Method, system and equipment for predicting hydration heat and adiabatic temperature of concrete doped with slag powder

Abstract

The invention provides a method, a system and equipment for predicting hydration heat and adiabatic temperature of concrete doped with slag powder, and belongs to the technical field of cement hydration and concrete simulation modeling. The method comprises the following steps: expressing the total heat release of a Portland cement-slag system as the sum of the hydration heat release of Portland cement and the hydration heat release of slag to obtain a Portland cement-slag hydration heat release prediction model; deriving the model, multiplying the model by the use amount of a single cementing material to serve as an internal heat source item of a concrete heat conduction differential equation, and solving the concrete heat conduction differential equation by adopting a finite difference method to obtain the temperature field distribution of the concrete under the adiabatic condition. Wherein the hydration degree prediction model of the Portland cement and the slag is constructed based on a Portland cement hydration dynamic mechanism. According to the method, the concrete hydration heat does not need to be tested, the hydration heat release rule and the adiabatic temperature rise behavior of the cement-slag system can be accurately predicted only by providing related parameters, and support is provided for mass concrete temperature control design.

Description

Technical Field

[0001] The present application relates to the technical field of cement hydration and concrete simulation modeling, and in particular to a method, system and device for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder. Background Art

[0002] During the construction of large-volume concrete, the sheer volume of concrete and the significant heat released by the cement hydration reaction, combined with uneven heat dissipation inside and outside the concrete and internal and external constraints, lead to cracking caused by thermal stresses induced by temperature gradients. This is a major factor affecting the durability and safe use of concrete structures. In marine engineering, in particular, large amounts of slag are often incorporated to enhance resistance to chloride ion corrosion. Slag not only reduces the heat of hydration but also solidifies chloride ions, significantly improving concrete durability. Therefore, accurately predicting the evolution of the heat of hydration and the temperature field distribution of large-volume concrete incorporating slag is crucial for optimizing construction processes and temperature control measures.

[0003] In the existing technology, domestic and foreign scholars have mostly used experimental methods to obtain hydration heat data for cementitious materials and combined them with finite element methods or finite difference methods to predict temperature changes within concrete. For example, one study measured the hydration heat of cementitious materials and recorded the ambient temperature, then used finite element models to predict the temperature changes of concrete over time. Related standards use experimentally obtained heat release at different ages to infer the total heat release, and use experimental or empirical methods to estimate the heat release for cement with different admixtures. Other studies have established temperature field prediction models based on finite element or finite difference methods, taking into account various factors such as water-cement ratio, cement type, and admixtures, to calculate the temperature distribution pattern within concrete and verify it with measured results.

[0004] However, in actual large-volume concrete projects, a wide variety of cementitious materials are used, such as low-heat cement or a large amount of mineral admixtures added to silicate cement. If the hydration heat release process of each type of cement is measured one by one through experiments, it will not only be time-consuming and labor-intensive, but will also lead to a lag in temperature control.

[0005] Therefore, it is necessary to provide an improved technical solution that can accurately predict the hydration heat release and temperature changes of large-volume concrete without relying on experimental data, so as to support the formulation and regulation of its temperature control measures. Summary of the Invention

[0006] The purpose of this application is to provide a method, system and equipment for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder, so as to alleviate or solve the time-consuming and labor-intensive problem of relying on experiments to obtain hydration heat data and the problem of delayed temperature control in the prior art. By replacing experimental data with a theoretical model, the hydration heat and concrete temperature evolution law of pure Portland cement system and Portland cement-slag composite cementitious system are directly and accurately predicted, providing a theoretical basis and technical support for the temperature rise control of large-volume concrete.

[0007] In order to achieve the above objectives, this application provides the following technical solutions: In a first aspect, the present application provides a method for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder, comprising: The total heat release of the Portland cement-slag system is expressed as the sum of the hydration heat release of Portland cement and the hydration heat release of slag, and a prediction model for the hydration heat release of Portland cement-slag is obtained. The total heat release of the Portland cement-slag system calculated by the Portland cement-slag hydration heat release prediction model is multiplied by the amount of cementitious material per cubic meter to obtain the internal heat source term of the concrete heat conduction differential equation, and the concrete heat conduction differential equation is solved using a finite difference method to obtain the temperature field distribution of the concrete under adiabatic conditions; The hydration heat of the Portland cement is calculated based on the hydration degree of the Portland cement, which is predicted by a Portland cement hydration degree prediction model. The Portland cement hydration degree prediction model is constructed based on the PK hydration kinetic model and comprehensively considers the effects of hydration time, water-cement ratio, specific surface area, relative humidity, and curing environment temperature on the hydration rate of Portland cement. The heat released by slag hydration is calculated based on the slag hydration degree; the slag hydration degree is predicted by a slag hydration degree model, which comprehensively considers the effects of slag content, water-binder ratio, specific surface area and curing environment temperature on the slag hydration process.

[0008] In conjunction with the first aspect, in some possible implementations, a slag hydration degree model is constructed based on a hydration kinetic mechanism, including: The hydration kinetics of slag is considered to be controlled by the diffusion reaction process. Based on the diffusion reaction process equation in the hydration kinetics equation of silicate cement, the initial hydration kinetics equation of slag is written. The maximum hydration degree of slag is introduced to correct the initial hydration kinetic equation of the slag to obtain a final hydration kinetic equation of the slag, and the final hydration kinetic equation of the slag is integrated to obtain a first slag hydration degree prediction model.

[0009] In combination with the first aspect, in some possible implementations, the maximum hydration degree of the slag is related to the slag activity index, and the effects of different slag water-binder ratios, slag dosage, specific surface area, and curing environment temperature on the hydration process are comprehensively considered.

[0010] In conjunction with the first aspect, in some possible implementations, the expression for the maximum hydration degree of slag is as follows: , The final slag hydration kinetic equation is expressed as follows: , Where, is the maximum hydration degree of slag; is the activity index of slag; is the water-binder ratio; is the slag content; is the specific surface area of ​​slag; is the reference value of slag specific surface area; is the apparent activation energy of slag; is the universal gas constant; is the reference temperature; To maintain the ambient temperature; is the hydration degree of slag; is the reaction rate constant of the slag diffusion reaction process, which is related to the water-binder ratio and slag content; is the hydration time, that is, the hydration age.

[0011] In conjunction with the first aspect, in some possible implementations, the method further includes: obtaining a slag hydration degree model by surface fitting based on statistical results of experimental data from various existing studies, as follows: Obtain the test results of different researchers on the non-evaporable water content of Portland cement-slag system and the corresponding test conditions; Determine a preliminary expression for the degree of slag hydration based on an expression for the non-evaporable water content of a Portland cement-slag system, wherein the non-evaporable water content of the Portland cement-slag system is expressed as the sum of the non-evaporable water content of the Portland cement and the non-evaporable water content of the slag; Substituting the test results of the non-evaporable water content of the Portland cement-slag system by different researchers into the preliminary expression of the slag hydration degree, the slag hydration degree under different test conditions was calculated; Performing surface fitting on the slag hydration degree under the different test conditions to obtain a surface fitting expression for the slag hydration degree; the surface fitting expression for the slag hydration degree is used to characterize the variation of the slag hydration degree with hydration time under different water-binder ratios; Comprehensively considering the effects of effective water-binder ratio, hydration time, slag content, specific surface area and curing environment temperature on the slag hydration process, the slag hydration degree expression of the surface fitting is modified to obtain a second slag hydration degree prediction model; The effective water-binder ratio adopts the slag activity index to adjust the effective contribution of slag.

[0012] In conjunction with the first aspect, in some possible implementations, the expression of the second slag hydration degree prediction model is as follows: , Where, is the hydration time, i.e., the hydration age; is the hydration degree of slag; is the activity index of slag; is the slag content; is the effective water-binder ratio; is the specific surface area of ​​slag; is the reference value of slag specific surface area; is the apparent activation energy of slag; is the universal gas constant; is the reference temperature; To maintain the ambient temperature.

[0013] In combination with the first aspect, in some possible implementations, the slag activity index comprehensively considers the influence of the two different forms of Al2O3, tetracoordinate and hexacoordinate, in the chemical composition of the slag on the slag activity.

[0014] In conjunction with the first aspect, in some possible implementations, a finite difference method is used to solve the concrete heat conduction differential equation to obtain the temperature field distribution of the concrete under adiabatic conditions, including: Perform 2D meshing of concrete cross sections; Initial conditions and adiabatic boundary conditions are set, and the finite difference method is used to calculate the temperature of each node at each moment in two-dimensional space to obtain the adiabatic temperature prediction results of concrete mixed with slag powder; The types of nodes include: internal nodes, boundary nodes and corner nodes.

[0015] In a second aspect, this embodiment provides a system for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder. The system is configured to perform the steps of the method for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder provided in any of the above embodiments, including: a hydration heat prediction model building unit configured to obtain a Portland cement-slag hydration heat release prediction model by expressing the total heat release of the Portland cement-slag system as the sum of the heat release of hydration of the Portland cement and the heat release of hydration of the slag; an adiabatic temperature prediction unit configured to multiply the total heat release of the Portland cement-slag system calculated by the Portland cement-slag hydration heat release prediction model by the amount of cementitious material per cubic meter to obtain an internal heat source term of the concrete heat conduction differential equation, and solve the concrete heat conduction differential equation using a finite difference method to obtain a temperature field distribution of the concrete under adiabatic conditions; The hydration heat of the Portland cement is calculated based on the hydration degree of the Portland cement, which is predicted by a Portland cement hydration degree prediction model. The Portland cement hydration degree prediction model is constructed based on the PK hydration kinetic model and comprehensively considers the effects of hydration time, water-cement ratio, specific surface area, relative humidity, and curing environment temperature on the hydration rate of Portland cement. The heat released by slag hydration is calculated based on the hydration degree of the slag; the hydration degree of the slag is predicted by a hydration degree model of the slag, and the hydration degree model of the slag is constructed based on the hydration kinetic mechanism.

[0016] In a third aspect, this embodiment provides a computer device comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder provided in any of the above embodiments.

[0017] Beneficial effects: The technical solution provided in this application is based on the hydration kinetics mechanism to predict the hydration degree of silicate cement (referred to as cement) and slag respectively, and the hydration heat release of cement and slag is modeled separately and then coupled to obtain the total heat release of the silicate cement-slag system, and then the finite difference method is used to solve the temperature field distribution. This approach multiplies the total heat release of the Portland cement-slag system, calculated using a Portland cement-slag hydration exotherm prediction model, by the amount of cementitious material per cubic meter. This internal heat source term is substituted into the concrete heat conduction differential equation to obtain the temperature field distribution of concrete under adiabatic conditions. This theoretical prediction of the entire process, from hydration reaction to temperature field evolution, provides a scientific basis for the development of temperature control measures for large-volume concrete. Furthermore, this prediction process eliminates the need for hydration heat tests to determine the hydration heat release of cement and slag, reducing R&D costs and time. The method distinguishes the hydration behaviors of cement and slag, and considers the influence of factors such as slag content and water-binder ratio in the modeling, improving the accuracy and applicability of composite system hydration heat prediction. Furthermore, since this method does not rely on concrete test data, it only requires concrete-related material parameters and external parameters (such as mix proportion and curing environment temperature) to predict hydration heat and adiabatic temperature. Therefore, this method can be used to predict temperature rise during the mix proportion design phase, enabling preemptive temperature control and providing technical support for optimizing construction plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the structure of a computer device.

[0019] Figure 2 Schematic diagram of the hydration process of silicate cement, where (a) is the crystallization nucleation and crystal growth reaction process, (b) is the diffusion reaction process, and (c) is the process of forming a hydration shell or hydration film.

[0020] Figure 3 is the time-varying law of non-evaporable water content under different slag content, where (a) is the slag content =30% of the time-varying curve, (b) is the slag content =40% of the time-varying curve, (c) is the slag content =50% of the time-varying curve, (d) is the slag content =60% time-varying curve, (e) is the slag content =70% of the time-varying curve, (f) is the slag content =80% of the time-varying curve.

[0021] Figure 4 is the time-varying law of non-evaporable water content under different water-binder ratios, where (a) is the water-binder ratio = 0.3, (b) is the time-varying curve of water-binder ratio = 0.4, (c) is the time-varying curve of water-binder ratio = 0.5 time-varying curve.

[0022] Figure 5 Schematic diagram comparing the simulated temperature and monitored temperature at the center point and one quarter of the distance from the surface of the massive concrete specimen.

[0023] Figure 6 Schematic diagram of the fitting surface of slag hydration degree, where (a) is the curing temperature =20℃ fitting surface, (b) is the water-binder ratio = 0.3, (c) is the water-binder ratio = 0.4, (d) is the water-binder ratio = 0.5.

[0024] Figure 7 Schematic diagram comparing the test results and predicted results of slag hydration degree.

[0025] Figure 8Schematic diagram comparing the predicted results of cumulative heat release with different slag dosages and the experimental results, where (a) is a comparison with the experimental results of scholars Gruyaert et al., and (b) is a comparison with the experimental results of scholars Park et al.

[0026] Figure 9 Schematic diagram of concrete cross-section meshing.

[0027] Figure 10 These are the temperature field distribution cloud maps of concrete with a cross-sectional size of 1.5m×1.5m when the hydration time is 1 day, 3 days, and 7 days. Among them, (a) is the temperature cloud map when the hydration time is 1 day, (b) is the temperature cloud map when the hydration time is 3 days, and (c) is the temperature cloud map when the hydration time is 7 days. DETAILED DESCRIPTION

[0028] The embodiments of the present application are described below with reference to the accompanying drawings.

[0029] This embodiment provides a method for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder, wherein the concrete mixed with slag powder belongs to a Portland cement-slag composite cementitious system. The method can be executed by a computer device and includes: Step S1: obtaining a prediction model for the hydration heat release of Portland cement-slag by expressing the total heat release of the Portland cement-slag system as the sum of the hydration heat release of Portland cement and the hydration heat release of slag.

[0030] Step S2: Multiply the total heat release of the Portland cement-slag system calculated by the Portland cement-slag hydration heat release prediction model by the amount of cementitious material per cubic meter to obtain the internal heat source term of the concrete heat conduction differential equation. The concrete heat conduction differential equation is solved using the finite difference method to obtain the temperature field distribution of the concrete under adiabatic conditions.

[0031] Among them, the hydration heat release of Portland cement is calculated based on the hydration degree of Portland cement, and the hydration degree of Portland cement is predicted by the hydration degree prediction model of Portland cement; the hydration degree prediction model of Portland cement is constructed based on the PK hydration kinetic model, and comprehensively considers the effects of hydration time, water-cement ratio, specific surface area, relative humidity and curing environment temperature on the hydration rate of Portland cement.

[0032] The technical solution of this embodiment is based on the kinetic mechanism of the Portland cement hydration reaction. It predicts the hydration degree of Portland cement and slag separately, and then calculates the hydration heat release of each of Portland cement and slag. It then combines this with the finite difference method to achieve adiabatic temperature simulation. This solution breaks through the traditional two-stage temperature prediction method of first measuring the hydration heat by experimental means and then inputting the experimental data into the finite element method for temperature field simulation. By embedding the prediction of the hydration degree of Portland cement and the prediction of the hydration degree of slag into the hydration heat prediction process, the Portland cement-slag hydration heat release prediction model can be used to calculate the cumulative total heat release without experimental data. The temperature field can then be directly solved based on the concrete heat conduction differential equation, achieving highly accurate temperature prediction.

[0033] The following first introduces the steps for predicting the hydration heat release of silicate cement.

[0034] Portland cement is a multi-mineral aggregate, mainly composed of four clinker minerals: tricalcium silicate (C3S), dicalcium silicate (C2S), tricalcium aluminate (C3A), and tetracalcium aluminoferrite (C4AF), as well as a small amount of free calcium oxide (f-CaO), magnesium oxide (f-MgO), SO3 and other substances. The hydration heat of Portland cement is directly related to the above composition, so the hydration heat of Portland cement can be expressed as: (1) Where, yes The hydration heat of Portland cement at this moment, is the serial number of each phase (i.e. mineral composition), When cement is fully hydrated The maximum heat release of a phase (material composition); It is The mass fraction of the phase; It is the first Species Hydration level at all times.

[0035] According to existing research, the maximum heat release values ​​of each phase in formula (1) are shown in Table 1. Table 1 is as follows: Table 1 Maximum heat release of each phase

[0036] In formula (1), for the four main clinker mineral phases C3S, C2S, C3A and C4AF, their mineral composition mass fractions are It can be calculated according to the modified Bogue equation in ASTM C 150. Therefore, the mass fraction of each mineral component is expressed as: when When the quality score It is calculated as follows: (2) (3) (4) (5) when , quality score It is calculated as follows: (6) (7) (8) (9) Where, 、 、 、 、 are the mass fractions of C3S, C2S, C3A, C4AF, and C2F, 、 、 、 and are the mass fractions of CaO, SiO2, Al2O3, Fe2O3 and SO3 in cement clinker respectively.

[0037] If limestone or inorganic materials are not added to the cement, the mass fraction of each mineral component can be calculated using the above formulas (2) to (9): No adjustment is required.

[0038] Furthermore, when limestone or inorganic materials are added to cement, or both are used together, the mineral composition needs to be modified. In this case, the contents of C3S, C2S, C3A and C4AF can be adjusted according to the following equations: (10) Where, It is the content of C3S, C2S, C3A and C4AF added with limestone or inorganic processing additions. It is the content of C3S, C2S, C3A and C4AF in basic cement (i.e. pure clinker cement without any limestone or inorganic processed materials). is the mass percentage of limestone, is the mass percentage of inorganic processed materials.

[0039] It should be pointed out here that due to the low content of SO3, f-CaO (free calcium oxide) and f-MgO (free magnesium oxide) in silicate cement, they can be considered to be able to fully react during the hydration process, so the hydration degree is considered to be 1. The hydration degree of other mineral phases (such as C3S, C2S, C3A, C4AF) needs to be further calculated through the hydration dynamic model.

[0040] In order to calculate the hydration degree of each mineral, firstly, the cement clinker mineral hydration kinetics model based on the classic PK model is introduced.

[0041] The degree of hydration of the four clinker minerals (C3S, C2S, C3A, C4AF) of Portland cement depends on their chemical reaction kinetics. Figure 2 As shown in the figure, different colors and symbols are used to represent the components. The hydration process of Portland cement can be described as three stages: (a) Nucleation and Growth: This stage represents the initial stage of the hydration reaction, when water molecules enter the cement surface and react chemically with the clinker minerals to produce initial hydration products (i.e., CSH gel) and calcium hydroxide ( ), the hydration products form tiny crystal nuclei on the cement surface and gradually grow outward, covering part of the cement surface; (b) Diffusion reaction process: This stage represents the middle stage of hydration. As the hydration products (CSH gel) deposit on the cement surface, a dense hydration layer is formed, which hinders the further diffusion of water molecules inward. Water molecules need to bypass or diffuse through the pores to the unreacted area, while the mineral clinker diffuses and migrates from the inside to the outside through the pores. Therefore, the hydration rate is controlled by diffusion; (c) Formation of hydration shell or hydration film process: This stage represents the late stage of hydration. The hydration product (CSH gel) has completely wrapped the cement, forming a continuous hydration shell. It is difficult for water molecules to enter the reaction zone, and the hydration reaction tends to be slow, eventually entering a stable period. Therefore, the hydration kinetics of the four clinker minerals can be represented by the PK model. The expressions of the hydration rates in the three stages are as follows: Crystallization nucleation and crystal growth reaction process (Nucleation and Growth): (11) Diffusion reaction process (Diffusion): (12) Formation of hydration shell or hydration film process: (13) Where, is the degree of hydration, represents the hydration rate, It represents the hydration rate of the crystal nucleation and crystal growth reaction process, represents the hydration rate of the diffusion reaction process, It represents the hydration rate of the process of forming a hydration shell or hydration film, 、 、 are the reaction rate constants of the three stages respectively; 、 are the reaction orders of the crystallization nucleation and crystal growth reaction process, and the formation of hydration shell or hydration film process. 、 、 、 、 Collectively referred to as hydration reaction kinetic parameters.

[0042] Formulas (11), (12), and (13) are also called the hydration kinetic equations for the three stages of crystallization nucleation and crystal growth reaction process, diffusion reaction process, and hydration shell or hydration film formation process. By integrating the above three hydration kinetic equations respectively, the relationship between hydration degree and hydration time is obtained, which is expressed as follows: (14) (15) (16) Where, 、 、 They are the hydration functions of the crystallization nucleation and crystal growth reaction process, the diffusion reaction process, and the formation of a hydration shell or hydration film process, which are used to describe the reaction progress of each stage of the hydration process.

[0043] According to the quantitative analysis of silicate hydration samples with different clinker mineral contents by the Rietveld method by scholars Lothenbach et al., the hydration reaction kinetic parameters of the four clinker minerals in formulas (11) to (13) and (14) to (16) are given, as shown in Table 2. Table 2 is as follows: Table 2. Kinetic parameters of hydration reactions required to describe the temporal changes in the hydration degree of a single mineral.

[0044] Based on the above description, it can be seen that in the hydration process of a single mineral in cement clinker shown in formulas (11) to (13), the hydration process is controlled by the minimum hydration rate condition. However, for ground cement, its hydration process is not only related to the water-cement ratio, but also to factors such as the specific surface area of ​​cement, relative humidity and temperature during hydration. Therefore, it is necessary to improve formulas (11) to (13) and comprehensively consider the effects of hydration time, water-cement ratio, specific surface area, relative humidity and temperature on the hydration rate of silicate cement to form an improved cement hydration kinetic model that describes the hydration rate of a single mineral. The expression is as follows: (17) Where, is the hydration time, For the The degree of hydration of the phase, 、 、 、 They are the influence coefficients of water-cement ratio, specific surface area, relative humidity and curing environment temperature on cement clinker minerals.

[0045] Among them, each influence coefficient 、 、 、 is calculated as follows: The influence coefficient of water-cement ratio on cement clinker minerals The expression is as follows: (18) Where, is the water-cement ratio; For the The hydration degree of a phase; H is an empirical constant that needs to be determined through experiments based on the hydration degree of a single mineral at different water-cement ratios.

[0046] Specific surface area influence coefficient The expression is as follows: (19) Where, is the specific surface area of ​​actual cement; is the surface area of ​​the benchmark cement. In this embodiment, =3850cm 2 / g.

[0047] Relative humidity influence coefficient The expression is as follows: (20) Where, is the relative humidity of the pores in the hardened paste.

[0048] The influence coefficient of curing environment temperature on the hydration of single mineral can be expressed as: (twenty one) Where, is the apparent activation energy; is the gas constant ( ); is the reference temperature ( =293K); It is the maintenance environment temperature in the actual environment, referred to as the maintenance environment temperature.

[0049] Substituting formulas (11) to (13) and formulas (18) to (21) into formula (17), we can obtain the improved cement hydration kinetics model that comprehensively considers the effects of water-cement ratio, temperature, relative humidity and cement specific surface area on the hydration rate.

[0050] On this basis, the hydration degree of Portland cement can be expressed by the hydration rate of each phase, as shown below: (twenty two) Where, 、 、 、 are the hydration degrees of C3S, C2S, C3A, and C4AF, respectively. Equation (22) is based on the hydration kinetics of Portland cement and is also known as the hydration degree prediction model for Portland cement.

[0051] The following are the empirical constants calibration process.

[0052] To avoid experimental errors, we used The chemical composition and specific surface area of ​​Portland cement are shown in Table 3. Table 3 is as follows: Table 3 Chemical composition and specific surface area of ​​cement

[0053] For silicate cement, the non-evaporable water content is often used to characterize the degree of hydration of silicate cement. The test process is briefly as follows: the sample is placed in a drying oven and dried at a temperature of 105°C for 24 hours. After being taken out and cooled in a desiccator, it is weighed and the mass is recorded as m1. Then, it is placed in a Martens furnace and heated to 1000°C for 4 hours. After cooling, it is taken out and weighed and the mass is recorded as m2. Considering that the cementitious material still has loss on ignition under high temperature conditions, the change in loss on ignition (LOI) of the cementitious material must be considered when calculating the non-evaporable water content. The cementitious material is weighed after drying and the mass is recorded as m a , cool and weigh after burning, the mass is recorded as m bThree samples are taken for each weighing and the arithmetic mean of the results is taken. Calculate the LOI and non-evaporable water content based on the test data , and then calculate the cement hydration degree (Right now ), the relevant calculation formula can refer to the existing technology, and this embodiment will not be repeated here. The calculation results are statistically analyzed to obtain the test results of the hydration degree of Portland cement at different ages and different water-cement ratios, as shown in Table 4. Table 4 is as follows: Table 4 Hydration degree of Portland cement at different water-cement ratios (%)

[0054] Substituting the test results in Table 4 into formula (18), the empirical constants of each phase under different water-cement ratios are obtained. The statistical results are shown in Table 5. Table 5 is as follows: Table 5 Empirical constant H at different water-cement ratios

[0055] Substituting Table 4 and Table 5 into formula (22), the hydration degree of Portland cement with different water-cement ratios can be predicted. Substituting the predicted results into formula (1), we can get any The hydration heat of Portland cement is released at all times.

[0056] In order to verify the reliability of the prediction results of the hydration degree of Portland cement, the experimental results of scholars Wong et al. and Liao et al. were used for comparative verification. The mineral composition and specific surface area of ​​Portland cement clinker used by the two scholars are shown in Table 6. Table 6 is as follows: Table 6 Chemical composition and specific surface area of ​​cement and slag

[0057] Substituting the mineral composition, water-cement ratio, hydration age, curing environment temperature, and cement specific surface area of ​​clinker into the hydration degree prediction model of silicate cement, that is, formula (22), the prediction results of silicate cement hydration degree can be obtained. The prediction results are compared and analyzed with the experimental results given by scholars. The analysis results show that the prediction results are basically consistent with the experimental results. If the experimental results are used as the benchmark, the maximum error between the prediction and experimental results is 14.78%. This error range is relatively small for silicate cement with multiple mineral compositions, further proving that the prediction results of silicate cement hydration degree are reliable.

[0058] Furthermore, the predicted result of the hydration degree of Portland cement is substituted into formula (1) to obtain the hydration heat of Portland cement. The prediction results were verified by the following steps: the test used slurries with water-cement ratios of 0.35 and 0.50, and the TAMAIR eight-channel isothermal calorimeter from TA Instruments of the United States was used for testing. The test temperature was constant at 20 ± 1 °C. At the same time, the corresponding parameters were substituted into formula (1) to predict the cumulative hydration heat of cement. , and get the predicted results. Comparing the test results with the predicted results, we can see that the cumulative heat release of silicate cement The prediction results are basically consistent with the test results, both showing a trend of rapid growth in the early stage and slow growth in the later stage. The maximum error is 6.31%, indicating that the hydration heat of silicate cement in formula (1) is The prediction accuracy is high and reasonable.

[0059] After describing in detail the steps for predicting the degree of hydration and hydration heat release of Portland cement, the following introduces the steps for predicting the degree of hydration and hydration heat release of Portland cement-slag system.

[0060] It should be noted that slag is a by-product produced by extreme cooling through water quenching during the blast furnace ironmaking process. The glass phase content is usually above 90%, and exists in an irregular network form. It is often used as a mixed material for cement or a mineral admixture for concrete, and is widely used in large-volume concrete for marine engineering.

[0061] Considering that the hydration process of the Portland cement-slag system is relatively complex, its hydration exotherm can be simply expressed as the sum of the hydration exotherm of Portland cement and the hydration exotherm of slag. Therefore, a prediction model for the hydration exotherm of Portland cement-slag is established, and the expression is as follows: (twenty three) (twenty four) (25) Where, for The total heat release of the Portland cement-slag system at this moment, and They are The cumulative heat released by the hydration of Portland cement (cement) and slag at each moment; is the slag content; and are the theoretical heat release of complete hydration of cement and slag, 、 are the hydration degrees of cement and slag at time t respectively.

[0062] The above-mentioned silicate cement-slag hydration exotherm prediction model decomposes the complex silicate cement-slag system into two subsystems, namely cement and slag subsystems. After modeling them separately, they are weighted summed up, making the formula clear in structure and physical meaning, and intuitively reflecting the slag content. The regulation of total heat release enables a theoretical description of the hydration behavior of the composite cementitious system, solving the problem of poor applicability of existing models to cement-slag composite systems.

[0063] The theoretical heat release for complete hydration of slag per unit mass is It can be taken as 630 J / g; while the theoretical heat release of cement complete hydration is According to the maximum heat release of each phase The mass fraction of each phase The maximum heat release of each phase is calculated We can refer to existing research results, as shown in Table 1.

[0064] Cumulative heat release of hydration of Portland cement at a given moment The hydration heat of silicate cement is referred to as It can be calculated according to formula (1) in the above embodiment, that is, the hydration degree of silicate cement is predicted by the hydration degree prediction model of silicate cement; and the hydration heat of silicate cement is calculated according to the hydration degree of silicate cement.

[0065] The following describes the heat release of slag hydration Theoretical calculation process.

[0066] In this embodiment, the heat released by slag hydration is calculated based on the slag hydration degree; the slag hydration degree is predicted by a slag hydration degree model, which comprehensively considers the effects of slag content, water-binder ratio, specific surface area and curing environment temperature on the slag hydration process.

[0067] Specifically, the hydration degree of slag can be predicted in two ways. One is the prediction of the hydration degree of slag based on hydration dynamics, which is called the first slag hydration degree prediction model; the other is the prediction based on the statistical results of experimental data from different researchers, which is obtained after surface fitting and correction, and is called the second slag hydration degree prediction model.

[0068] The following introduces two prediction processes of slag hydration degree.

[0069] Firstly, the process of slag hydration degree prediction based on hydration kinetics is explained.

[0070] In one embodiment, a slag hydration degree model is constructed based on the kinetic mechanism of Portland cement hydration reaction, including: In step S11a, the hydration kinetics of the slag is considered to be controlled by a diffusion reaction process, and the initial hydration kinetics equation of the slag is written according to the equation of the diffusion reaction process in the hydration kinetics equation of silicate cement.

[0071] Step S11b: introducing the maximum hydration degree of slag to correct the initial hydration kinetic equation of slag to obtain the final hydration kinetic equation of slag, and integrating the final hydration kinetic equation of slag to obtain the first hydration degree prediction model of slag.

[0072] It should be noted that the hydration reaction kinetics of slag is basically the same as that of silicate cement, and is also divided into three stages: crystallization nucleation and crystal growth reaction process, diffusion reaction process, and hydration shell formation. Considering that the glass network structure of slag itself is less active in the early stage than the metastable silicate clinker mineral components, and the crystallization nucleation and crystal growth process of slag is very slow and almost difficult to test, the hydration kinetics of slag is considered to be controlled by the diffusion reaction process. According to formula (12), that is, the equation of the diffusion reaction process, the initial hydration kinetics of slag can be expressed as: (26) Where, express The hydration degree of slag at the time, It is the reaction rate constant of the slag diffusion reaction process, which is related to the water-binder ratio and slag content.

[0073] Since the slag phase composition contains a certain amount of inert crystal phase, its hydration reaction degree has an upper threshold, so the maximum hydration degree of slag (also known as the final hydration degree) is introduced. The slag hydration kinetics equation, formula (26), is modified to obtain the final slag hydration kinetics equation, which is expressed as follows: (27) Where, It is the maximum hydration degree when the slag is fully hydrated (i.e. the maximum hydration degree of the slag).

[0074] Preferably, the maximum hydration degree of slag It is related to the activity index of slag, and comprehensively considers the effects of different water-binder ratios of slag, slag dosage, specific surface area, and curing environment temperature on the hydration process.

[0075] Maximum hydration degree of slag Related to the activity index of slag, its preliminary expression is as follows: (28) Where, is the slag content; Indicates the activity index of slag; Indicates the water-to-cement ratio.

[0076] Furthermore, since the hydration of slag is not only related to the water-cement ratio, but also to factors such as specific surface area and curing environment temperature, The initial expression of The final expression is as follows: (29) Where, is the water-binder ratio, is the actual specific surface area of ​​slag; is the benchmark specific surface area; represents activation energy; is the gas constant; is the standard curing temperature, also known as the reference temperature. is the maintenance environment temperature. The final expression comprehensively considers the effects of different water-binder ratios of slag, slag content, specific surface area, and curing environment temperature on the hydration process.

[0077] Will The final expression of (29) is substituted into (27) and integrated to obtain the first slag hydration degree prediction model.

[0078] It should also be noted that in formula (27), the reaction rate constant of the slag diffusion reaction process is It is usually set according to the temperature. Considering that the water-binder ratio and slag content vary greatly in different engineering scenarios (for example, high content and low water-binder ratio are commonly used in marine engineering), if a fixed , may not accurately describe its hydration characteristics. Therefore, in this embodiment, as a further improvement, the test data of slag hydration degree are combined with the test results of different scholars to fit the test data of slag hydration degree with the hydration kinetic model (i.e., formula (27)), and the slag reaction rate constants at different slag dosages and curing ambient temperatures with water-binder ratios of 0.3, 0.4, and 0.5 are given. , as shown in Table 7, which is as follows: Table 7 Slag reaction rate constants under different conditions

[0079]

[0080] The above reaction rate constant for slag In the determination step, the slag reaction rate constant is no longer regarded as a fixed value determined by temperature, but as a function of water-binder ratio, slag content and temperature. By fitting the experimental data with the model, the prediction of slag hydration degree can more realistically reflect the hydration behavior under actual working conditions, reduce the error caused by parameter simplification, and improve the prediction accuracy.

[0081] In another embodiment, based on the statistical results of experimental data from various existing studies, a slag hydration degree model is obtained by surface fitting, including: Step S12a, obtaining the test results of different researchers on the non-evaporable water content of the Portland cement-slag system and the corresponding test conditions.

[0082] Step S12b: Determine a preliminary expression for the degree of slag hydration based on an expression for the non-evaporable water content of the Portland cement-slag system; wherein the non-evaporable water content of the Portland cement-slag system is expressed as the sum of the non-evaporable water content of the Portland cement and the non-evaporable water content of the slag.

[0083] Step S12c: Substitute the test results of different researchers on the non-evaporable water content of the Portland cement-slag system into the preliminary expression of the slag hydration degree to calculate the slag hydration degree under different test conditions.

[0084] Step S12d, performing surface fitting on the slag hydration degree under different test conditions to obtain a surface fitting expression for the slag hydration degree; the surface fitting expression for the slag hydration degree is used to characterize the variation of the slag hydration degree with hydration time under different water-binder ratios.

[0085] Step S12e, comprehensively considering the effects of effective water-binder ratio, hydration age, slag content, specific surface area and curing environment temperature on the slag hydration process, correcting the surface fitting expression of slag hydration degree to obtain a second slag hydration degree prediction model.

[0086] Among them, the effective water-binder ratio uses the slag activity index to adjust the effective contribution of slag.

[0087] Specifically, for the hydration degree model of slag, prediction can be made by testing the change of non-evaporable water content. Considering that the non-evaporable water content of the Portland cement-slag system is related to factors such as water-binder ratio, hydration age, slag content, specific surface area and curing environment temperature, in step S12a, the test data of the non-evaporable water content of the Portland cement-slag system from different researchers are obtained, and these test results are used to verify the correlation between the hydration degree of slag and the above factors. Specifically, according to the time-varying law of the non-evaporable water content statistically calculated at different slag content and water-binder ratio (such as Figure 3 、 Figure 4The corresponding test conditions are given, including slag content, water-binder ratio, specific surface area and temperature, as shown in Table 8. Table 8 is as follows: Table 8 Test conditions for non-evaporable water content

[0088] The purpose of step S12b is to obtain a preliminary expression of the hydration degree of slag, which is related to the hydration degree of slag, the non-evaporated water content of slag, and the hydration degree of Portland cement. Specifically: Since the hydration process of cement-slag cementitious system is relatively complicated, in this example, it is assumed that the hydration of cement and slag is independent, and the non-evaporable water content of the Portland cement-slag system is The total non-evaporable water content can be expressed as the sum of the non-evaporable water content of cement and the non-evaporable water content of slag, as follows: (30) Where, It is the non-evaporable water content when cement and slag are fully hydrated. It is related to the composition and structure of the slag and is generally 0.25-0.30. In this embodiment, the result of scholar Wang et al. is adopted and 0.30 is taken.

[0089] By transforming formula (30), the hydration degree of slag can be expressed by the non-evaporated water content as follows: (31) According to formula (31), the hydration degree of slag is related to the non-evaporated water content and the hydration degree of cement. The hydration degree of cement and slag is not only related to their composition structure, but also to their chemical composition. The glass phase content of slag is above 90%. Under this premise, the activity of slag is measured by the activity index. Reflection, as shown in formula (32): (32) In formula (32), the chemical composition of slag takes into account the existence of two forms of Al2O3: tetracoordinate and hexacoordinate, and different forms have different effects on the activity of slag.

[0090] The prediction of slag hydration degree needs to be calculated based on the basic parameters of the raw materials. The slag composition, burning vector and activity index calculated by formula (32) selected by different researchers (collectively referred to as slag parameters) are shown in Table 9. Table 9 is as follows: Table 9 Slag parameters

[0091] In step S12c, the non-evaporated water content results of slag used by different researchers are substituted into the preliminary expression of slag hydration degree, i.e., formula (31), to obtain the slag hydration degree under different test conditions.

[0092] Next, in step S12d, the calculation results, i.e., the slag hydration degree under different test conditions, are subjected to surface fitting, such as Figure 6 Specifically, the hydration time , slag dosage As the independent variable, the slag hydration degree As the dependent variable, the water-binder ratio and curing temperature are used as the control variables for surface fitting: First, the calculation results are grouped according to different combinations of water-binder ratio and temperature. Then, for each group of data, a three-dimensional scatter plot is made with hydration time as the horizontal axis, slag content as the vertical axis, and hydration degree as the vertical axis. Polynomial regression or empirical function fitting method is used to generate a smooth surface. Different surfaces represent the trend changes under different test parameter conditions, that is, the change of slag hydration degree with hydration time under different water-binder ratios; all the above-mentioned fitted slag hydration degrees are statistically fitted to obtain the empirical expression of slag hydration degree, that is, the slag hydration degree expression of surface fitting, which is as follows: (33) Where, Indicates the hydration time (hydration age), Indicates the water-to-cement ratio.

[0093] Formula (33) only reflects the effects of slag content, water-cement ratio, and hydration age on the hydration degree of slag. Studies have shown that the hydration reaction of slag is also related to factors such as its fineness (specific surface area) and the curing environment temperature. In addition, in the Portland cement-slag composite system, the dilution effect of slag also causes changes in the effective water-cement ratio of cement. Taking these factors into consideration, in order to further improve the accuracy of the slag hydration degree prediction, Formula (33) is further modified in step S12e to obtain a second slag hydration degree prediction model, which is expressed as follows: (34) Where, For time; is the hydration degree of slag; is the activity index of slag; is the slag content; is the effective water-binder ratio; is the specific surface area of ​​slag; The reference value of slag specific surface area is 4500 cm 2 / g; is the apparent activation energy of the slag (50 kJ / mol- 60 kJ / mol); is the universal gas constant; is the reference temperature; To maintain the ambient temperature.

[0094] The effective water-binder ratio uses the slag activity index to adjust the effective contribution of slag, and the expression is as follows: (35) Where, Indicates the amount of water used for mixing. Indicates the amount of cementitious material used.

[0095] Among them, the slag activity index takes into account the influence of the two different forms of Al2O3 in the chemical composition of slag, namely tetracoordinate and hexacoordinate, on the activity of slag. Its expression can be found in formula (32).

[0096] In order to verify the rationality of the slag hydration degree calculated by formulas (34) and (35), the test results of slag hydration degree published by other researchers in the literature (different from the literature of the aforementioned surface fitting process) are cited, and the corresponding test conditions and parameters are substituted into formulas (34) and (35) to obtain the predicted results of slag hydration degree. The fitting curve of the predicted results is compared with the test results. The results are as follows: Figure 7 As shown in the figure, it can be seen that the test data and the fitting results have the same changing trend and are quite consistent. Therefore, the second slag hydration degree prediction model represented by formula (34) and (35) has a high accuracy.

[0097] After establishing the first slag hydration degree prediction model and the second slag hydration degree prediction model and verifying the calculated slag hydration degree, the slag hydration degree can be substituted into formula (25) to calculate the slag hydration heat release , that is, the cumulative calorific value of the slag, and verify its rationality.

[0098] Regarding the verification of the cumulative calorific value of slag, it is difficult to accurately separate the heat of slag from the total heat in the silicate cement-slag cement system. Therefore, this embodiment verifies the total heat release of the silicate cement-slag system. According to the cumulative heat release test results of the silicate cement-slag system with a water-cement ratio of 0.5, a curing environment temperature of 20°C, and slag content of 0, 30%, and 50% given by scholars Gruyaert et al. and Park et al. in the open literature, the basic parameters in the literature are substituted into formulas (34) and (35) to calculate the hydration degree of the slag. The hydration degree of the slag is then substituted into formula (25) to predict the cumulative calorific value of the slag. , the prediction results were compared with the experimental results in the open literature, and the results were as follows Figure 8 As shown. Figure 8It can be seen that the prediction results are basically consistent with the test results, with a maximum error of 9.47%, indicating that it is reliable and reasonable to predict the hydration degree of slag based on (34) and (35), and then predict the cumulative calorific value of slag.

[0099] In predicting the cumulative calorific value of slag Based on the above formula (1), the heat released by hydration of silicate cement is predicted The total heat release of the Portland cement-slag system can be obtained by weighted summing the two through formula (23): prediction results.

[0100] Obtain the total heat release of the Portland cement-slag system After the prediction model is obtained, step S2 uses the Portland cement-slag hydration heat release prediction model to calculate the concrete temperature field, which specifically includes the following steps: Firstly, based on the solid conduction theory and the law of conservation of energy, the heat conduction differential equation for calculating the concrete temperature field is derived.

[0101] It should be noted that the concrete temperature field refers to the temperature distribution law inside the concrete, that is, for any Any point inside the concrete Temperature at the location .

[0102] According to solid conduction theory, concrete is a poor conductor of heat, and its temperature fluctuations are related to its composition, pore structure, and external environment. In practical projects, in addition to measuring the heat from the concrete center to the concrete surface, more often, analysis is performed on the temperature distribution patterns from the concrete center and from the center to the concrete surface.

[0103] For the calculation of concrete temperature field after pouring, the differential equation of concrete heat conduction can be derived based on heat flow analysis. , in unit time, the heat released by concrete per unit time and per unit volume is , then the microelement The heat released per unit time is According to the law of conservation of energy, the heat caused by the change in concrete temperature is equal to the sum of the heat retained by the concrete through external heat transfer and internal heat release, so: (36) Where, is the temperature of a point inside the concrete; is the hydration time; is the thermal conductivity of concrete; It is the heat released by the cementitious material in unit volume of concrete per unit time; is the specific heat capacity of concrete; is the density of concrete.

[0104] Taking into account the effect of hydration heat, assuming that the concrete is in adiabatic conditions, all hydration heat is used for temperature rise, and the temperature change rate is determined only by the heat release per unit volume, without considering the heat conduction term. Therefore, the temperature rise of concrete can be preliminarily expressed as formula (37): (37) Where, is the adiabatic temperature rise of concrete, is the temperature rise rate of concrete under adiabatic conditions. Perform integral transformation on formula (37) and add the total heat release of the silicate cement-slag system calculated by the silicate cement-slag hydration heat release prediction model to the amount of cementitious material per cubic meter. Multiplying together, we get The cumulative heat released by the cementitious material per unit volume of concrete at the time , as the internal heat source term in the differential equation of concrete heat conduction, the calculation formula for the adiabatic temperature rise is as follows: (38) Where, Indicates the amount of cementitious material used per cubic meter; yes The total heat release of the silicate cement-slag system at this moment can be theoretically predicted by formulas (23) to (25).

[0105] The finite difference method is used to solve the concrete heat conduction differential equation to obtain the temperature field distribution of the concrete under adiabatic conditions, which includes the following sub-steps: First, set the initial conditions and adiabatic boundary conditions. In this embodiment, it is assumed that the initial temperature distribution of the concrete is relatively uniform, so When , the initial instantaneous temperature inside the concrete (i.e. initial condition) is: (39) Where, Represents the initial temperature inside the concrete, which is a constant.

[0106] Assuming the concrete surface is adiabatic, the heat flux density at the boundary is zero, and the boundary condition can be expressed as: (40) Where n is the outer normal direction of the concrete surface.

[0107] Secondly, the concrete cross section is divided into two dimensions. This embodiment focuses on the temperature field analysis of concrete in two dimensions (i.e., a certain cross section of concrete). Based on the finite difference method, the temperature of each node at each moment is calculated to solve the concrete temperature field. The details are as follows: In two-dimensional space, the vertical direction can be ignored ( direction), so formula (36) can be simplified to the following two-dimensional heat conduction differential equation: (41) Then, the concrete section is meshed to obtain a discrete mesh. Specifically, Figure 9 As shown, half of the concrete section is Axis and Axis direction with spacing and Divide equally and take the heat transfer time interval as , get the discrete grid, the coordinates of each node on the grid The temperature at express.

[0108] Based on the meshing results, the finite difference method was then used to calculate the temperature of each node in two-dimensional space at each moment. This resulted in a prediction of the adiabatic temperature of the concrete mixed with slag powder. This involved solving for the temperature values ​​of the concrete's internal nodes, boundary nodes, and corner nodes. Different iterative formulas were used for each node type. The specific iterative formulas can be derived from existing techniques and are omitted here for brevity.

[0109] As an example, in the method provided in this embodiment, the prediction process of the heat release of the composite cementitious material during hydration and the temperature field inside the concrete can be performed according to the following process: 1. Calculate the hydration heat of Portland cement. The hydration heat of Portland cement is obtained by formula (1): ; 2. The mass fraction of each clinker mineral phase is obtained by formula (2) to (9); 3. The maximum heat release of each mineral phase is obtained from Table 1; 4. Determine the mass fraction of cement in the cementitious system according to the actual mix ratio; 5. Calculate the hydration degree of slag by integrating formula (27) or formulas (34) and (35): ; 6. Determine the theoretical heat release of complete hydration of slag , this value comes from existing research results; 7. Calculate the total heat release of the Portland cement-slag system using formulas (23) to (25): ; 8. Calculate the temperature field distribution of concrete using formula (41) to obtain the temperature prediction result.

[0110] The following introduces the experimental verification process of the concrete temperature field prediction results.

[0111] The mix ratio of mass concrete is shown in Table 10, which is as follows: Table 10 Concrete mix ratio

[0112]

[0113] The test adopted Cement, fine aggregate uses river sand with particle size distribution zone II, coarse aggregate uses basalt aggregate with continuous grading of 5mm~20mm, and the specimen size is 1.5m×1.5m×0.8m. Based on the above parameters, the temperature rise test is carried out. According to the concrete composition materials, the concrete parameters required for the temperature field prediction of large-volume concrete are as follows: thermal conductivity of concrete Specific heat capacity of concrete ; Density of concrete , the initial temperature inside the concrete is 20℃.

[0114] During the test, the internal temperature rise of concrete was measured using an SCT2002 intelligent temperature controller (temperature sensor). The temperature measurement resolution was 0.1°C, the maximum measurement range was -55°C to 125°C, and the temperature acquisition interval was 1 hour. The prepared concrete specimens were placed in a 2-cm-thick foam box for thermal insulation. Temperature sensors were placed at the center of the concrete specimen (point A) and one-quarter of the way from the surface (point B). The concrete testing environment was maintained at 20 ± 1°C. Data acquisition was terminated when the concrete temperature reached equilibrium with the ambient temperature.

[0115] Figure 5 The figure shows a comparison of the simulated and monitored temperatures at the center and one-quarter of the distance from the surface of a large-volume concrete specimen. As can be seen, after pouring, the internal temperature of the concrete rises rapidly, reaching a peak within one day. Due to the thickness and poor thermal conductivity of large-volume concrete, heat is concentrated within the concrete, with the highest temperature at the center, 56.7°C. With increasing hydration time, the center temperature decreases to 35.2°C after three days. By the seventh day of hydration, the heat dissipation rate of the concrete exceeds the heat generation rate, and the temperature of the entire concrete structure approaches the ambient temperature. The measured (i.e., monitored) temperatures are generally consistent with the simulated temperature results. Using the measured results as a benchmark, the maximum error between the two is 10.26%, indicating that the model is reasonable and has high prediction accuracy.

[0116] Figure 10The temperature distribution contours for a 1.5m×1.5m concrete cross-section after hydration times of 1, 3, and 7 days are shown. (a) shows the temperature contour for 1 day, (b) shows the temperature contour for 3 days, and (c) shows the temperature contour for 7 days. The contours clearly show that the temperature is highest at the center of the concrete and gradually decreases from the center outward. By the 7th day of hydration, the temperature difference between the center and the surface approaches the ambient temperature.

[0117] In summary, the technical solution provided in this embodiment proposes a prediction model for the degree of hydration of Portland cement and a model for the degree of hydration of slag based on the hydration kinetics of Portland cement. On this basis, a prediction model for the hydration heat of Portland cement systems and cement-slag systems under different conditions is established. Furthermore, based on the solid conduction theory and the finite difference method, the evolution law of the central temperature of large-volume concrete in the Portland cement-slag system is predicted. This solution eliminates the need to rely on experimental measurements for the prediction of the hydration heat of large-volume concrete in the cement-slag system. It only requires obtaining parameters such as the mix ratio, thermal conductivity, and specific heat capacity of the large-volume concrete to obtain the prediction results of the concrete temperature field. The experimental results show that this solution can accurately predict the exothermic hydration process and adiabatic temperature rise of cementitious materials.

[0118] Based on the same inventive concept, this embodiment provides a system for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder. The system is configured to execute the steps of the method for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder provided in any of the above embodiments, including: a hydration heat prediction model building unit configured to express the total heat release of the Portland cement-slag system as the sum of the hydration heat release of the Portland cement and the hydration heat release of the slag, thereby obtaining a Portland cement-slag hydration heat release prediction model; an adiabatic temperature prediction unit configured to multiply the total heat release of the Portland cement-slag system calculated by the Portland cement-slag hydration heat release prediction model by the amount of cementitious material per cubic meter to obtain an internal heat source term of the concrete heat conduction differential equation, and solve the concrete heat conduction differential equation using a finite difference method to obtain a temperature field distribution of the concrete under adiabatic conditions; The hydration heat of the Portland cement is calculated based on the hydration degree of the Portland cement, which is predicted by a Portland cement hydration degree prediction model. The Portland cement hydration degree prediction model is constructed based on the PK hydration kinetic model and comprehensively considers the effects of hydration time, water-cement ratio, specific surface area, relative humidity, and curing environment temperature on the hydration rate of Portland cement. The heat released by slag hydration is calculated based on the slag hydration degree; the slag hydration degree is predicted by a slag hydration degree model, which comprehensively considers the effects of slag content, hydration time, water-binder ratio, specific surface area and curing environment temperature on the slag hydration process.

[0119] The system for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder provided in this embodiment can implement the steps and processes of the method for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder provided in any of the above embodiments and achieve the same technical effects, which will not be described in detail here.

[0120] The embodiments of the present application can be applied to Figure 1 In the illustrated computer device, computer device 200 may include one or more of the following components: a processor 201, a memory 203, a communication interface 202, and a communication bus 204. Memory 203 may be connected to processor 201 via bus 204. The bus enables data transmission between processor 201 and memory 203. Buses may be classified as address buses, data buses, control buses, and the like. Memory 203 stores a computer program, which processor 201 executes to implement the steps of the method for predicting the hydration heat and adiabatic temperature of concrete containing slag powder as provided in any of the aforementioned embodiments.

Claims

1. A method for predicting the hydration heat and adiabatic temperature of concrete mixed with slag powder, characterized in that: include: The total heat release of the Portland cement-slag system is expressed as the sum of the hydration heat release of Portland cement and the hydration heat release of slag, and a prediction model for the hydration heat release of Portland cement-slag is obtained. The total heat release of the Portland cement-slag system calculated by the Portland cement-slag hydration heat release prediction model is multiplied by the amount of cementitious material per cubic meter to obtain the internal heat source term of the concrete heat conduction differential equation, and the concrete heat conduction differential equation is solved using a finite difference method to obtain the temperature field distribution of the concrete under adiabatic conditions; The hydration heat of the Portland cement is calculated based on the hydration degree of the Portland cement, which is predicted by a Portland cement hydration degree prediction model. The Portland cement hydration degree prediction model is constructed based on the PK hydration kinetic model and comprehensively considers the effects of hydration time, water-cement ratio, specific surface area, relative humidity, and curing environment temperature on the hydration rate of Portland cement. The heat released by slag hydration is calculated based on the slag hydration degree; the slag hydration degree is predicted by a slag hydration degree model, which comprehensively considers the effects of slag content, hydration time, water-binder ratio, specific surface area and curing environment temperature on the slag hydration process.

2. The method according to claim 1, characterized in that The slag hydration degree model is constructed based on the hydration kinetics mechanism, including: The hydration kinetics of slag is considered to be controlled by the diffusion reaction process. Based on the diffusion reaction process equation in the hydration kinetics equation of silicate cement, the initial hydration kinetics equation of slag is written. The maximum hydration degree of slag is introduced to correct the initial hydration kinetic equation of the slag to obtain a final hydration kinetic equation of the slag, and the final hydration kinetic equation of the slag is integrated to obtain a first slag hydration degree prediction model.

3. The method according to claim 2, characterized in that The maximum hydration degree of the slag is related to the slag activity index, and comprehensively considers the effects of different slag water-binder ratios, hydration time, slag content, specific surface area, and curing environment temperature on the hydration process.

4. The method according to claim 3, characterized in that The expression of the maximum hydration degree of the slag is as follows: ， The final slag hydration kinetic equation is expressed as follows: ， Where, is the maximum hydration degree of slag; is the activity index of slag; is the water-binder ratio; is the slag content; is the specific surface area of ​​slag; is the reference value of slag specific surface area; is the apparent activation energy of slag; is the universal gas constant; is the reference temperature; To maintain the ambient temperature; is the hydration degree of slag; is the reaction rate constant of the slag diffusion reaction process, which is related to the water-binder ratio and slag content; The hydration time.

5. The method according to claim 1, wherein The method further includes: obtaining a slag hydration degree model by surface fitting based on the statistical results of experimental data from various existing studies, as follows: Obtain the test results of different researchers on the non-evaporable water content of Portland cement-slag system and the corresponding test conditions; Determine a preliminary expression for the degree of slag hydration based on an expression for the non-evaporable water content of a Portland cement-slag system, wherein the non-evaporable water content of the Portland cement-slag system is expressed as the sum of the non-evaporable water content of the Portland cement and the non-evaporable water content of the slag; Substituting the test results of non-evaporable water content of Portland cement-slag system by different researchers into the preliminary expression of slag hydration degree, the slag hydration degree under different test conditions was calculated; Surface fitting is performed on the slag hydration degree under different test conditions to obtain a surface fitting expression for the slag hydration degree; the surface fitting expression for the slag hydration degree is used to characterize the variation of the slag hydration degree with hydration time under different water-binder ratios; Comprehensively considering the effects of effective water-binder ratio, hydration time, slag content, specific surface area and curing environment temperature on the slag hydration process, the slag hydration degree expression of the surface fitting is modified to obtain a second slag hydration degree prediction model; The effective water-binder ratio adopts the slag activity index to adjust the effective contribution of slag.

6. The method according to claim 5, characterized in that The expression of the second slag hydration degree prediction model is as follows: ， Where, is the hydration time; is the hydration degree of slag; is the activity index of slag; is the slag content; is the effective water-binder ratio; is the specific surface area of ​​slag; is the reference value of slag specific surface area; is the apparent activation energy of slag; is the universal gas constant; is the reference temperature; To maintain the ambient temperature.

7. The method according to claim 3 or 5, characterized in that The slag activity index comprehensively considers the influence of the two different forms of Al2O3, tetracoordinate and hexacoordinate, in the chemical composition of the slag on the slag activity.

8. The method according to claim 1, characterized in that The concrete heat conduction differential equation is solved by the finite difference method to obtain the temperature field distribution of the concrete under adiabatic conditions, including: Perform 2D meshing of concrete cross sections; Initial conditions and adiabatic boundary conditions are set, and the finite difference method is used to calculate the temperature of each node at each moment in two-dimensional space to obtain the adiabatic temperature prediction results of concrete mixed with slag powder; The types of nodes include: internal nodes, boundary nodes and corner nodes.

9. A system for predicting the hydration heat and adiabatic temperature of concrete containing slag powder, the system being configured to execute the steps of the method for predicting the hydration heat and adiabatic temperature of concrete containing slag powder according to any one of claims 1 to 8, comprising: a hydration heat prediction model building unit configured to express the total heat release of the Portland cement-slag system as the sum of the hydration heat release of the Portland cement and the hydration heat release of the slag, thereby obtaining a Portland cement-slag hydration heat release prediction model; an adiabatic temperature prediction unit configured to multiply the total heat release of the Portland cement-slag system calculated by the Portland cement-slag hydration heat release prediction model by the amount of cementitious material per cubic meter to obtain an internal heat source term of the concrete heat conduction differential equation, and solve the concrete heat conduction differential equation using a finite difference method to obtain a temperature field distribution of the concrete under adiabatic conditions; The hydration heat of the Portland cement is calculated based on the hydration degree of the Portland cement, which is predicted by a Portland cement hydration degree prediction model. The Portland cement hydration degree prediction model is constructed based on the PK hydration kinetic model and comprehensively considers the effects of hydration time, water-cement ratio, specific surface area, relative humidity, and curing environment temperature on the hydration rate of Portland cement. The heat released by slag hydration is calculated based on the slag hydration degree; the slag hydration degree is predicted by a slag hydration degree model, which comprehensively considers the effects of slag content, hydration time, water-binder ratio, specific surface area and curing environment temperature on the slag hydration process.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method for predicting hydration heat and adiabatic temperature of concrete containing slag powder according to any one of claims 1 to 8.

Images