling according to pouring scheme and simulating construction by using life and death unit in ABAQUS; calculating temperature field based on composite exponential hydration heat release of HETVAL subprogram and time-varying heat transfer boundary of FILM subprogram; introducing Arrhenius equivalent age coupling ACI 209R-92 shrinkage through USDFLD and UEXPAN subprograms, realizing age evolution of elastic modulus and thermal expansion coefficient in combination with UFIELD subprogram, and obtaining temperature-shrinkage stress field; calculating tensile / compressive damage by using CDP model and outputting damage cloud picture, giving three-level maintenance crack control measures according to damage factor partition, and checking parameters in combination with on-site temperature / strain monitoring. The present scheme realizes the transition from point judgment to global recognition and grading control, takes into account the time-varying characteristics of temperature field, shrinkage effect and material, improves the prediction accuracy and operability, reduces the risk of cracks and leakage, improves durability and reduces rework cost.

Description

Technical Field

[0001] This invention relates to the field of concrete structure engineering technology, specifically to a method for predicting and classifying the damage and cracking of large-volume concrete pouring considering shrinkage effects. Background Technology

[0002] Mass concrete is widely used in subway stations, underground structural slabs and abutments, bridge foundations, and hydraulic structures. Due to its large cross-sectional dimensions and difficulty in heat dissipation, the heat released during cement hydration after pouring causes a rapid rise in internal temperature. The outer surface is affected by heat exchange conditions from the formwork, air, and surrounding rock, creating a significant temperature gradient. The subsequent cooling process, combined with volumetric deformations such as autogenous shrinkage and drying shrinkage, transforms into tensile stress under the constraints of the foundation, surrounding rock, reinforcing steel, and the already poured structure. This stress easily induces cracks in the early stages before the concrete's strength and stiffness are fully developed, thus affecting its impermeability and durability.

[0003] Currently, crack analysis often employs a "temperature field-temperature stress" approach: first, the temperature stress at a certain point in the concrete is calculated, and then compared with the allowable tensile stress to determine whether that point has cracked. This method is essentially a point-based assessment, making it difficult to provide an intuitive and comprehensive evaluation of the overall crack range, spatial distribution, and risk zoning of the main structure. Furthermore, traditional methods in engineering applications commonly suffer from problems such as insufficient calibration of hydration heat release parameters, inadequate consideration of the time-varying nature of boundary heat transfer, simplified handling of shrinkage effects and their coupling with temperature history, insufficient representation of the time-varying nature of early-age material parameters, and a lack of closed-loop verification between monitoring data and model results. These issues limit the accuracy of crack prediction and the specificity of corrective measures.

[0004] Therefore, there is an urgent need to propose a crack prediction and classification evaluation method for the entire process of large-volume concrete pouring, which can comprehensively consider hydration heat release, boundary heat transfer, shrinkage effect and material time-varying characteristics, so as to realize the spatial identification and risk zoning of damage / cracking at the structural scale, and provide a basis for the formulation of temperature control and curing crack control measures. Summary of the Invention

[0005] To address the problems existing in the background technology, this invention proposes a method for predicting and classifying the damage and cracking of large-volume concrete pouring that considers the shrinkage effect. This method realizes the transformation of cracking analysis from point discrimination to global identification and graded control, while taking into account the temperature field, shrinkage effect and time-varying characteristics of materials. This improves the prediction accuracy and operability, reduces the risk of cracks and leakage, enhances durability and reduces rework costs.

[0006] To achieve the above objectives, the present invention adopts the following solution:

[0007] A method for predicting and classifying damage and cracking in large-volume concrete pouring considering shrinkage effects includes the following steps: Step 1: Establish a geometric model of a large-volume concrete structure. According to the preset construction and pouring plan, the geometric model is divided into layers and meshed. The construction process is simulated by the birth and death element method to construct a numerical model. Step 2: Perform thermal analysis on the numerical model, taking into account the heat release from concrete hydration and dynamic thermal boundary conditions, and calculate the temperature field during construction and curing. Step 3: Perform stress analysis on the numerical model, import the temperature field as a thermal load, and calculate the stress field by considering the time-varying characteristics of concrete mechanical properties and shrinkage deformation. Step 4: Perform damage analysis on the numerical model, import the stress field, and use the concrete plastic damage model (CDP model) to calculate the damage and cracking results. Step 5: Deploy sensors at the construction site to monitor the temperature and strain changes of the concrete in real time, and feed the monitoring data back to the numerical model for verification and correction to predict the location of cracks. Step 6: Based on the numerical model verified and corrected in Step 5, output the damage cloud map, identify potential damaged units and divide the crack risk area, conduct graded evaluation according to the damage factor, and take corresponding control measures.

[0008] Optionally, the thermal analysis in step 2 includes: specifying the divided mesh cells as DC3D8 type, assigning thermophysical properties to the concrete material, defining thermodynamic boundary conditions that include at least the heat exchange between the concrete and air, formwork, and rock strata, and adjusting the convective heat dissipation coefficient and ambient temperature over time by calling the FILM subroutine, while also considering the heat conduction inside the concrete during the pouring process; setting the analysis step and incremental step, and calling the HETVAL subroutine to simulate the hydration heat release process of the concrete based on the composite exponential model.

[0009] Optionally, adjusting the convective heat dissipation coefficient and ambient temperature over time includes: the thermodynamic boundary conditions for heat exchange include: calculating heat loss caused by heat convection and thermal radiation using Newton's law of cooling and Stefan-Boltzman's law, and simultaneously using the FILM subroutine to simulate the changes in the convective heat dissipation coefficient and ambient temperature over time; wherein the formulas for heat convection and thermal radiation are as follows: , , In the formula, and These are losses due to heat convection and heat radiation. The convective heat dissipation coefficient; and For concrete temperature and ambient temperature; Thermal emissivity; Let be the Stefan-Boltzman constant, taken as 5.67 × 10⁻⁶. -8 W / (m 2 ·K 4 ); The equation governing heat conduction within the concrete during the pouring process is as follows: , In the formula, For concrete pouring time; The thermal diffusivity of concrete; For the temperature rise of concrete insulation; , , These are the three directions from which heat originates.

[0010] Optionally, the expression for the heat release model of concrete hydration is: , In the formula, The heat release rate of the heat source; This represents the maximum heat release during concrete hydration. , The influence coefficient of the model; Among them, the , The results were obtained from a semi-adiabatic temperature rise test, specifically including the following: Step 2.1: Establish a finite element model of the semi-adiabatic temperature rise test device in ABAQUS. Set the concrete specimen as a cube with a side length of 20 cm. The specimen is completely wrapped in an insulation box composed of insulation layer. Call the HETVA subroutine to simulate the heat release of concrete hydration based on the composite index model. Step 2.2 involves conducting parameter analysis on the insulation layer thickness, thermodynamic parameters of the insulation material, and external environment, and selecting appropriate test conditions. Step 2.3: Based on the analysis results of Step 2.2, construct the experimental device and embed temperature sensors in the concrete to monitor temperature changes in real time; Step 2.4: Based on the temperature-age test data obtained in Step 2.3, the finite element model from Step 2.1 is called to perform calculations. , Sensitivity analysis was performed, experimental curves were fitted, and finally, applicable parameters were obtained. , .

[0011] Optionally, in step 3, the stress analysis includes: designating the divided mesh elements as type C3D8R, assigning mechanical properties to concrete and reinforcing steel; simulating the changes in the elastic modulus and thermal expansion coefficient of concrete with age by calling the UFIELD and UEXPAN subroutines respectively; defining mechanical boundary conditions including at least the formwork fixed end constraint, the already cast component constraint, and the surrounding rock layer constraint; setting the analysis step and incremental step synchronized with step 2, and importing the temperature field obtained in step 2 into the predefined field; calling the USDFLD and UEXPAN subroutines, based on the ACI 209R-92 shrinkage prediction model and using the Arrhenius equivalent age to replace the actual time, to simulate the shrinkage process of concrete.

[0012] Optionally, the expression for the model of how the elastic modulus of concrete changes with age is as follows: , In the formula, For concrete at the age of The elastic modulus at that time; This refers to the elastic modulus of concrete at 28 days of age under standard curing conditions. For calculation parameters; This is the correction factor for mineral admixtures; The model expression for the change of the coefficient of thermal expansion with age is as follows: , In the formula, Age The coefficient of thermal expansion at that time; The coefficient of thermal expansion at 28 days of age; Hydration time parameters related to admixtures; The formula for calculating temperature strain is as follows: , In the formula, For temperature strain; T This represents the change in concrete temperature. The formula for calculating the Arrhenius equivalent age is as follows: , , In the formula, The running time variable is used during the integration process; and These are the reference temperature and the temperature history, respectively. , and These are the equivalent age, the drying start time, and the actual equivalent conversion age, respectively. It is the apparent activation energy; The ideal gas constant is taken as 8.314 J / (mol·K); The calculation formula for the ACI 209R-92 contraction prediction model is as follows: , In the formula, for The equivalent age at any given moment; for Contraction strain at any moment; This is the final contraction strain.

[0013] Optionally, the steps of calling the USDFLD and UEXPAN subroutines to simulate the shrinkage process of concrete based on the shrinkage prediction model and using the Arrhenius equivalent age to replace the actual time include: Step 3.1: Call the USDFLD subroutine to calculate and output the equivalent age, that is, update the equivalent age with the Arrhenius acceleration factor integral in each incremental step and pass it to the UEXPAN subroutine. Step 3.2: Call the USDFLD subroutine to record the equivalent age for drying start. If the pouring zones or layers are different, the drying start time for each point can be determined by field variables or zone logic. Step 3.3: Call the UEXPAN subroutine to calculate the shrinkage strain based on the equivalent age in Step 3.1 and the equivalent age calculated from the start of drying in Step 3.2, output the strain increment of the current increment step, save the strain value of the previous increment step, and then perform the calculation for the next increment step.

[0014] Optionally, in step 4, the damage analysis includes: assigning CDP model parameters based on the stress analysis model in step 3; realizing the time-varying nature of CDP model parameters as the early mechanical behavior of concrete changes by introducing field variables or calling the UFIELD subroutine; importing the stress field obtained in step 3 into a predefined field, and calculating and outputting the damage cracking results. The damage factors in the CDP model are calculated based on the uniaxial stress state of concrete. These damage factors include tensile cracking damage factors and crushing damage factors. The calculation formula for the tensile cracking damage factor is as follows: , In the formula, It is a tensile damage factor; The coefficient is dimensionless. Normalized strain ratio; For the parameters of the tension-induced descent segment; The formula for calculating the crushing damage factor is as follows: , In the formula, It is a crushing damage factor; The coefficient is dimensionless. Normalized strain ratio; It is a uniaxial compressive strain; These are the parameters for the pressure-induced descent phase; These are the shape parameters of the compressed rising section.

[0015] Optionally, step 5 specifically includes: Step 5.1: Before the on-site concrete structure is poured, vibrating wire concrete embedded strain gauges are embedded in layers and sections to obtain real-time temperature and strain field time history data around the embedding points. Step 5.2: Run the numerical model as described in Step 2, calculate the output temperature field results, and verify and adjust the parameters with the field temperature monitoring data fed back by the strain gauge to ensure that the relative error is controlled within 5%. Step 5.3: Based on the model calibration in Step 5.2, calculate the output temperature strain and the strain caused by the structure's self-weight according to Step 3. Calculate the shrinkage strain based on the on-site measured strain. The calculation formula is as follows: , In the formula, These are the measured values ​​from the strain gauge. This represents the strain value caused by the self-weight of the concrete structure. Step 5.4: Based on the calculation results of Step 5.3, recalculate the output shrinkage strain according to Step 3, and verify and adjust the parameters with the shrinkage strain obtained in Step 5.3 to ensure that the relative error is controlled within 20%.

[0016] Optionally, the graded evaluation and corresponding control measures mentioned in step 6 include: When the damage factor is ≥0 and <0.6, it is a level 1 risk area, and routine maintenance measures are adopted, including covering and insulation, moisture retention maintenance, demolding according to plan and routine monitoring. When the damage factor is ≥0.6 and <0.9, it is a level 2 risk area. Enhanced maintenance measures are adopted, including thickening the insulation layer, extending the insulation and moisture retention time, delaying demolding, wind and sun protection, and increasing the monitoring and early warning of key parts. When the damage factor is ≥0.9, it is a level 3 risk zone. Forced maintenance and emergency treatment measures are adopted, including multi-layer heat preservation and moisture retention, significantly delaying demolding and controlling the temperature drop after demolding, sealing and moisturizing in time when cracks appear, and sealing or grouting repair when necessary.

[0017] The beneficial effects of this invention are as follows: This solution realizes the transformation from point discrimination to global identification and hierarchical control, taking into account temperature field, shrinkage effect and time-varying characteristics of materials, improving prediction accuracy and operability, and reducing the risk of cracks and leakage. Specifically: (1) Boundary heat transfer is more in line with engineering practice: heat convection and heat radiation heat loss are uniformly incorporated into the temperature field calculation, and the convection coefficient and ambient temperature change with time are realized through the FILM subroutine, which improves the authenticity and stability of temperature field prediction.

[0018] (2) The heat source parameters have calibrable and verifiable characteristics: The composite exothermic hydration model is adopted and the model coefficients are obtained by combining the semi-adiabatic temperature rise test and finite element inversion. This realizes the transformation of the hydration heat input from empirical given to experimental calibration, which significantly reduces the uncertainty of the heat source parameters.

[0019] (3) The time-varying characteristics of early-age mechanical parameters are realized: the elastic modulus and thermal expansion coefficient of concrete are realized with age through UFIELD and UEXPAN, so as to calculate the early-age temperature strain and temperature stress more accurately, significantly reduce the calculation error caused by the use of constant parameters, and improve the analysis accuracy.

[0020] (4) Couple the shrinkage effect with the temperature history: Introduce the Arrhenius equivalent age and couple it with the ACI 209R-92 shrinkage model. Combine USDFLD+UEXPAN to realize the shrinkage calculation of different drying start times in different zones / layers, so that the shrinkage prediction can reflect the influence of the temperature history.

[0021] (5) Upgrade the cracking risk from point identification to global quantification: Based on the CDP model and the tensile cracking damage factor and crushing damage factor calculated according to the uniaxial state, a continuous damage field is obtained in the structure, which can intuitively identify the cracking concentration area and spatial distribution, overcoming the shortcomings of the traditional single-point temperature stress and allowable tensile stress comparison which can only determine single-point cracking.

[0022] (6) Closed-loop verification of monitoring and calculation: Real-time temperature monitoring is carried out using strain gauges buried on site. Based on the monitoring data, the temperature field distribution and shrinkage strain evolution are checked and adjusted in stages (temperature error control, shrinkage error control), which significantly improves the accuracy of model prediction and consistency with the field.

[0023] (7) An executable hierarchical control output has been formed: multi-level risk zone division is realized by using damage factors as indicators, providing a clear basis for the zoned implementation of temperature control and maintenance measures, effectively enhancing the pertinence and operability of on-site decision-making and ensuring structural safety. Attached Figure Description

[0024] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram of the ABAQUS numerical simulation calculation process in an embodiment of the present invention; Figure 3This is a schematic diagram of the finite element model and mesh generation of a large-volume concrete subway station in an embodiment of the present invention; Figure 4 This is a schematic diagram showing the strain gauge placement and on-site installation in an embodiment of the present invention; Figure 5 Fitting of semi-adiabatic temperature rise test in embodiments of the present invention , A flowchart; Figure 6 This is a schematic diagram of the concrete strain-stress-damage factor curve according to an embodiment of the present invention. Figure 6 Figure (a) shows a schematic diagram of the behavior under pressure. Figure 6 (b) is a schematic diagram of the tensile behavior curve; Figure 7 This is a schematic diagram of the test-simulated temperature change curve at measuring point 9 on the station floor according to an embodiment of the present invention; Figure 8 These are schematic diagrams of the strain-age variation curves at measuring point 9 of the station floor slab and the experimental-simulation calculation shrinkage strain variation curves, respectively, according to an embodiment of the present invention. Figure 8 (a) is a schematic diagram of the strain-age variation curve. Figure 8 (b) is a schematic diagram of the experimental-simulation calculation curve of shrinkage strain. Figure 9 This is a comparison diagram of the simulated damage and cracking results of the station floor slab in this embodiment of the invention and the actual cracking. Figure 10 This is a comparison diagram of the simulated damage and cracking results of the station sidewall in this embodiment of the invention and the actual cracking. Figure 11 This is a comparison diagram of the simulated damage and cracking results of the station roof wall according to an embodiment of the present invention and the actual cracking. Figure 12 This is a schematic diagram illustrating the division of the three-level cracking risk zone of the station side wall according to an embodiment of the present invention. Detailed Implementation

[0025] To make the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the given embodiments are merely one implementation method and do not represent all embodiments.

[0026] Combination Figure 1 This invention provides a method for predicting and classifying cracking damage in large-volume concrete pouring that takes into account shrinkage effects. This method aims to transform cracking analysis from point discrimination to global identification and graded control, while taking into account temperature field, shrinkage effect and time-varying characteristics of materials, so as to improve prediction accuracy and operability, and reduce the risk of cracks and leakage.

[0027] Specifically, taking a subway station project as a specific example, the crack prediction and grading evaluation method provided by this invention is described in detail and its effectiveness is verified. It includes the following steps: Step 1: Establish a geometric model of the large-volume concrete structure in ABAQUS. Based on the actual construction pouring plan, the geometric model of the concrete structure is layered and sectioned. Hexahedral elements are used to divide the mesh, and the construction process is simulated using birth and death elements to construct a numerical model. In this embodiment, the station structure's components that conform to the large-volume concrete structure are the station floor slab, the station's ground floor side walls, and the station roof slab. Although the average thickness of the station roof slab is less than 1m, the thickness of its upward-turning beam is greater than 1m. Figure 3 As shown. In this embodiment, to simplify the calculation, only these three components are simulated. The base plate is divided into a total of 30,600 units, the bottom side wall is divided into a total of 5,980 units, and the top plate is divided into a total of 40,334 units.

[0028] Step 2: Perform thermal analysis on the numerical model, considering the heat release from concrete hydration and dynamic thermal boundary conditions, to calculate the temperature field during construction and curing. Further, this includes: Step 2.1: Specify the generated concrete mesh element as DC3D8, and assign thermophysical properties to the concrete material, with the density set to 2400 kg / m³. 2 The thermal conductivity was set to 1.78 W / (m·K), and the specific heat capacity was set to 960 J / (kg·℃). Step 2.2 defines thermodynamic boundary conditions that include at least the heat exchange between concrete and air, formwork, and rock strata, where the pouring temperature is set to 20℃ and the heat release coefficient between concrete and formwork is set to 7.60×10⁻⁶. 4 J / (h·m 2 (℃), the heat transfer coefficient between concrete and rock strata is set at 1.05×10. 4 J / (h·m 2 ·℃).

[0029] Step 2.3 involves adjusting the convective heat dissipation coefficient and ambient temperature over time by calling the FILM subroutine, while also considering internal heat conduction within the concrete. Heat losses due to convection and radiation are calculated using Newton's law of cooling and the Stefan-Boltzman law, as shown in the following formulas: , , In the formula, and These are losses due to heat convection and heat radiation. The convective heat dissipation coefficient is W / (m²). 2 ·℃); and The concrete temperature and ambient temperature are in °C. The thermal emissivity is taken as 0.77; Let be the Stefan-Boltzman constant, taken as 5.67 × 10⁻⁶. -8 W / (m 2 ·K 4 The FILM subroutine is used to implement this. and Adjustments will be made over time to accommodate changes in the climate at the construction site.

[0030] The heat conduction within the concrete is controlled by the heat conduction equation: , In the formula, The concrete pouring time is d; Let m be the thermal diffusivity of concrete. 2 / s; The temperature rise of the concrete during insulation is ℃.

[0031] Step 2.4: Set the analysis step and incremental step, using a heat transfer (transient) analysis step with a time length of 40 days. Call the HETVAL subroutine to simulate the heat release from concrete hydration based on the composite exponential model. The model expression is as follows: , In the formula, The heat release rate of the heat source is expressed in W. The maximum value of heat release from concrete hydration is taken as 320 kJ / kg; , The model influence coefficients are set to 0.69 and 0.56, respectively. Wherein, the... , The results were obtained by fitting the semi-adiabatic temperature rise test, such as Figure 5 As shown, it specifically includes the following: Step 2.4.1: Establish a finite element model of the semi-adiabatic temperature rise test device in ABAQUS. Set the concrete specimen to a cube with a side length of 20 cm. The specimen is completely wrapped in an insulation box composed of insulation layer. Call the HETVA subroutine to simulate the heat release of concrete hydration based on the composite index model.

[0032] Step 2.4.2: Parameter analysis was performed on the insulation layer thickness, thermodynamic parameters of the insulation material, and external environment. Reasonable test conditions were selected, and the final test object was a concrete cube specimen with a side length of 20 cm. The concrete specimen was completely wrapped inside a cubic insulation box. The insulation material was selected as a 10 cm thick polyurethane insulation board. The surface of the insulation box was not treated. The test was carried out on a conventional concrete test site.

[0033] Step 2.4.3: Based on the analysis results of Step 2.4.2, construct the test device and embed a temperature sensor in the concrete to monitor temperature changes in real time.

[0034] Step 2.4.4: Based on the temperature-age test data obtained in Step 2.4.3, the finite element model from Step 2.4.1 is called to perform calculations. , Sensitivity analysis was performed, experimental curves were fitted, and finally, applicable parameters were obtained. , .

[0035] Therefore, the temperature field results during the concrete pouring and curing process are calculated and output.

[0036] Step 3: Perform stress analysis on the numerical model, import the temperature field as a thermal load, and consider the time-varying characteristics of concrete mechanical properties and shrinkage deformation to calculate the stress field. Further, this includes: Step 3.1: Specify the mesh element as C3D8R, and assign mechanical properties to the concrete and steel reinforcement materials. In this embodiment, the concrete material type is C40; the steel reinforcement type is HRB400. An ideal elastic-plastic model is adopted, and it is set as a truss element. Its material parameters are shown in Table 1.

[0037] Table 1 Mechanical Properties of Reinforcing Steel

[0038] Step 3.2: Call the UFIELD and UEXPAN subroutines respectively to simulate the change of the elastic modulus and thermal expansion coefficient of concrete with age.

[0039] The model expression for simulating the change of the elastic modulus of concrete with age using the UFIELD subroutine is as follows: , In the formula, For concrete at the age of The elastic modulus at that time, in MPa; The elastic modulus of concrete under standard curing conditions at an age of 28 days is taken as 32500 MPa; The parameter is set to 0.09 for calculation purposes. This is the correction factor for mineral admixtures, taken as 1.

[0040] The model for simulating the change of thermal expansion coefficient with age using the UEXPAN subroutine is as follows: , In the formula, Age The coefficient of thermal expansion at that time; The coefficient of thermal expansion at 28 days of age is taken as 1.0 × 10⁻⁶. -5 ; The hydration time parameter related to the admixture is set to 2.0.

[0041] The formula for calculating temperature strain is as follows: , In the formula, For temperature strain; T This represents the change in concrete temperature.

[0042] Step 3.3 defines mechanical boundary conditions including at least the formwork fixed-end constraint, the already cast component constraint, and the surrounding rock layer constraint. In this embodiment, the formwork fixed-end constraint limits the normal deformation of the concrete contact surface with the formwork to 0; the already cast component constraint is a full constraint; and the surrounding rock layer constraint uses springs to simulate the constraint effect of the rock layer on the concrete, with a spring stiffness of 1.45 × 10⁻⁶. 7 N / m.

[0043] Step 3.4: Set up the analysis step and incremental step synchronized with Step 2, and import the temperature field results from Step 2 into the predefined field.

[0044] Step 3.5: The USDFLD and UEXPAN subroutines are invoked to simulate the concrete shrinkage process based on the ACI 209R-92 shrinkage prediction model, and the Arrhenius equivalent age is used to replace the actual time. The formula for calculating the Arrhenius equivalent age is as follows: , , In the formula, The running time variable is used during the integration process; and These are the reference temperature and the temperature history, respectively, in K. The reference temperature is selected as 293.15 K. , and These are the equivalent age, drying start time, and actual equivalent conversion age, respectively, in days (d). The apparent activation energy is taken as 40000 J / mol; The ideal gas constant is taken as 8.314 J / (mol·K).

[0045] The calculation formula for the ACI 209R-92 contraction prediction model is as follows: , In the formula, for The equivalent age at any given moment; for Contraction strain at any moment; For the final contraction strain, 780×10 -6 This refers to the free shrinkage strain of concrete under standard conditions. This is the correction factor for initial maintenance conditions when they deviate from standard conditions; This is the correction factor for relative humidity when deviating from standard conditions; This is the correction factor for the component volume-to-surface area ratio when deviating from standard conditions; This is the correction factor for concrete slump when deviating from standard conditions; This is the correction factor for the fine aggregate content when deviating from standard conditions; This is the correction factor for cement content when deviating from standard conditions; The value of the air content correction factor for concrete when deviating from standard conditions is shown in Table 2.

[0046] Table 2. Formulas for calculating correction factors in the ACI 209R-92 model.

[0047] Furthermore, this step of simulating the concrete shrinkage process specifically includes: Step 3.5.1: Call the USDFLD subroutine to calculate and output the equivalent age, that is, update the equivalent age using the Arrhenius acceleration factor integral within each increment and pass it to the UEXPAN subroutine. The expression for updating the equivalent age is: , In the formula, The time for the (n+1)th increment step; The time for the nth increment step; t This is the time difference between the (n+1)th increment step and the nth increment step.

[0048] Step 3.5.2: Call the USDFLD subroutine to record the equivalent age for drying start. If the pouring zones or layers are different, the drying start time for each point can be determined by field variables or zone logic.

[0049] Step 3.5.3 calls the UEXPAN subroutine to calculate the shrinkage strain based on the equivalent age in Step 3.5.1 and the equivalent age calculated from the drying start date in Step 3.5.2, outputs the strain increment of the current increment step, saves the strain value of the previous increment step, and then performs the calculation for the next increment step. The formula for calculating the actual equivalent conversion age is as follows: , The formula for calculating the total contraction strain in the current incremental step is: , The formula for calculating the current incremental step contraction strain increment is: , In the formula, This represents the total contraction strain at the current increment step. This represents the total contraction strain of the previous incremental step; This represents the current incremental step of contraction strain increment.

[0050] Therefore, the stress field results during concrete construction and curing are calculated and output.

[0051] Step 4: Perform damage analysis on the numerical model, import the stress field, and use the concrete plastic damage model (CDP model) to calculate the damage and cracking results. Further, this includes: Based on the numerical model in step 3, parameters are assigned to the CDP model of concrete material. The damage factor in the CDP model is calculated according to the uniaxial stress state of concrete. The damage factor includes tensile cracking damage factor and crushing damage factor. The calculation formula for the tensile cracking damage factor is as follows: , In the formula, It is a tensile damage factor; These are dimensionless coefficients used to ensure that the curve matches the elastic modulus and peak stress / strain near the peak value. ; The elastic modulus of concrete, in N / mm². 2 ; The standard value of uniaxial tensile strength of concrete, in MPa; To and The corresponding peak tensile strain; To normalize the strain ratio, ; It is a uniaxial tensile strain; The parameters for the tensile descent segment (controlling the steepness of the tensile softening segment).

[0052] The formula for calculating the crushing damage factor is as follows: , In the formula, It is a crushing damage factor; These are dimensionless coefficients used to ensure that the curve matches the elastic modulus and peak stress / strain near the peak value. ; The standard value of uniaxial compressive strength of concrete, in MPa; To and The corresponding peak compressive strain; To normalize the strain ratio, ; It is a uniaxial compressive strain; The parameters for the pressure drop section are used to control the steepness of the pressure softening section. The shape parameters of the pressure-bearing rising section (controlling the degree of bending of the rising section). .

[0053] The calculation parameters for plastic damage in concrete are shown in Table 3, and the concrete strain-stress-damage factor curves are shown in Table 3. Figure 6 As shown.

[0054] Table 3 Calculation parameters for plastic damage in concrete

[0055] The stress field results from step 3 are then imported into a predefined field to calculate and output the damage and cracking results during concrete construction and curing.

[0056] The ABAQUS numerical simulation calculation process for steps 1-4 above is as follows: Figure 2 As shown.

[0057] Step 5: Deploy sensors at the large-volume concrete pouring site to monitor the temperature and strain changes of the concrete in real time. Feedback is then sent to the numerical model for verification and correction, thereby predicting the location of cracks during construction and curing. Further steps include: Step 5.1 involves embedding vibrating wire concrete-embedded strain gauges in layers and sections before pouring the concrete structure on site. This is used to acquire real-time time history data of the temperature and strain fields around the embedding points. In this example, the placement and on-site installation of the strain gauges on the base plate are as follows: Figure 4 As shown, one strain gauge is installed at each measuring point, and every two measuring points form a group. The measuring points in each group are arranged in an L-shape orthogonal arrangement to measure the transverse and longitudinal strain of the base plate respectively. The temperature data is taken as the average value of each group.

[0058] Step 5.2: Following Step 2, run the numerical model to calculate the output temperature field results, and verify and adjust the parameters against the field temperature monitoring data fed back by the strain gauge to ensure that the relative error is controlled within 5%. In this example, the test-simulated temperature change curve of typical measuring point 9 on the station floor is shown below. Figure 7 As shown, the error is within 5%.

[0059] Step 5.3, based on step 5.2, calculates the output thermal strain and strain caused by the structure's self-weight according to step 3, and then calculates the shrinkage strain based on the on-site measured strain. In this embodiment, preliminary calculations show that, without considering subsequent construction and other external loads, the strain of the station floor slab is approximately on the order of 1 × 10⁻⁶. -7 Its own weight has little effect on strain and can be ignored, so the calculation formula is as follows: , In the formula, These are the measured values ​​from the strain gauge.

[0060] Step 5.4: Based on Step 5.3, calculate the shrinkage strain according to Step 3, and verify and adjust the parameters with the shrinkage strain calculated in Step 5.3 to ensure that the relative error is controlled within 20%. The strain-age variation curve and the experimental-simulation calculated shrinkage strain variation curve of typical measuring point 9 of the station floor in this embodiment are shown below. Figure 8 As shown, the error is within 15%.

[0061] Furthermore, when the tensile or crushing damage factor is ≥0.9, it indicates that irreversible damage has occurred to the concrete at that location, and its stiffness is approximately zero, which can be considered as concrete fracture. A damage cloud map is output when the tensile damage factor is set to ≥0.9. The simulation results of damage and cracking of the station's floor slab, side walls, and roof slab are compared with the actual cracking results as shown in the following figures. Figure 9 , Figure 10 and Figure 11 As shown, the damage and cracking prediction results are in good agreement with the actual situation, proving that the prediction effect is good.

[0062] Step 6: Based on the numerical model verified and corrected in Step 5, output a damage cloud map. Simultaneously, identify potential damage units in mass concrete during construction and subsequent curing based on tensile cracking damage factors and crushing damage factors. Then, classify and evaluate the damage based on the magnitude of the tensile cracking damage factor and take corresponding measures. It should be noted that the most significant and dangerous disease in mass concrete is tensile cracking caused by temperature and shrinkage; and tensile cracking has the characteristics of sudden and overall failure. Therefore, the classification and evaluation need to accurately capture the cracking evolution and stiffness degradation. Thus, based on the tensile cracking damage factor... Conduct a tiered evaluation.

[0063] Furthermore, the tiered evaluation and corresponding control measures include: when At that time, it was a Level 1 risk zone, and routine maintenance measures were adopted, including covering and insulation, moisture retention maintenance (sprinkling / covering), demolding according to plan, and routine monitoring. when At that time, it was a level-two risk zone, so enhanced maintenance measures were adopted, including thickening the insulation layer, extending the insulation and moisture retention time, delaying the demolding, wind and sun protection, and increasing the monitoring and early warning of key parts; when The area was classified as a Level 3 risk zone, and mandatory maintenance and emergency response measures were adopted, including multi-layer insulation and moisture retention (insulation felt + film covering / spraying moisture retention), significantly delaying demolding and controlling the temperature drop after demolding, sealing and moisturizing in time when cracks appeared, and sealing or grouting repair when necessary.

[0064] This example uses a 25m sidewall cast in situ. A schematic diagram illustrating the three-level cracking risk zone division of the station sidewall is shown below. Figure 12 As shown.

[0065] In summary, this embodiment verifies the effectiveness of the damage cracking prediction and grading evaluation method through engineering simulation. The method realizes the transformation of cracking analysis from point discrimination to global identification and graded control, while taking into account temperature field, shrinkage effect and time-varying characteristics of materials, improving prediction accuracy and operability, and reducing the risk of cracks and leakage.

[0066] The specific embodiments of the present invention have been described in detail above with reference to the figures, but the present invention is not limited to the described embodiments. For those skilled in the art, various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and these variations still fall within the protection scope of the present invention.

Claims

1. A method for predicting and classifying damage and cracking in large-volume concrete pouring considering shrinkage effects, characterized in that, Includes the following steps: Step 1: Establish a geometric model of a large-volume concrete structure. According to the preset construction and pouring plan, the geometric model is divided into layers and meshed. The construction process is simulated by the birth and death element method to construct a numerical model. Step 2: Perform thermal analysis on the numerical model, taking into account the heat release from concrete hydration and dynamic thermal boundary conditions, and calculate the temperature field during construction and curing. Step 3: Perform stress analysis on the numerical model, import the temperature field as a thermal load, and calculate the stress field considering the time-varying characteristics of concrete mechanical properties and shrinkage deformation. The stress analysis includes: specifying the divided mesh elements as C3D8R type, assigning mechanical properties to concrete and steel reinforcement; simulating the changes in the elastic modulus and thermal expansion coefficient of concrete with age by calling the UFIELD and UEXPAN subroutines respectively; defining mechanical boundary conditions including at least the formwork fixed end constraint, the already cast component constraint, and the surrounding rock layer constraint; setting the analysis step and incremental step synchronized with Step 2, importing the temperature field obtained in Step 2 into the predefined field; calling the USDFLD and UEXPAN subroutines, based on the shrinkage prediction model and using the Arrhenius equivalent age to replace the actual time, simulating the shrinkage process of concrete, which includes: Step 3.1: Call the USDFLD subroutine to calculate and output the equivalent age, that is, update the equivalent age with the Arrhenius acceleration factor integral in each incremental step and pass it to the UEXPAN subroutine. Step 3.2: Call the USDFLD subroutine to record the equivalent age for drying start. If the pouring zones or layers are different, the drying start time for each point can be determined by field variables or zone logic. Step 3.3: Call the UEXPAN subroutine to calculate the shrinkage strain based on the equivalent age in Step 3.1 and the equivalent age calculated from the start of drying in Step 3.2, and output the strain increment of the current increment step, save the strain value of the previous increment step, and then perform the calculation of the next increment step. The expression for the change of the elastic modulus of concrete with age is as follows: ， In the formula, For concrete at the age of The elastic modulus at that time; This refers to the elastic modulus of concrete at 28 days of age under standard curing conditions. For calculation parameters; This is the correction factor for mineral admixtures; The model expression for the change of the coefficient of thermal expansion with age is as follows: ， In the formula, Age The coefficient of thermal expansion at that time; The coefficient of thermal expansion at 28 days of age; Hydration time parameters related to admixtures; The formula for calculating temperature strain is as follows: ， In the formula, For temperature strain; T This represents the change in concrete temperature. The formula for calculating the Arrhenius equivalent age is as follows: ， ， In the formula, The running time variable is used during the integration process; and These are the reference temperature and the temperature history, respectively. , and These are the equivalent age, the drying start time, and the actual equivalent conversion age, respectively. It is the apparent activation energy; The ideal gas constant is taken as 8.314 J / (mol·K); The calculation formula for the shrinkage prediction model is as follows: ， In the formula, for The equivalent age at any given moment; for Contraction strain at any moment; For the final contraction strain; Step 4: Perform damage analysis on the numerical model, import the stress field, and use the concrete plastic damage model to calculate the damage and cracking results. The damage analysis includes: assigning parameters to the concrete plastic damage model based on the stress analysis model in Step 3; realizing the time-varying nature of the model parameters as the early mechanical behavior of concrete changes by introducing field variables or calling the UFIELD subroutine; importing the stress field obtained in Step 3 into a predefined field, and calculating and outputting the damage and cracking results. The damage factors in the model are calculated based on the uniaxial stress state of concrete. These damage factors include tensile cracking damage factors and crushing damage factors. The calculation formula for the tensile cracking damage factor is as follows: ， In the formula, It is a tensile damage factor; The coefficient is dimensionless. Normalized strain ratio; For the parameters of the tension-induced descent segment; The formula for calculating the crushing damage factor is as follows: ， In the formula, It is a crushing damage factor; The coefficient is dimensionless. Normalized strain ratio; It is a uniaxial compressive strain; These are the parameters for the pressure-induced descent segment; The shape parameters of the pressure-bearing rising section; Step 5: Deploy sensors at the construction site to monitor the temperature and strain changes of the concrete in real time, and feed the monitoring data back to the numerical model for verification and correction to predict the location of cracks. Step 6: Based on the numerical model verified and corrected in Step 5, output the damage cloud map, identify potential damaged units and divide the crack risk area, conduct graded evaluation according to the damage factor, and take corresponding control measures.

2. The method for predicting and classifying damage and cracking in large-volume concrete pouring considering shrinkage effects according to claim 1, characterized in that: The thermal analysis described in step 2 includes: specifying the divided mesh cells as DC3D8 type, assigning thermophysical properties to the concrete material, defining thermodynamic boundary conditions that include at least the heat exchange between the concrete and air, formwork, and rock strata, and adjusting the convective heat dissipation coefficient and ambient temperature over time by calling the FILM subroutine, while also considering the heat conduction inside the concrete during the pouring process; setting the analysis step and incremental step, and calling the HETVAL subroutine to simulate the hydration heat release process of the concrete based on the composite exponential model.

3. The method for predicting and classifying damage and cracking in large-volume concrete pouring considering shrinkage effects according to claim 2, characterized in that: The thermodynamic boundary conditions for heat exchange include: calculating heat loss due to heat convection and heat radiation using Newton's law of cooling and Stefan-Boltzman's law, respectively; and simulating the convective heat dissipation coefficient and ambient temperature changes over time using the FILM subroutine; wherein the formulas for heat convection and heat radiation are as follows: ， ， In the formula, and These are losses due to heat convection and heat radiation. The convective heat dissipation coefficient; and For concrete temperature and ambient temperature; Thermal emissivity; Let be the Stefan-Boltzman constant, taken as 5.67 × 10⁻⁶. -8 W / (m 2 ·K 4 ); The equation governing heat conduction within the concrete during the pouring process is as follows: ； In the formula, For concrete pouring time; The thermal diffusivity of concrete; For the temperature rise of concrete insulation; , , These are the three directions from which heat originates.

4. The method for predicting and classifying damage and cracking in large-volume concrete pouring considering shrinkage effects according to claim 2, characterized in that, The expression for the heat release model of concrete hydration is: ， In the formula, The heat release rate of the heat source; This represents the maximum heat release during concrete hydration. , The influence coefficient of the model; Among them, the , The results were obtained from a semi-adiabatic temperature rise test, specifically including the following: Step 2.1: Establish a finite element model of the semi-adiabatic temperature rise test device in ABAQUS. Set the concrete specimen to a cube with a side length of 20cm. The specimen is completely wrapped in an insulation box composed of insulation layer. Call the HETVA subroutine to simulate the heat release of concrete hydration based on the composite index model. Step 2.2 involves conducting parameter analysis on the insulation layer thickness, thermodynamic parameters of the insulation material, and external environment, and selecting appropriate test conditions. Step 2.3: Based on the analysis results of Step 2.2, construct the experimental device and embed temperature sensors in the concrete to monitor temperature changes in real time; Step 2.4: Based on the temperature-age test data obtained in Step 2.3, the finite element model from Step 2.1 is called to perform calculations. , Sensitivity analysis was performed, experimental curves were fitted, and finally, applicable parameters were obtained. , .

5. The method for predicting and classifying damage and cracking in large-volume concrete pouring considering shrinkage effects according to claim 1, characterized in that: Step 5 specifically includes: Step 5.1: Before the on-site concrete structure is poured, vibrating wire concrete embedded strain gauges are embedded in layers and sections to obtain real-time temperature and strain field time history data around the embedding points. Step 5.2: Run the numerical model as described in Step 2, calculate the output temperature field results, and verify and adjust the parameters with the field temperature monitoring data fed back by the strain gauge to ensure that the relative error is controlled within 5%. Step 5.3: Based on the model calibration in Step 5.2, calculate the output temperature strain and the strain caused by the structure's self-weight according to Step 3. Calculate the shrinkage strain based on the on-site measured strain. The calculation formula is as follows: ， In the formula, These are the measured values ​​from the strain gauge. This represents the strain value caused by the self-weight of the concrete structure. Step 5.4: Based on the calculation results of Step 5.3, calculate the output shrinkage strain according to Step 3, and verify and adjust the parameters with the shrinkage strain obtained in Step 5.3 to ensure that the relative error is controlled within 20%.

6. The method for predicting and classifying damage and cracking in large-volume concrete pouring considering shrinkage effects according to claim 1, characterized in that, The graded evaluation and corresponding control measures mentioned in step 6 include: When the damage factor is ≥0 and <0.6, it is a level 1 risk area, and routine maintenance measures are adopted, including covering and insulation, moisture retention maintenance, demolding according to plan and routine monitoring. When the damage factor is ≥0.6 and <0.9, it is a level 2 risk area. Enhanced maintenance measures are adopted, including thickening the insulation layer, extending the insulation and moisture retention time, delaying demolding, wind and sun protection, and increasing the monitoring and early warning of key parts. When the damage factor is ≥0.9, it is a level 3 risk zone. Forced maintenance and emergency treatment measures are adopted, including multi-layer heat preservation and moisture retention, significantly delaying demolding and controlling the temperature drop after demolding, timely sealing and moisture retention when cracks appear, and sealing or grouting repair.

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