Method and system for processing strength data of concrete performance

Abstract

The invention provides a strength data processing method and system for concrete performance, and relates to the technical field of data processing.The method comprises the steps that hydration heat temperature strain data of a concrete structure of a super high-rise building foundation is obtained to generate a temperature strain data set with spatial distribution characteristics, and the strength data of the concrete performance is obtained by combining material characteristic parameters of the concrete structure; constructing a concrete three-dimensional entity by using the pre-constructed digital twin model so as to simulate a temperature gradient field, a thermal stress field and a time-space evolution rule of strength development of a concrete structure; based on the space-time evolution rule and different maintenance condition parameters, predicting a strength increase curve of the concrete structure under different maintenance conditions; according to the strength increasing curve, the strength standard probability and the risk threshold value of different curing stages are calculated, strength development simulation and risk early warning of the concrete structure are carried out based on the strength standard probability and the risk threshold value, and the intelligent monitoring and early cracking risk early warning capacity of the concrete strength development process is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a strength data processing method and system for concrete performance. BACKGROUND

[0002] In the foundation construction process of super high-rise buildings, the strength development of mass concrete structures is significantly affected by the hydration heat effect, and the complex coupling of the internal temperature field and stress field can easily cause early cracking, thereby threatening the integrity and durability of the structure. In order to ensure construction quality and structural safety, an engineering practice urgently needs a technical means that can integrate multi-source monitoring data, reflect the material constitutive relationship and have a certain prediction ability, so as to realize scientific management and risk pre-warning of the concrete strength development process and improve the intelligent level of construction decision-making.

[0003] At present, some researches and engineering applications have adopted a modeling method based on finite element simulation and fusion of measured temperature data. By collecting internal temperature time series data after concrete pouring, combining with the thermodynamic parameters of the material, a non-steady-state heat conduction model is constructed, and then the temperature field distribution is deduced and the thermal stress evolution generated thereby is estimated. On this basis, an empirical strength development function is introduced to convert the temperature history into an equivalent age, and further predict the strength growth path of the concrete. However, this method still has obvious limitations in practical application, for example, the model is usually based on static grid division and homogeneous material assumption, which is difficult to fully reflect the non-uniformity of concrete in actual spatial distribution and the dynamic change of boundary conditions, reducing the fine modeling capability of the internal thermal-mechanical coupling behavior of the structure. At the same time, the strength prediction relies on empirical formula and temperature interpolation at discrete time points, lacking real-time dynamic feedback mechanism for multi-physical field coupling, and it is difficult to accurately depict the continuity and uncertainty of strength development. SUMMARY

[0004] The purpose of the present application is to provide a strength data processing method and system for concrete performance, in order to solve the problems of insufficient fine modeling capability of the internal thermal-mechanical coupling behavior of the structure, difficulty in accurately depicting the continuity and uncertainty of strength development, etc. in the prior art.

[0005] To solve the above technical problems, in a first aspect, the present application provides a strength data processing method for concrete performance, comprising: obtaining hydration heat temperature strain data of a concrete structure of a super high-rise building foundation to generate a temperature strain data set with spatial distribution characteristics; constructing a concrete three-dimensional entity by using a pre-constructed digital twin model according to the temperature strain data set and material characteristic parameters of the concrete structure, to simulate the temperature gradient field, thermal stress field and spatio-temporal evolution law of strength development of the concrete structure; Based on the spatio-temporal evolution law and different curing condition parameters, the digital twin model is used to predict the strength growth curve of the concrete structure under different curing conditions. According to the strength growth curve, the strength compliance probability and risk threshold of different curing stages are calculated, and based on the strength compliance probability and risk threshold, the strength development simulation and risk warning of the concrete structure are carried out.

[0006] Optionally, based on the spatio-temporal evolution law and different curing condition parameters, the digital twin model is used to predict the strength growth curve of the concrete structure under different curing conditions, which comprises: Based on the design strength grade of the concrete structure, the climate characteristics of the construction area and the conventional curing scheme, a plurality of curing condition parameters are determined, including curing environment temperature range, environment humidity value, surface covering material type and cooling medium flow; According to the initial strength value, temperature gradient field reference value and thermal stress field reference value of each three-dimensional grid element in the spatio-temporal evolution law, combined with the curing condition parameters, the digital twin model is used to adjust each three-dimensional grid element to obtain adjusted grid parameters, including adjusted temperature change rate, corrected strength growth coefficient, adjusted temperature exchange amount and adjusted stress release rate; According to the preset time interval, the strength increase value of each three-dimensional grid element under the action of the adjusted grid parameters is calculated, and the strength increase value at each time point is accumulated to generate the strength-time curve of each three-dimensional grid element.

[0007] Optionally, according to the initial strength value, temperature gradient field reference value and thermal stress field reference value of each three-dimensional grid element in the spatio-temporal evolution law, combined with the curing condition parameters, the digital twin model is used to adjust each three-dimensional grid element to obtain adjusted grid parameters, including adjusted temperature change rate, corrected strength growth coefficient, adjusted temperature exchange amount and adjusted stress release rate, which comprises: The curing environment temperature range is compared with the temperature gradient field reference value of each three-dimensional grid element in the spatio-temporal evolution law to determine the correlation ratio; If the internal stress of the thermal stress field reference value exceeds the preset range, the correlation ratio is enlarged by a preset ratio to obtain the final correlation ratio, and according to the final correlation ratio, the temperature change rate of each three-dimensional grid element is adjusted by the digital twin model to obtain the adjusted temperature change rate; determine a humidity influence ratio based on the deviation value of the environmental humidity value from the standard curing humidity and the initial strength value of the strength development, and correct a strength growth coefficient corresponding to each three-dimensional grid unit by the digital twin model according to the humidity influence ratio, to obtain a corrected strength growth coefficient; determine a temperature exchange priority direction of the edge region of the concrete structure according to the surface covering material type and the cooling medium flow, in combination with the thermal stress field reference value, to adjust a temperature exchange amount and an internal stress release rate of a corresponding three-dimensional grid unit and an external environment according to the temperature exchange priority direction by the digital twin model, to obtain an adjusted temperature exchange amount and an adjusted stress release rate.

[0008] Optionally, according to the strength growth curve, a strength compliance probability and a risk threshold value of different curing stages are calculated, and based on the strength compliance probability and the risk threshold value, the strength development simulation and risk warning of the concrete structure are carried out, including: The curing process of the concrete structure is divided into multiple curing stages, wherein the division time nodes of each curing stage are determined based on the slope change characteristics of the strength growth curve, and the curing stages include an early curing stage, a middle curing stage and a late curing stage; The cumulative post-strength value of each time point in the strength change curve with time of each curing stage is compared with the corresponding design strength standard value, to calculate the strength compliance probability of each three-dimensional grid unit in the corresponding curing stage; Based on the material strength dispersion coefficient of the concrete and the structural design safety margin, the risk threshold value of each three-dimensional grid unit in the corresponding curing stage is determined, wherein the risk threshold values of different three-dimensional grid units are differentiated according to the corresponding structural importance coefficients; The three-dimensional grid units with a strength compliance probability lower than the risk threshold value are marked as risk areas, and the time point and the duration when the cumulative post-strength value of the risk area is lower than the design strength standard value of the corresponding curing stage are recorded; Based on the strength compliance probability of each three-dimensional grid unit, the risk area, the time point and the duration, a risk warning level is generated to realize the strength development simulation and risk warning of the concrete structure.

[0009] Optionally, generating a risk warning level based on the strength compliance probability of each three-dimensional grid unit, the risk area, the time point and the duration includes: According to the strength compliance probability of each three-dimensional grid unit, the three-dimensional spatial coordinates of the risk area, the time point, and the duration, combined with the concrete three-dimensional entity, the strength development state of the concrete structure at different curing stages is dynamically simulated through the digital twin model, wherein each simulation period is divided according to the division time node of each curing stage; The strength compliance probability distribution density and the risk area proportion of each three-dimensional grid unit in each simulation period are counted, and the difference between the cumulative strength value of all risk areas in each simulation period and the corresponding design strength standard value is calculated; According to the risk area proportion, a plurality of first warning coefficients are set, and according to the difference, a plurality of second warning coefficients are set, different first warning coefficients and second warning coefficients correspond to different warning levels; The first warning coefficient and the second warning coefficient are combined to generate a risk warning level.

[0010] Optionally, the hydration heat temperature strain data of the concrete structure of the super high-rise building foundation is obtained to generate a temperature strain data set with spatial distribution characteristics, including: The temperature values and strain values collected at different time intervals of each sampling point are obtained, the temperature values reflect the hydration heat temperature of the concrete structure, and the strain values reflect the deformation of the concrete structure caused by temperature change; Each sampling point is assigned a preset three-dimensional spatial coordinate, and the three-dimensional spatial coordinate is determined based on the design size of the concrete structure and the sensor deployment position deployed on the concrete structure; The temperature values and strain values of each sampling point are respectively associated with the corresponding three-dimensional spatial coordinates to obtain temperature data and strain data with spatial identifiers; According to the physical position corresponding to the three-dimensional spatial coordinates of each sampling point and the geometric shape of the concrete structure, the concrete structure is divided into a plurality of three-dimensional grid units, and the temperature data and strain data with spatial identifiers belonging to the same three-dimensional grid unit are classified to form the temperature strain data set with spatial distribution characteristics.

[0011] Optionally, according to the temperature strain data set and the material characteristic parameters of the concrete structure, a pre-constructed digital twin model is used to construct a concrete three-dimensional entity to simulate the temperature gradient field, thermal stress field, and spatio-temporal evolution law of strength development of the concrete structure, including: According to the temperature data and strain data of each three-dimensional grid element in the temperature strain data set, and the material characteristic parameters of the concrete structure, a pre-constructed digital twin model is used to generate a concrete three-dimensional entity consistent with the physical form of the concrete structure, the concrete three-dimensional entity being composed of a plurality of three-dimensional grid elements, and the material characteristic parameters including thermal conductivity, specific heat capacity, elastic modulus, and strength growth coefficient; Based on the temperature data of each three-dimensional grid element, the thermal conductivity and the specific heat capacity are combined to calculate the temperature transfer amount and the temperature difference between adjacent three-dimensional grid elements to form a temperature gradient field of the concrete structure; Based on the temperature value and temperature change rate of each three-dimensional grid element in the temperature gradient field, the elastic modulus and the strain data of each three-dimensional grid element are combined to calculate the internal stress and stress direction of each three-dimensional grid element caused by temperature change to form a thermal stress field of the concrete structure; The strength value of each three-dimensional grid element at different times is calculated by combining the internal stress of each three-dimensional grid element in the thermal stress field, the strength growth coefficient, and a preset time step, and the spatiotemporal evolution law of the strength development of the concrete structure is generated by combining the change trend of the temperature gradient field.

[0012] In a second aspect, the present application provides a strength data processing system for concrete performance, comprising: An acquisition module is configured to acquire hydration heat temperature strain data of a concrete structure of an ultra-high-rise building foundation to generate a temperature strain data set with spatial distribution characteristics; A simulation module is configured to use a pre-constructed digital twin model to construct a concrete three-dimensional entity according to the temperature strain data set and the material characteristic parameters of the concrete structure to simulate a temperature gradient field, a thermal stress field, and a spatiotemporal evolution law of strength development of the concrete structure; A prediction module is configured to use the digital twin model to predict the strength growth curve of the concrete structure under different curing conditions based on the spatiotemporal evolution law and different curing condition parameters; A calculation module is configured to calculate the strength compliance probability and risk threshold of different curing stages according to the strength growth curve, and perform strength development simulation and risk warning of the concrete structure based on the strength compliance probability and risk threshold.

[0013] In a third aspect, the present application provides an electronic device, comprising: A memory is configured to store a computer program; A processor is configured to execute the computer program to implement the steps of the strength data processing method for concrete performance according to the first aspect.

[0014] In a fourth aspect, the present application provides a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and the computer program, when executed by a processor, enables the steps of the strength data processing method for concrete performance to be implemented according to the first aspect.

[0015] The application provides a concrete performance strength data processing method, which comprises the following steps: obtaining the hydration heat temperature strain data of the concrete structure of the super-high building foundation, to generate a temperature strain data set with spatial distribution characteristics; according to the temperature strain data set and the material characteristic parameters of the concrete structure, a pre-constructed digital twin model is used to construct a concrete three-dimensional entity to simulate the temperature gradient field, thermal stress field and spatio-temporal evolution law of strength development of the concrete structure; based on the spatio-temporal evolution law and different curing condition parameters, the digital twin model is used to predict the strength growth curve of the concrete structure under different curing conditions; according to the strength growth curve, the strength compliance probability and risk threshold value of different curing stages are calculated, and based on the strength compliance probability and risk threshold value, the strength development simulation and risk warning of the concrete structure are carried out. By obtaining the hydration heat temperature strain data of the concrete structure of the super-high building foundation to generate a data set with spatial distribution characteristics, the non-uniform evolution process of the internal temperature and strain of the structure can be truly reflected, and the simulation distortion problem caused by the homogeneity assumption and static grid division in the traditional method can be overcome; based on the data set, the material characteristic parameters are combined, and the pre-constructed digital twin model is used to construct a concrete three-dimensional entity, so that high-fidelity dynamic simulation of the temperature gradient field, thermal stress field and spatio-temporal evolution law of strength development is realized, the fine characterization ability of the multi-physical field coupling is improved, and the shortcomings of the existing simulation method in the dynamic change of the boundary and the real-time feedback mechanism are made up; further, the digital twin model is used to predict the strength growth curve in combination with different curing condition parameters, which breaks through the continuity and adaptability limitations brought by the traditional empirical formula dependence and discrete interpolation, and enhances the prediction flexibility and accuracy of the strength development path under complex environmental conditions; finally, the strength compliance probability and risk threshold value of each curing stage are calculated according to the strength growth curve, and the strength development simulation and risk warning are carried out accordingly, the probabilistic evaluation mechanism is introduced, the quantitative identification ability of the strength development uncertainty and early cracking risk is improved, and the systematic risk pre-judgment and dynamic response are realized. Further, by dividing the curing process into early, middle and late stages and the like according to the slope change characteristics of the strength growth curve, the scientific division of the key time sequence of strength development is realized, the strength compliance probability of each three-dimensional grid unit is calculated based on the comparison between the cumulative post-strength value and the design standard, the risk threshold value is set in combination with the material discreteness, safety margin and structure importance coefficient difference, and then the risk area with the strength compliance probability lower than the threshold value is identified and marked, the time node and duration of insufficient strength are recorded, and finally the multi-dimensional information such as probability, area distribution and time characteristics is generated to form a graded risk warning, and a closed-loop risk identification and evaluation process is formed.The scientificity and adaptability of the curing stage definition are improved by the stage division method based on the dynamic characteristics of the strength development, deviation caused by fixed time division is avoided, and the response capability of the model to the actual construction rhythm is enhanced; through the coupling analysis mechanism of the grid level strength compliance probability and the differentiated risk threshold, fine risk identification from macro trend to local weak area is realized, the defects that the traditional method only relies on average value or experience judgment and cannot capture spatial non-uniform risk are overcome, the precise positioning and graded early warning capability of the structure early cracking risk are enhanced, and the core bottlenecks of the prior art in non-homogeneous modeling, dynamic feedback deficiency and risk assessment quantization deficiency are broken through. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating laborious work.

[0017] Figure 1 A flowchart of a strength data processing method of concrete performance provided by an embodiment of the present application; Figure 2 A specific implementation schematic diagram of a strength data processing method of concrete performance provided by an embodiment of the present application; Figure 3 A structural schematic diagram of a strength data processing system of concrete performance provided by an embodiment of the present application. DETAILED DESCRIPTION

[0018] For the scenario that the strength development is significantly affected by hydration heat in the construction of super high-rise building mass concrete foundation and needs to dynamically evaluate the curing effect and risk, the prior art relies on the method of combining finite element simulation and empirical strength model, which is difficult to accurately simulate the spatial non-uniformity of materials and the coupling effect of multiple physical fields, has weak response capability to the change of curing conditions, and lacks quantitative evaluation of the strength growth uncertainty and compliance probability. In order to improve the spatio-temporal continuity and risk warning capability of strength development prediction, the present application constructs a temperature strain data set with spatial distribution characteristics by acquiring the hydration heat temperature strain data of the concrete structure, establishes a three-dimensional entity of concrete in a digital twin environment combined with material characteristic parameters, simulates the dynamic process of temperature gradient, thermal stress and strength evolution, and introduces different curing parameters for multi-scenario prediction, and finally calculates the strength compliance probability and risk threshold of each curing stage based on the predicted strength growth curve, realizes the dynamic simulation and risk identification of the whole process of concrete strength development.

[0019] For those skilled in the art to better understand the present application, the present application will be further described in detail below in combination with the drawings and specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present application.

[0020] The core of the present application is to provide a strength data processing method for concrete performance, and a specific embodiment of the method is shown in the flowchart Figure 1 The method comprises: Step 101: Obtain the hydration heat temperature strain data of the concrete structure of the super high-rise building foundation to generate a temperature strain data set with spatial distribution characteristics.

[0021] In this step, the hydration heat temperature strain data refers to the temperature data generated by the concrete during the hydration reaction process and the deformation data caused by the temperature change, which is collected based on the sensors deployed in the concrete structure, reflecting the hydration heat effect and temperature deformation characteristics of the concrete. Spatial distribution characteristics refer to the distribution state of data in the three-dimensional space of the concrete structure, which is determined based on the three-dimensional space coordinates of each sampling point and the three-dimensional grid element to which it belongs, and is used to reflect the differences of data at different positions. The temperature strain data set refers to a set of temperature data and strain data integrated by each three-dimensional grid element, which is obtained by classifying and processing the temperature data and strain data with spatial identifiers according to the three-dimensional grid elements, and is used for subsequent model construction and simulation analysis.

[0022] Step 102: According to the temperature strain data set and the material characteristic parameters of the concrete structure, a digital twin model pre-constructed is used to construct a three-dimensional entity of the concrete to simulate the temperature gradient field, thermal stress field and spatiotemporal evolution law of strength development of the concrete structure.

[0023] In this step, the material property parameter refers to a parameter reflecting the physical and mechanical properties of the concrete material, including the thermal conductivity (reflecting the heat conduction ability), the specific heat capacity (reflecting the heat required for temperature change), the elastic modulus (reflecting the relationship between deformation and stress), and the strength growth coefficient (reflecting the characteristics of strength growth over time), which is determined based on the properties of the concrete material itself and is used to simulate the temperature field, stress field, and strength development. The concrete three-dimensional entity refers to a three-dimensional virtual model consistent with the physical form of the concrete structure, which is constructed by a digital twin model and consists of multiple three-dimensional grid elements corresponding to the spatial division of the actual concrete structure, and is used to simulate and display data such as temperature, stress, and strength. The temperature gradient field refers to a field distribution reflecting the temperature distribution and change trend inside the concrete structure, which is calculated based on the temperature transfer amount and temperature difference of adjacent three-dimensional grid elements, and is used to reflect the temperature difference and transmission characteristics at different positions. The thermal stress field refers to a field distribution reflecting the internal stress distribution inside the concrete structure caused by temperature change, which is calculated based on the temperature value and temperature change rate in the temperature gradient field, combined with the elastic modulus and strain data, and is used to reflect the numerical value and directional characteristics of the internal stress. The spatio-temporal evolution law of strength development refers to the law of concrete strength change with time and spatial position, which is generated based on the strength value of each three-dimensional grid element at different times and the change trend of the temperature gradient field, and is used to reflect the development characteristics of strength in the time and space dimensions.

[0024] Step 103: Based on the spatio-temporal evolution law and different curing condition parameters, the digital twin model is used to predict the strength growth curve of the concrete structure under different curing conditions.

[0025] In this step, the curing condition parameter refers to a parameter affecting the curing effect of concrete, including the curing environment temperature range, the environmental humidity value, the surface covering material type, and the cooling medium flow, which is determined based on the design strength grade, the climate characteristics, and the conventional curing scheme, and is used to simulate the influence of different curing conditions on strength growth. The strength growth curve refers to a curve reflecting the change of concrete strength with time, which is generated based on the cumulative strength value of each three-dimensional grid element under the action of the adjusted grid parameters, and is used to reflect the strength state at different time points.

[0026] Step 104: According to the strength growth curve, the strength compliance probability and risk threshold of different curing stages are calculated, and based on the strength compliance probability and risk threshold, the strength development simulation and risk warning of the concrete structure are carried out.

[0027] In this step, the strength compliance probability refers to the proportion of time points at which the strength of the three-dimensional grid unit reaches the corresponding design strength standard value in a certain maintenance stage, which is calculated by comparing the cumulative strength value with the design strength standard value, and is used to measure the possibility of strength compliance. The risk threshold refers to the lower limit value of the strength compliance probability for judging whether there is a risk in the development of strength, which is determined based on the strength dispersion coefficient of concrete material, the structural design safety margin and the structural importance coefficient, and is used to define the risk area.

[0028] The embodiment of the present application realizes fine simulation of the temperature gradient field, the thermal stress field and the spatio-temporal evolution law of strength development, overcomes the problem of insufficient reflection of non-uniformity caused by the static grid and the homogeneous material assumption; by introducing different maintenance condition parameters to dynamically adjust the grid parameters and predict the strength growth curve, a dynamic feedback mechanism of multi-physical field coupling is established, solving the problem of insufficient strength prediction accuracy caused by relying on empirical formula and discrete interpolation; the strength development simulation and risk warning in different maintenance stages are realized, multi-source monitoring data and material constitutive relationship are fused, the scientific management ability and risk pre-warning level of the concrete strength development process are improved, intelligent support is provided for construction decision of super high-rise building foundation mass concrete, which helps to reduce the early cracking risk and ensure the integrity and durability of the structure.

[0029] The present application provides a specific embodiment, step 101, obtaining the hydration heat temperature strain data of the concrete structure of the super high-rise building foundation to generate a temperature strain data set with spatial distribution characteristics, specifically including the following steps: Step 101: obtaining temperature values and strain values collected at different time intervals at each sampling point, wherein the temperature values reflect the hydration heat temperature of the concrete structure, and the strain values reflect the deformation of the concrete structure caused by temperature change.

[0030] In this step, the strain value refers to the quantitative value of the deformation degree of the concrete structure caused by temperature change, which is collected based on the strain sensor deployed at the sampling point, and reflects the shrinkage or expansion state of the concrete under the action of hydration heat.

[0031] In the embodiment of the present application, a plurality of sampling points are preset inside and on the surface of the concrete structure of the super high-rise building foundation, a sensor capable of simultaneously collecting temperature and strain is deployed at each sampling point, different time intervals are set according to the intensity of the concrete hydration reaction, such as collecting once every 2 hours in the early stage and once every 12 hours in the later stage, and the temperature value (which directly reflects the internal temperature caused by the heat released by the concrete hydration reaction) and the strain value (which directly reflects the shrinkage or expansion deformation of the concrete structure caused by temperature change) of each sampling point are recorded in real time by the sensor.

[0032] Step 102: assigning a preset three-dimensional spatial coordinate to each sampling point, the three-dimensional spatial coordinate being determined based on the design size of the concrete structure and the sensor deployment position deployed on the concrete structure.

[0033] In this step, the preset three-dimensional spatial coordinate refers to the x, y, z three-dimensional coordinate previously set for each sampling point, which is used to identify the spatial position of the sampling point in the structure.

[0034] In the embodiment of the present application, the design size such as length, width and height of the concrete structure is obtained according to the design drawing of the concrete structure, a three-dimensional coordinate system is established with a fixed corner of the structure as the coordinate origin (such as the lower left corner of the foundation bottom surface) (the x-axis is along the length direction, the y-axis is along the width direction, and the z-axis is along the height direction), and then the corresponding x, y, z coordinate values (i.e. the preset three-dimensional spatial coordinate) are assigned to each sampling point according to the actual physical position of the sensor deployment (such as the x-direction distance, y-direction distance and z-direction distance from the origin).

[0035] Step 103: associating the temperature value and the strain value of each sampling point with the corresponding three-dimensional spatial coordinate respectively to obtain temperature data and strain data with spatial identification.

[0036] In this step, the temperature data with spatial identification refers to the temperature data containing the three-dimensional spatial coordinate of the sampling point, which is used to reflect the spatial distribution position of the temperature value in the concrete structure. The strain data refers to the strain data obtained by associating the strain value with the three-dimensional spatial coordinate, which is used for subsequent analysis of the relationship between temperature change and deformation.

[0037] In the embodiment of the present application, the temperature value collected by each sampling point at a certain moment is bound with the three-dimensional spatial coordinate (x, y, z) of the sampling point to form temperature data with spatial identification containing [coordinate, temperature value, time]; similarly, the strain value of each sampling point is bound with the corresponding three-dimensional spatial coordinate to form strain data with spatial identification containing [coordinate, strain value, time], so that each item of temperature and strain data can correspond to a specific spatial position.

[0038] Step 104: dividing the concrete structure into a plurality of three-dimensional grid units according to the physical position corresponding to the three-dimensional spatial coordinate of each sampling point and the geometric shape of the concrete structure, and classifying the temperature data and strain data with spatial identification belonging to the same three-dimensional grid unit to form the temperature strain data set with spatial distribution characteristics.

[0039] In this step, the physical position refers to the actual position of each sampling point in the concrete structure, such as the inside of the structure, the surface, the corner, etc., which is determined based on the three-dimensional spatial coordinates of the sampling points corresponding to the position on the structure entity. The geometric shape refers to the external shape and internal structural features of the concrete structure, such as a cuboid, a ladder shape, with grooves, etc., which is determined based on the design drawings of the structure and the actual construction form. The three-dimensional grid element refers to a small spatial element (such as a cube) that is divided according to the preset size of the concrete structure based on the geometric shape of the structure and the physical position of the sampling points, which is used for spatial subdivision of the structure to reflect the spatial distribution of data.

[0040] In the embodiment of the present application, according to the actual physical position (such as the inside of the structure, the surface, the corner, etc.) corresponding to the three-dimensional spatial coordinates of each sampling point and the geometric shape (such as a cuboid, a ladder shape, etc.) of the concrete structure, the entire concrete structure is divided into a plurality of continuous three-dimensional grid elements according to a preset size (such as 1m x 1m x 1m); then by judging whether the coordinates of each space-identified temperature data and strain data fall within the coordinate range of a certain three-dimensional grid element, all temperature data and strain data belonging to the same three-dimensional grid element are grouped together, and finally the grouping data of all three-dimensional grid elements are integrated to form a temperature and strain data set that can reflect the differences in data at different spatial positions.

[0041] The embodiment of the present application realizes the association of temperature and strain data with spatial position, solves the problem of traditional data collection which only focuses on time dimension and lacks spatial information, enables the data to accurately reflect the hydration heat temperature and deformation difference at different positions of the concrete structure, provides fine basic data for subsequent construction of three-dimensional entity, simulation of temperature gradient field and thermal stress field using digital twin model, improves the ability to depict the internal non-uniformity of the concrete structure, and lays a data foundation for the accuracy of subsequent strength development simulation and risk warning.

[0042] The present application provides a specific embodiment, step 102, according to the temperature and strain data set and the material characteristic parameters of the concrete structure, using a pre-constructed digital twin model, a concrete three-dimensional entity is constructed to simulate the temperature gradient field, thermal stress field and spatio-temporal evolution law of strength development of the concrete structure, which specifically includes the following steps: Step 201: According to the temperature data and strain data of each three-dimensional grid element in the temperature and strain data set, and the material characteristic parameters of the concrete structure, a pre-constructed digital twin model is used to generate a concrete three-dimensional entity consistent with the physical form of the concrete structure, the concrete three-dimensional entity is composed of a plurality of three-dimensional grid elements, and the material characteristic parameters include thermal conductivity, specific heat capacity, elastic modulus and strength growth coefficient.

[0043] In this step, the strength growth coefficient refers to a quantitative parameter reflecting the rate of growth of concrete strength with time, which is obtained based on experimental data of material proportions of concrete (cement type, admixture ratio, etc.), hydration reaction characteristics and curing environment characteristics, and is used to calculate the concrete strength value at different times in combination with time and internal stress, reflecting the speed of strength growth.

[0044] In the embodiment of the present application, the temperature data and strain data of each three-dimensional grid element in the temperature strain data set, and the material characteristic parameters of the concrete are input into the pre-constructed digital twin model, the model restores the actual size, shape and internal grid division of the concrete structure based on these data, and generates a concrete three-dimensional entity composed of multiple three-dimensional grid elements, which completely matches the physical structure form.

[0045] Step 202: Based on the temperature data of each three-dimensional grid element, the temperature transfer amount and temperature difference between adjacent three-dimensional grid elements are calculated in combination with the thermal conductivity and specific heat capacity, to form a temperature gradient field of the concrete structure.

[0046] In this step, the temperature transfer amount refers to the amount of heat transferred between adjacent three-dimensional grid elements per unit time, which is calculated based on the thermal conductivity, temperature difference and distance between the two elements, and is used to reflect the transfer efficiency and path of temperature in the concrete structure, and is a core parameter for constructing the temperature gradient field.

[0047] In the embodiment of the present application, the temperature data of each three-dimensional grid element at the same time is extracted, for each two adjacent three-dimensional grid elements, the thermal conductivity is multiplied by the temperature difference of the two elements (i.e. the difference between the temperature values of adjacent elements), and then divided by the distance between the centers of the two elements, to obtain the temperature transfer amount (reflecting the amount of heat transferred per unit time) of the adjacent elements; at the same time, the difference between the temperature values of the two elements (the temperature difference between the high-temperature element and the low-temperature element) is calculated; based on the temperature transfer amount and temperature difference of all adjacent elements, the gradient trend of temperature change (such as the change rate from high-temperature area to low-temperature area) is drawn according to the spatial distribution rule, to form a temperature gradient field.

[0048] Step 203: Based on the temperature value and temperature change rate of each three-dimensional grid element in the temperature gradient field, the internal stress and stress direction of each three-dimensional grid element caused by temperature change are calculated in combination with the elastic modulus and the strain data of each three-dimensional grid element, to form a thermal stress field of the concrete structure.

[0049] In the embodiment of the present application, the current temperature value and the temperature change rate (the change amount of the temperature value divided by the time interval) of each three-dimensional grid unit in the temperature gradient field are obtained, the temperature change rate is multiplied by the elastic modulus of the unit, and the internal stress (reflecting the size of the force resisting deformation) generated by the temperature change is obtained in combination with the strain data (the deformation amount caused by the temperature change); the stress direction (the compression stress direction when expanding, and the tensile stress direction when shrinking) is determined according to the direction of the temperature change (such as expansion by heating or shrinkage by cooling); and the internal stress size and direction of all three-dimensional grid units are integrated according to the spatial distribution to form a thermal stress field.

[0050] In step 204, the internal stress of each three-dimensional grid unit in the thermal stress field, the strength growth coefficient, and the preset time step are combined to calculate the strength value of each three-dimensional grid unit at different times, and the time-space evolution law of the strength development of the concrete structure is generated in combination with the change trend of the temperature gradient field.

[0051] In this step, the preset time step refers to the time interval (such as 12 hours or 1 day) set when calculating the concrete strength value, which is determined based on the rate of concrete strength growth (early growth is fast, so the step is short, and late growth is slow, so the step is longer) and the simulation accuracy requirement, and is used to accumulate the strength increase value step by step to obtain the strength value at different times, and is the basis for realizing the time dimension simulation of the strength development.

[0052] In the embodiment of the present application, the internal stress of each three-dimensional grid unit in the thermal stress field (excessive internal stress inhibits strength growth) is extracted, the internal stress is multiplied by the strength growth coefficient (reflecting the proportion of strength growth per unit time), and then multiplied by the preset time step (such as 1 day, that is, the time interval for calculating the strength), to obtain the strength increase value in the time step; the initial strength value is accumulated with the strength increase value of each time step to obtain the strength value at different times; and the influence of temperature on the strength growth is analyzed in combination with the change trend (such as the regional distribution change of temperature rise or fall) of the temperature gradient field, and finally the strength values of each three-dimensional grid unit at different times and different spatial positions are integrated to form the time-space evolution law of the strength development.

[0053] In the embodiment of the present application, the temperature strain data and material characteristic parameters are integrated by the digital twin model to construct a concrete three-dimensional entity consistent with the physical form of the concrete structure, breaking through the limitations of the static grid and homogeneous material assumption in the traditional method; the dynamic simulation of the temperature gradient field, the thermal stress field, and the time-space evolution law of the strength development is realized, overcoming the problem of insufficient description of the internal non-uniformity and the coupling effect of multiple physical fields in the traditional model; high-precision basic data support is provided for subsequent prediction of the strength growth curve and risk warning under different curing conditions, and the fine control ability of the concrete strength development process is improved.

[0054] The present application provides a specific embodiment, such as Figure 2 As shown in step 103, based on the spatio-temporal evolution law and different curing condition parameters, the digital twin model is used to predict the strength growth curve of the concrete structure under different curing conditions, specifically including the following steps: Step 301: Based on the design strength grade of the concrete structure, the climate characteristics of the construction area, and the conventional curing scheme, a plurality of sets of curing condition parameters are determined, including curing environment temperature range, environment humidity value, surface covering material type, and cooling medium flow.

[0055] In this step, the conventional curing scheme refers to the set of curing methods commonly used in the project for similar concrete structures, including reflecting curing temperature control method, humidity retention measure, covering material selection, and cooling method, etc. It is obtained based on past construction experience and industry standards, and is used as the basis for determining the range of multiple sets of curing condition parameters.

[0056] Step 302: According to the initial strength value of the strength development of each three-dimensional grid element in the spatio-temporal evolution law, the temperature gradient field reference value, and the thermal stress field reference value, combined with the curing condition parameters, the digital twin model is used to adjust each three-dimensional grid element to obtain adjusted grid parameters, including adjusted temperature change rate, corrected strength growth coefficient, adjusted temperature exchange amount, and adjusted stress release rate.

[0057] In this step, the initial strength value of the strength development refers to the quantitative value of the strength of each three-dimensional grid cell at the initial moment of entering the curing stage, reflecting the basic strength state of the concrete at the beginning of curing, and is obtained based on the strength data at the corresponding moment in the spatiotemporal evolution law, which is used as a benchmark for subsequent calculation of strength growth. The reference value of the temperature gradient field refers to the initial temperature distribution and transfer characteristic value of each three-dimensional grid cell in the spatiotemporal evolution law, including temperature value and adjacent cell temperature transfer rate, which is used to compare with the curing environment temperature range to adjust the temperature change rate. The reference value of the thermal stress field refers to the initial internal stress state of each three-dimensional grid cell in the spatiotemporal evolution law, including internal stress size and stress direction, reflecting the internal stress distribution at the beginning of curing, which is used to adjust the stress-related parameters of the grid cell in combination with the curing condition parameters. The adjusted grid parameters refer to the parameter set of the grid cell after adjustment by the digital twin model for calculating the strength growth, including the adjusted temperature change rate, the corrected strength growth coefficient, etc., which is calculated based on the association of the curing condition parameters and the reference value, and is used to accurately simulate the strength development under different curing conditions. The adjusted temperature change rate refers to the corrected rate of temperature change of each three-dimensional grid cell with time under the action of curing conditions, which is obtained based on the associated proportion of the curing environment temperature range and the reference value of the temperature gradient field, reflecting the influence degree of curing temperature on the temperature of the grid cell. The corrected strength growth coefficient refers to the strength growth parameter corrected by the environmental humidity and the initial strength, which is obtained based on the humidity influence proportion determined by the environmental humidity deviation value and the initial strength value of the strength development, and is used to more accurately calculate the strength increase value. The adjusted temperature exchange amount refers to the heat exchange correction amount of the three-dimensional grid cells in the edge area with the external environment, which is obtained based on the surface covering material type, the cooling medium flow and the temperature exchange priority direction, reflecting the heat dissipation or heat preservation effect of the edge area. The adjusted stress release rate refers to the corrected rate of change of the internal stress of the three-dimensional grid cells in the edge area with the temperature exchange, which is associated with the adjusted temperature exchange amount, and is used to simulate the speed of stress release in the edge area.

[0058] Step 303: According to the preset time interval, calculate the strength increase value of each three-dimensional grid cell under the action of the adjusted grid parameters, and accumulate the strength increase value at each time point to generate the strength-time curve of each three-dimensional grid cell.

[0059] In this step, the preset time interval refers to the fixed time period for calculating the strength increase value, such as every 6 hours or 12 hours, which is set based on the rate characteristics of strength growth, and is used to accumulate the strength value in stages to generate the time-varying curve. The strength increase value refers to the strength amount of each three-dimensional grid cell increased within the preset time interval, which is calculated based on the adjusted grid parameters, and is the basis for accumulating the strength value at different times.

[0060] Optionally, in step 302, the initial strength value, the temperature gradient field reference value, and the thermal stress field reference value of each three-dimensional grid cell in the spatio-temporal evolution rule are combined with the curing condition parameters to adjust each three-dimensional grid cell using the digital twin model to obtain adjusted grid parameters, including the adjusted temperature change rate, the corrected strength growth coefficient, the adjusted temperature exchange amount, and the adjusted stress release rate, specifically including the following steps: Step 311: Comparing the curing environment temperature range with the temperature gradient field reference value of each three-dimensional grid cell in the spatio-temporal evolution rule to determine the correlation ratio.

[0061] In this step, the correlation ratio refers to the temperature adjustment ratio coefficient obtained by comparing the curing environment temperature range with the temperature gradient field reference value, reflecting the deviation degree of the curing temperature from the initial temperature field, and used to determine the adjustment amplitude of the temperature change rate.

[0062] Step 312: If the internal stress of the thermal stress field reference value exceeds the preset range, the correlation ratio is enlarged by a preset ratio to obtain a final correlation ratio, and the temperature change rate of each three-dimensional grid cell is adjusted by the digital twin model according to the final correlation ratio to obtain an adjusted temperature change rate.

[0063] In this step, the preset range refers to the threshold range for determining whether the internal stress of the thermal stress field reference value needs to enlarge the correlation ratio, which is set based on the stress bearing capacity characteristics of the concrete material and used to trigger the influence of the internal stress on the adjustment of the temperature change rate. The final correlation ratio refers to the temperature adjustment ratio coefficient corrected by the influence of the internal stress, which is used to determine the final amplitude of the adjusted temperature change rate.

[0064] Step 313: Based on the deviation value of the environment humidity value from the standard curing humidity, the strength development initial strength value is combined to determine the humidity influence ratio, so that the strength growth coefficient corresponding to each three-dimensional grid cell is corrected by the digital twin model according to the humidity influence ratio to obtain a corrected strength growth coefficient.

[0065] In this step, the standard curing humidity refers to the ideal humidity reference value for the strength growth of concrete, reflecting the best conditions for humidity on the strength development, which is obtained based on material test data and used to calculate the deviation degree of the environment humidity value. The humidity influence ratio refers to the correction ratio of the deviation of the environment humidity value from the standard curing humidity on the strength growth coefficient, which is determined in combination with the strength development initial strength value and used to correct the strength growth coefficient to reflect the influence of the actual humidity.

[0066] Step 314: determining the temperature exchange priority direction of the edge region of the concrete structure according to the surface covering material type and the cooling medium flow, in combination with the thermal stress field reference value, so as to adjust the temperature exchange amount and the internal stress release rate of the corresponding three-dimensional grid unit and the external environment according to the temperature exchange priority direction through the digital twin model, to obtain the adjusted temperature exchange amount and the adjusted stress release rate.

[0067] In this step, the temperature exchange priority direction refers to the main direction of heat exchange between the three-dimensional grid unit of the edge region and the external environment, which is determined based on the surface covering material type, the cooling medium flow and the stress direction of the thermal stress field reference value, and is used to adjust the temperature exchange amount of the edge region. The temperature exchange amount with the external environment refers to the natural heat exchange amount between the grid unit of the edge region and the external environment, which is the basic value before adjustment, and is used to obtain the adjusted temperature exchange amount in combination with the curing condition parameter correction. The internal stress release rate refers to the natural release rate of the internal stress of the grid unit of the edge region with temperature change, which is the basic value before adjustment, and is used to obtain the adjusted stress release rate in combination with the temperature exchange priority direction.

[0068] In the embodiment of the present application, first, a plurality of groups of maintenance condition parameters are determined through step 301, specifically: based on the design strength grade of the concrete structure (such as C40, C50), the climate characteristics of the construction area (such as high temperature and much rain in summer, cold and dry in winter), and the conventional maintenance scheme (such as commonly used thin film moisture preservation, watering cooling, etc.), a plurality of groups of parameters covering different maintenance environment temperature ranges (such as 5-15℃, 15-25℃), environment humidity values (such as 60%, 80%), surface covering material types (such as plastic film, cotton felt), and cooling medium flow rates (such as low speed, medium speed) are screened out, and each group of parameters corresponds to one possible maintenance scene. Secondly, the adjusted grid parameters are obtained by adjusting each three-dimensional grid unit through step 302, specifically: the maintenance environment temperature range (such as 15-25℃) is compared with the temperature gradient field reference value (such as initial temperature 20℃, adjacent unit transfer rate 0.5℃ / h) of each three-dimensional grid unit, the temperature deviation amount (such as 5℃, which is the deviation of the reference temperature 20℃ from the upper limit of the maintenance range 25℃) of the two is calculated, and the correlation ratio is determined according to the proportion of the deviation amount to the reference temperature (such as 5 / 20=25%). If the internal stress (such as 3MPa, the internal stress of a certain unit) in the thermal stress field reference value exceeds the preset range (such as 2MPa), the correlation ratio (25%×1.2=30%) is amplified by a preset ratio (such as 1.2 times) to obtain the final correlation ratio, and based on this, the original temperature change rate (such as 0.3℃ / h) is adjusted to the rate corresponding to 30% (such as 0.3×1.3=0.39℃ / h) through the digital twin model, to obtain the adjusted temperature change rate. Then, the deviation value (-20%) of the environment humidity value (such as 70%) and the standard maintenance humidity (such as 90%) is calculated, and the humidity influence ratio (such as the deviation value weight is increased by 20%) is determined in combination with the initial strength value of the strength development (such as the initial strength of a certain unit is 15MPa, which is lower than the preset threshold 20MPa), and accordingly the strength growth coefficient (such as 0.05 / day) is corrected (such as 0.05×0.8=0.04 / day) through the digital twin model, to obtain the corrected strength growth coefficient. Finally, according to the surface covering material type (such as cotton felt, low thermal conductivity) and the cooling medium flow rate (such as low speed), in combination with the stress direction (such as tensile stress direction in the edge area) of the thermal stress field reference value, the temperature exchange priority direction (such as preferentially dissipating heat from the tensile stress area) is determined, and accordingly the temperature exchange amount (such as the original exchange amount 50J / h is adjusted to 30J / h) and the internal stress release rate (such as the original rate 0.2MPa / h is adjusted to 0.15MPa / h) of the edge area grid unit are adjusted, to obtain the adjusted temperature exchange amount and the adjusted stress release rate, and the above parameters are integrated to form the adjusted grid parameters.Finally, the strength-time curve is generated. Specifically, the strength increase value of each three-dimensional grid unit is calculated based on the adjusted grid parameters (such as the adjusted temperature change rate of 0.39°C / h and the corrected strength growth coefficient of 0.04 / day) at a preset time interval (such as 12 hours), the strength increase value at each time point is accumulated (such as 15 MPa + 0.2 MPa + 0.3 MPa…), and the strength value at different time is obtained, and then the strength-time curve of each three-dimensional grid unit is generated.

[0069] For example, for the concrete structure of A super high-rise building foundation (its design strength grade is C45), first of all, based on its design requirements, the climate characteristics of A region in summer with high temperature and much rain, and the conventional film covering and watering maintenance scheme, 3 groups of maintenance condition parameters are determined: the first group is the maintenance environment temperature range of 20-30°C, the environment humidity value of 85%, the surface covering material is plastic film, and the cooling medium flow rate is low; the second group is the temperature range of 15-25°C, the humidity of 75%, the covering material is cotton felt, and the flow rate is medium; the third group is the temperature range of 25-35°C, the humidity of 90%, the covering material is plastic film, and the flow rate is high. Then, the initial strength value of the strength development of each three-dimensional grid unit (such as most units are 18 MPa), the reference value of the temperature gradient field (such as the average initial temperature is 22°C, and the adjacent unit transfer rate is 0.4°C / h), and the reference value of the thermal stress field (such as the average internal stress is 2.5 MPa, and the edge area is tensile stress) are extracted from the spatio-temporal evolution law. For the first group of parameters, 20-30°C is compared with the reference value of the temperature gradient field, and the correlation ratio is 10%; because the internal stress of 2.5 MPa exceeds the preset range of 2 MPa, the correlation ratio is enlarged by 1.1 times according to the preset ratio, and the adjusted temperature change rate is 1.11 times of the original rate; the deviation value of the environment humidity of 85% and the standard curing humidity of 90% is -5%, combined with the initial strength of 18 MPa (lower than the threshold of 20 MPa), the humidity influence ratio is determined to be 95%, and the corrected strength growth coefficient is 0.95 times of the original coefficient; the temperature exchange priority direction is determined to be vertical to the surface and outward combined with the plastic film (low thermal conductivity), low flow rate, and tensile stress direction, the adjusted temperature exchange amount is 0.8 times of the original amount, and the adjusted stress release rate is 0.8 times of the original rate. Finally, the strength increase value of each unit under the adjusted grid parameters is calculated at a preset time interval of 12 hours (such as 0.3 MPa in the first 12 hours), and the strength value at each time point is accumulated (such as 18.3 MPa after 12 hours and 18.7 MPa after 24 hours…), and the strength-time curve of each three-dimensional grid unit is generated.

[0070] The embodiment of the present application determines multiple sets of maintenance condition parameters by combining design requirements, climate characteristics and conventional schemes, ensures the practicability and coverage of the parameters, adjusts the grid unit parameters based on the correlation between the benchmark value and the maintenance parameters by using the digital twin model, realizes the fine simulation of different maintenance conditions, and overcomes the limitation that the traditional empirical formula is difficult to reflect the coupling influence of multiple factors; the strength increase value is calculated and accumulated in stages to generate a change curve, which accurately depicts the development characteristics of the strength of each grid unit over time, provides a reliable basis for analyzing the strength compliance under different maintenance conditions, and improves the accuracy of concrete strength prediction and the scientificity of maintenance scheme optimization.

[0071] The present application provides an embodiment, step 104, calculating the strength compliance probability and risk threshold of different maintenance stages according to the strength growth curve, and based on the strength compliance probability and risk threshold, simulating the strength development of the concrete structure and conducting risk warning, specifically including the following steps: Step 401: dividing the maintenance process of the concrete structure into multiple maintenance stages, wherein the division time nodes of each maintenance stage are determined based on the slope change characteristics of the strength growth curve, and the maintenance stages include early maintenance stage, middle maintenance stage and late maintenance stage.

[0072] In this step, the slope change characteristics refer to the increasing and decreasing trend and turning point characteristics of the slope in the strength growth curve, reflecting the change law of the concrete strength growth rate (such as large early slope and small late slope), which is calculated based on the first derivative of the curve and used to determine the division time nodes of the maintenance stages. The early maintenance stage refers to the initial stage of rapid strength growth after concrete pouring, usually corresponding to the period with the largest slope of the strength growth curve, reflecting the stage with the most intense hydration reaction, which is divided based on the first significant turning point in the slope change characteristics and used to focus on the monitoring of early strength development. The middle maintenance stage refers to the intermediate stage of slowing down but still growing strength, corresponding to the period with gradually decreasing slope of the strength growth curve, reflecting the stage of stable hydration reaction, which is divided based on the second turning point in the slope change characteristics and used to monitor the stability of strength growth. The late maintenance stage refers to the final stage of the strength growth rate tending to be flat, corresponding to the period with a slope close to zero of the strength growth curve, reflecting the stage of basically completed hydration reaction, which is divided based on the last turning point in the slope change characteristics and used to confirm whether the strength meets the design standard.

[0073] Step 402: comparing the cumulative post-strength value of each time point in the strength-time curve of each maintenance stage with the corresponding design strength standard value to calculate the strength compliance probability of each three-dimensional grid unit in the corresponding maintenance stage.

[0074] In this step, the cumulative post-strength value refers to the total strength value after the strength increase value of each time point is accumulated, reflecting the actual strength level of the concrete at a certain time, which is obtained based on the strength increase value accumulated in a preset time interval, and is used for comparison with the design strength standard value. The design strength standard value refers to the minimum strength requirement that the concrete should reach at the corresponding curing stage, reflecting the basic requirement of structural safety on strength, which is determined based on the structural design specification and the concrete strength grade, and is used to measure whether the strength meets the standard.

[0075] Step 403: Based on the material strength dispersion coefficient of the concrete and the structural design safety margin, determine the risk threshold value of each three-dimensional grid element at the corresponding curing stage, wherein the risk threshold values of different three-dimensional grid elements are differentiated according to the corresponding structural importance coefficients.

[0076] In this step, the material strength dispersion coefficient refers to a parameter reflecting the uniformity of the concrete material strength distribution, representing the fluctuation degree of the same batch of material strength, which is calculated based on the ratio of the standard deviation to the average value of the material test data, and is used to determine the basic range of the risk threshold value. The structural design safety margin refers to the strength redundancy set to ensure structural safety, reflecting the difference between the design strength and the actual demand, which is determined based on the structural importance and load characteristics, and is used to adjust the risk threshold value to improve safety. The structural importance coefficient refers to the weight coefficient set according to the structural function importance of the location where the three-dimensional grid element is located (such as high core area coefficient), reflecting the influence degree of different positions on the overall safety of the structure, which is obtained based on the key part division in the structural design drawing, and is used to differentiate the risk threshold value.

[0077] Step 404: Mark the three-dimensional grid elements with a strength compliance probability lower than the risk threshold value as risk areas, and record the time point and duration when the cumulative post-strength value of the risk area is lower than the design strength standard value of the corresponding curing stage.

[0078] In this step, the risk area refers to a set of three-dimensional grid elements with a strength compliance probability lower than the risk threshold value, reflecting the parts in the concrete structure where the strength development has hidden dangers, which is determined based on the comparison result of the compliance probability and the risk threshold value, and is used for focused risk monitoring.

[0079] Step 405: Based on the strength compliance probability of each three-dimensional grid element, the risk area, the time point, and the duration, generate a risk warning level, realizing the strength development simulation and risk warning of the concrete structure.

[0080] In this step, the risk warning level refers to the warning level divided according to the severity of the risk area (such as first, second, and third), reflecting the emergency degree of the strength development risk, which is obtained based on the combination of the risk area proportion and the strength difference, and is used to intuitively present the warning result.

[0081] Optionally, at step 405, a risk warning level is generated based on the strength compliance probability of each three-dimensional grid unit, the risk area, the time point, and the duration, specifically including the following steps: Step 411: According to the strength compliance probability of each three-dimensional grid unit, the three-dimensional spatial coordinates of the risk area, the time point, and the duration, and in combination with the three-dimensional entity of concrete, the strength development state of the concrete structure at different curing stages is dynamically simulated through the digital twin model, wherein each simulation period is divided according to the division time node of each curing stage.

[0082] In this step, the strength development state refers to the strength distribution and change trend of concrete at different curing stages, reflecting the strength compliance of each three-dimensional grid unit, which is obtained based on the dynamic simulation of the digital twin model and used for visualizing the strength development process. The simulation period refers to the dynamic simulation time interval corresponding to the curing stage, and the duration of each period is consistent with the corresponding curing stage, which is determined based on the division time node of the curing stage and used for phased statistical risk data. The division time node refers to the specific time point separating different curing stages, reflecting the key turning point of the strength growth rate, which is determined based on the slope change characteristics of the strength growth curve and used to define the start and end time of each curing stage.

[0083] Step 412: The strength compliance probability distribution density and the risk area proportion of each three-dimensional grid unit in each simulation period are counted, and the difference between the cumulative strength value of all risk areas in each simulation period and the corresponding design strength standard value is calculated.

[0084] In this step, the strength compliance probability distribution density refers to the distribution density of the strength compliance probability of each three-dimensional grid unit in space, reflecting the spatial aggregation characteristics of the compliance probability, which is obtained based on the spatial distribution statistics of the compliance probability data and used for analyzing the concentrated area of risk. The risk area proportion refers to the proportion of the number of three-dimensional grid units in the risk area to the total number of units, reflecting the size of the risk range, which is calculated based on the ratio of the number of risk area units to the total number of units and used to set the first warning coefficient.

[0085] Step 413: According to the risk area proportion, a plurality of first warning coefficients are set, and according to the difference, a plurality of second warning coefficients are set, and different first and second warning coefficients correspond to different warning levels.

[0086] In this step, the first early warning coefficient refers to the early warning weight coefficient set according to the proportion of the risk area, reflecting the influence of the risk range on the early warning level, obtained based on the interval division of the proportion, and used to combine the second early warning coefficient to generate the final early warning level. The second early warning coefficient refers to the early warning weight coefficient set according to the risk area intensity difference, reflecting the influence of the intensity deficiency degree on the early warning level, obtained based on the interval division of the difference, and used to combine the first early warning coefficient to generate the final early warning level.

[0087] Step 414: combining the first early warning coefficient and the second early warning coefficient to generate a risk early warning level.

[0088] In the embodiment of the present application, first, the maintenance stage is divided through step 401, specifically: the slope change characteristics of the strength growth curve are extracted (such as calculating the slope of each point of the curve, identifying the turning point where the slope changes from rapid increase to decrease), the initial stage with the largest slope is divided into the early maintenance stage, the intermediate stage with gradually decreasing slope is divided into the middle maintenance stage, and the stage with gradually decreasing slope is divided into the late maintenance stage, and the division time nodes of each stage are determined (such as early stage 0-7 days, middle stage 7-28 days, and late stage 28 days later). Secondly, the strength compliance probability is calculated through step 402, specifically: for each maintenance stage, the strength change curve of each three-dimensional grid element with time is extracted, the cumulative strength value at each time point in the curve is obtained (such as the cumulative strength of 20 MPa at the third day of the early stage), and the cumulative strength value is compared with the design strength standard value (such as 25 MPa required in the early stage), the proportion of the number of time points at which the cumulative strength value reaches the standard value to the total number of time points is calculated, and the strength compliance probability of each three-dimensional grid element in the corresponding stage is obtained. Then, the risk threshold is determined through step 403, specifically: based on the material strength dispersion coefficient of concrete (such as the coefficient value reflecting the strength fluctuation) and the structural design safety margin (such as the additional strength redundancy), the base value of the risk threshold is calculated; then, according to the structural importance coefficient of each three-dimensional grid element (such as the core area coefficient 1.2 and the edge area 0.8), the base value is differentiated adjusted (the threshold value is increased in the core area and decreased in the edge area), and the corresponding risk threshold of each unit is obtained. Then, the risk area is marked through step 404, specifically: the strength compliance probability of each three-dimensional grid element is compared with the corresponding risk threshold, if the compliance probability is lower than the threshold, the unit is marked as a risk area; at the same time, the specific time point (such as the fifth day) and the duration (such as from the fifth day to the eighth day, a total of three days) of the cumulative strength value lower than the design strength standard value in the risk area are recorded. Finally, the risk warning level is generated through step 405, specifically: the strength compliance probability of each three-dimensional grid element, the three-dimensional space coordinates of the risk area, the recorded time point and the duration are input into the digital twin model, combined with the three-dimensional entity of concrete, the simulation period is set according to the division time node of the maintenance stage (such as early stage 0-7 days), and the strength development state of each stage is dynamically simulated (such as visualizing the spatio-temporal distribution of the strength of each unit). Step 412 is executed, in each simulation period, the distribution density of the strength compliance probability of each unit (such as which areas have a compliance probability of more than 80%) and the proportion of the risk area (such as the proportion of the risk unit to the total unit) are calculated, and the difference between the cumulative strength value of the risk area and the design standard value (such as an average of 5 MPa) is calculated. According to the proportion of the risk area, the first warning coefficient is set (such as the higher the proportion, the higher the coefficient), and according to the strength difference, the second warning coefficient is set (such as the larger the difference, the higher the coefficient). The first warning coefficient and the second warning coefficient are combined to generate the risk warning level, realizing the strength development simulation and risk warning.

[0089] For example, for the A-super high-rise building foundation C45 concrete structure, the generated strength-time curve is continued, first, the curing stage is divided, specifically, by analyzing the slope change of the curve, it is found that the slope is maximum (the strength grows rapidly) from 0 to 7 days, which is divided into the early curing stage; the slope gradually decreases (the growth slows down) from 7 to 28 days, which is divided into the middle curing stage; the slope is close to 0 (the growth is flat) after 28 days, which is divided into the late curing stage. Second, the compliance probability is calculated: the design strength standard value of the early stage is 30 MPa, the strength curve of a certain three-dimensional grid element is extracted, the cumulative strength value of which is 28 MPa (not up to standard) on the 3rd day, 32 MPa (up to standard) on the 5th day, and 35 MPa (up to standard) on the 7th day, the total time point is 3, the up-to-standard time point is 2, and therefore the early compliance probability is 2 / 3. Next, the risk threshold is determined: based on the material strength dispersion coefficient and the design safety margin, the foundation threshold is 70%; the element is located in the core area, and the structure importance coefficient is 1.1, so the risk threshold is adjusted to 77%. Then, the risk area is marked: the early compliance probability of the element is 67%, which is lower than 77%, and therefore the element is marked as a risk area, and the time point at which the cumulative strength value of the element is lower than 30 MPa is recorded as the 3rd day, and the duration is 1 day (the 3rd day). Finally, the warning level is generated: inputting the above data into the digital twin model, setting the simulation period as the early stage (0-7 days), the simulation shows that the risk area is concentrated in the edge of the core area; the risk area accounts for 15%, and the first warning coefficient is set to 2; the average strength difference of the risk area is 2 MPa, and the second warning coefficient is set to 1; the two are combined to generate a secondary risk warning, and the simulation and warning of the strength development in this stage are realized.

[0090] The embodiment of the present application divides the curing stage based on the slope change characteristics of the strength growth curve, realizes the accurate focus on different stages of strength development, calculates the compliance probability by comparing the cumulative strength value with the design standard value, sets the risk threshold in combination with the material characteristics and the structure importance, improves the accuracy of risk identification, dynamically simulates the strength development state through the digital twin model, generates the warning level in combination with the risk area ratio and the strength difference, overcomes the limitations of the traditional method that the risk warning is general and lacks spatial targeting, realizes the fine monitoring and risk pre-warning of the concrete strength development, and provides scientific protection for the construction safety of the super high-rise building foundation concrete.

[0091] Figure 3 A structural schematic diagram of a specific implementation of a concrete performance strength data processing system provided by the embodiment of the present application, referring to Figure 3 The system can include: The acquisition module 21 is configured to acquire the hydration heat temperature strain data of the concrete structure of the super high-rise building foundation to generate a temperature strain data set with spatial distribution characteristics. The simulation module 22 is configured to construct a concrete three-dimensional entity by using a pre-constructed digital twin model according to the temperature strain data set and the material characteristic parameters of the concrete structure, so as to simulate the temperature gradient field, the thermal stress field and the spatio-temporal evolution law of the strength development of the concrete structure. The prediction module 23 is configured to predict the strength growth curve of the concrete structure under different curing conditions by using the digital twin model based on the spatio-temporal evolution law and different curing condition parameters. The calculation module 24 is configured to calculate the strength compliance probability and the risk threshold of different curing stages according to the strength growth curve, and perform the strength development simulation and risk warning of the concrete structure based on the strength compliance probability and the risk threshold.

[0092] The strength data processing system for concrete performance provided in the embodiments of the present application is used to implement the strength data processing method for concrete performance described above, and the specific embodiments of the strength data processing system for concrete performance can be found in the foregoing embodiment part of the strength data processing method for concrete performance, and the specific embodiments can be referred to the description of the corresponding embodiment part, which will not be described herein again.

[0093] The present application also provides an electronic device, comprising: a memory for storing a computer program; a processor for executing the computer program to implement the steps of any one of the strength data processing methods for concrete performance described above.

[0094] The present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of any one of the strength data processing methods for concrete performance described above.

[0095] In an exemplary embodiment, the computer readable storage medium described above can include, but is not limited to, a U disk, a read-only memory, a random access memory, a mobile hard disk, a magnetic disk or an optical disk, and various media that can store computer programs.

[0096] The embodiments of the present application also provide a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps in the embodiments of any one of the strength data processing methods for concrete performance described above.

[0097] Those skilled in the art will further realize that the mechanisms of the various examples described herein are capable of being implemented using computer software, firmware, hardware, or combinations of them, and that the various examples give the necessary control signals and data information to a responsible application-specific computer or network component to cause the computer or network component to implement various aspects of the mechanisms effectively. The computer software referred to herein can be stored in main memory and / or secondary memory application-specific or network computer-readable media as computer program code means, which can be executed by a computer or network component to implement the mechanisms of the various examples.

[0098] The above describes in detail the strength data processing method of the concrete performance provided by the present application. The principles and implementation modes of the present application are described by applying specific examples in this paper. The above example description is only used to help understand the method and its core idea of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the present application.

Claims

1. A method for processing strength data of concrete performance, characterized in that, include: Acquire hydration heat, temperature, and strain data of the concrete structure of the foundation of super high-rise buildings to generate a temperature and strain dataset with spatial distribution characteristics. Based on the temperature strain dataset and the material property parameters of the concrete structure, a three-dimensional concrete entity is constructed using a pre-built digital twin model to simulate the temperature gradient field, thermal stress field, and spatiotemporal evolution of the strength development of the concrete structure. Based on the spatiotemporal evolution law and different curing condition parameters, the strength growth curve of the concrete structure under different curing conditions is predicted using the digital twin model; Based on the strength growth curve, the probability of achieving the strength standard and the risk threshold at different curing stages are calculated. Based on the probability of achieving the strength standard and the risk threshold, the strength development of the concrete structure is simulated and risk warning is given.

2. The method according to claim 1, characterized in that, Based on the aforementioned spatiotemporal evolution patterns and different curing condition parameters, the digital twin model is used to predict the strength growth curves of the concrete structure under different curing conditions, including: Based on the design strength grade of the concrete structure, the climate characteristics of the construction area, and the conventional curing scheme, multiple sets of curing condition parameters are determined. These curing condition parameters include the curing environment temperature range, environmental humidity value, surface covering material type, and cooling medium flow rate. Based on the initial strength value, temperature gradient field reference value, and thermal stress field reference value of each three-dimensional grid unit in the spatiotemporal evolution law, and combined with the maintenance condition parameters, the three-dimensional grid units are adjusted using the digital twin model to obtain the adjusted grid parameters. The adjusted grid parameters include the adjusted temperature change rate, the corrected strength growth coefficient, the adjusted temperature exchange amount, and the adjusted stress release rate. Based on a preset time interval, the intensity increase of each three-dimensional mesh element under the action of the adjusted mesh parameters is calculated, and the intensity increase at each time point is accumulated to generate the intensity change curve of each three-dimensional mesh element over time.

3. The method according to claim 2, characterized in that, Based on the initial intensity value, temperature gradient field reference value, and thermal stress field reference value of each three-dimensional mesh element in the spatiotemporal evolution law, and in conjunction with the maintenance condition parameters, the digital twin model is used to adjust each three-dimensional mesh element to obtain the adjusted mesh parameters. These adjusted mesh parameters include the adjusted temperature change rate, the corrected intensity growth coefficient, the adjusted temperature exchange rate, and the adjusted stress release rate. The temperature range of the maintenance environment is compared with the reference value of the temperature gradient field of each three-dimensional grid unit in the spatiotemporal evolution law to determine the correlation ratio; If the internal stress of the thermal stress field reference value exceeds the preset range, the correlation ratio is amplified by the preset ratio to obtain the final correlation ratio. Based on the final correlation ratio, the temperature change rate of each three-dimensional mesh unit is adjusted through the digital twin model to obtain the adjusted temperature change rate. Based on the deviation between the environmental humidity value and the standard maintenance humidity, and combined with the initial strength value of strength development, the humidity influence ratio is determined. Based on the humidity influence ratio, the strength growth coefficient corresponding to each three-dimensional mesh unit is corrected through the digital twin model to obtain the corrected strength growth coefficient. Based on the surface covering material type and cooling medium flow rate, and combined with the thermal stress field reference value, the preferred direction of temperature exchange in the edge region of the concrete structure is determined. Based on the preferred direction of temperature exchange, the temperature exchange amount and internal stress release rate between the corresponding three-dimensional mesh unit and the external environment are adjusted through the digital twin model to obtain the adjusted temperature exchange amount and the adjusted stress release rate.

4. The method according to claim 1, characterized in that, Based on the strength growth curve, the probability of achieving strength standards and the risk threshold at different curing stages are calculated. Based on these probabilities and thresholds, the strength development of the concrete structure is simulated and risk warnings are provided, including: The curing process of the concrete structure is divided into multiple curing stages. The time nodes for dividing each curing stage are determined based on the slope change characteristics of the strength growth curve. The curing stages include an early curing stage, a mid-term curing stage, and a late curing stage. The cumulative strength value at each time point in the strength change curve of each curing stage is compared with the corresponding design strength standard value to calculate the strength compliance probability of each three-dimensional mesh unit for the curing stage. Based on the material strength dispersion coefficient of concrete and the structural design safety margin, the risk threshold of the curing stage corresponding to each three-dimensional mesh unit is determined. The risk threshold of different three-dimensional mesh units is set differently according to the corresponding structural importance coefficient. Three-dimensional mesh cells with a strength compliance probability lower than the risk threshold are marked as risk areas, and the time point and duration when the cumulative strength value of the risk area is lower than the design strength standard value of the corresponding maintenance stage are recorded. Based on the strength compliance probability of each three-dimensional mesh unit, the risk area, the time point, and the duration, a risk warning level is generated to realize the strength development simulation and risk warning of the concrete structure.

5. The method according to claim 4, characterized in that, Based on the probability of intensity compliance for each 3D mesh cell, the risk area, the time point, and the duration, a risk warning level is generated, including: Based on the strength compliance probability of each three-dimensional mesh unit, the three-dimensional spatial coordinates of the risk area, the time point, and the duration, combined with the three-dimensional concrete entity, the strength development state of the concrete structure at different curing stages is dynamically simulated through the digital twin model. Each simulation cycle is divided according to the time nodes of each curing stage. The probability distribution density of strength compliance and the proportion of risk areas for each three-dimensional mesh element in each simulation cycle are statistically analyzed. At the same time, the difference between the cumulative strength value of all risk areas in each simulation cycle and the corresponding design strength standard value is calculated. Based on the proportion of the risk area, multiple first warning coefficients are set, and based on the difference, multiple second warning coefficients are set. Different first warning coefficients and second warning coefficients correspond to different warning levels. The first warning coefficient and the second warning coefficient are combined to generate a risk warning level.

6. The method according to claim 1, characterized in that, Acquire hydration heat, temperature, and strain data of the concrete structure of the foundation of super high-rise buildings to generate a temperature and strain dataset with spatial distribution characteristics, including: Temperature and strain values ​​collected at each sampling point at different time intervals are obtained. The temperature value reflects the heat of hydration of the concrete structure, and the strain value reflects the deformation of the concrete structure caused by temperature changes. Each sampling point is assigned a preset three-dimensional spatial coordinate, which is determined based on the design dimensions of the concrete structure and the sensor deployment locations on the concrete structure; The temperature and strain values ​​at each sampling point are associated with their corresponding three-dimensional spatial coordinates to obtain temperature and strain data with spatial identifiers. Based on the physical location corresponding to the three-dimensional spatial coordinates of each sampling point and the geometric shape of the concrete structure, the concrete structure is divided into multiple three-dimensional grid units, and the temperature and strain data with spatial identification belonging to the same three-dimensional grid unit are classified and processed to form the temperature and strain dataset with spatial distribution characteristics.

7. The method according to claim 1, characterized in that, Based on the temperature strain dataset and the material property parameters of the concrete structure, a three-dimensional concrete entity is constructed using a pre-built digital twin model to simulate the temperature gradient field, thermal stress field, and spatiotemporal evolution of the concrete structure's strength development, including: Based on the temperature and strain data of each three-dimensional mesh unit in the temperature and strain dataset, and the material property parameters of the concrete structure, a three-dimensional concrete entity with the physical form of the concrete structure is generated using a pre-built digital twin model. The three-dimensional concrete entity is composed of multiple three-dimensional mesh units, and the material property parameters include thermal conductivity, specific heat capacity, elastic modulus, and strength growth factor. Based on the temperature data of each three-dimensional grid cell, combined with the thermal conductivity and specific heat capacity, the temperature transfer and temperature difference between adjacent three-dimensional grid cells are calculated to form the temperature gradient field of the concrete structure. Based on the temperature value and temperature change rate of each three-dimensional grid cell in the temperature gradient field, combined with the elastic modulus and strain data of each three-dimensional grid cell, the internal stress and stress direction of each three-dimensional grid cell due to temperature change are calculated to form the thermal stress field of the concrete structure. By combining the internal stress of each three-dimensional mesh element in the thermal stress field, the strength growth coefficient, and the preset time step, the strength value of each three-dimensional mesh element at different times is calculated. Combined with the changing trend of the temperature gradient field, the spatiotemporal evolution law of the strength development of the concrete structure is generated.

8. A strength data processing system for concrete performance, characterized in that, include: The acquisition module is used to acquire hydration heat, temperature and strain data of the concrete structure of the foundation of super high-rise buildings in order to generate a temperature and strain dataset with spatial distribution characteristics. The simulation module is used to construct a three-dimensional concrete entity based on the temperature strain dataset and the material property parameters of the concrete structure, using a pre-built digital twin model, in order to simulate the temperature gradient field, thermal stress field, and spatiotemporal evolution of the strength development of the concrete structure. The prediction module is used to predict the strength growth curve of the concrete structure under different curing conditions based on the spatiotemporal evolution law and different curing condition parameters, using the digital twin model. The calculation module is used to calculate the probability of achieving the strength standard and the risk threshold at different curing stages based on the strength growth curve, and to perform strength development simulation and risk warning of the concrete structure based on the probability of achieving the strength standard and the risk threshold.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of a strength data processing method for concrete performance as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, enables a method for processing strength data of concrete properties as described in any one of claims 1 to 7.

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