Concrete dam operation period temperature field reconstruction calculation method and system

Abstract

The invention belongs to the field of temperature field finite element calculation, and discloses a concrete dam operation period temperature field reconstruction calculation method and system, and the method comprises the following steps: S1, determining a concrete temperature field basic theory; s2, establishing a stable temperature field reconstruction method; s3, establishing an unstable temperature field reconstruction method; and S4, verifying the validity of the algorithm in the dam surface temperature inversion analysis process. According to the method, the sensitivity degree of the overall temperature field precision to changes can be reduced, and the temperature field calculation efficiency relative to a traditional inversion analysis method can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of finite element calculation of temperature fields, and particularly relates to a method and system for reconstructing and calculating the temperature field during the operation period of a concrete dam. Background Art

[0002] An accurate concrete displacement field is crucial for predicting and preventing possible structural problems, and it is necessary to construct an accurate temperature field. To obtain the temperature field of a concrete dam, scholars have proposed various methods, which can be roughly summarized as: numerical simulation analysis method, inversion analysis method, spatial interpolation method, and data model method. The numerical calculation method requires setting initial conditions, boundary conditions, and various calculation parameters of materials first. However, due to the randomness of factors such as air temperature, water temperature, sunlight, and material ratio, as well as the approximation of temperature boundary setting, it is very difficult to accurately simulate the temperature field. In addition, the actual conditions at the pouring site are complex, and the calculation parameters obtained through experiments do not match the actual parameters. Especially after the dam has been in service for many years, the continuous change of the moisture content in the concrete, the continuous curing of the material, and the change of the microstructure will all affect the material parameters. Therefore, scholars use measured temperature values and optimization algorithms for iterative calculation to obtain the material parameters with the smallest error between the measured value and the calculated value. However, there are still problems with the approximate setting of boundary conditions in the forward calculation of the inversion. Common spatial interpolation methods include linear interpolation, spline interpolation, Kriging interpolation, etc. Spatial interpolation is performed using monitoring data and the characteristics of the variation structure. When the spatial distribution of the monitoring data is uneven or at the boundary of the spatial distribution of the measurement points, due to the lack of sufficient information, the stability and convergence of the interpolation results are not good. In addition, the spatial interpolation method is sensitive to monitoring data, and when there is noise in the data, the interpolation accuracy is greatly reduced. The data model method uses intelligent algorithms to construct a mapping model between the measured temperature value and the main factors such as pouring temperature, thermal conductivity, air temperature, water-binder ratio, and cooling water temperature, and can only predict local temperature values and cannot obtain the overall temperature field. Another data model method uses a neural network to construct a mapping model between the measured value and the current numerically calculated temperature field, and trains a network model with fixed parameters. When the measured temperature value at the next moment is measured, the temperature field is generated through the network model. However, when training the neural network model, a large amount of data needs to be fed, and numerical calculations need to be performed to construct temperature data samples, which still involves problems such as the setting of temperature boundaries. Summary of the Invention

[0003] To solve the problems existing in the prior art, the present invention provides a method and system for reconstructing and calculating the temperature field during the operation period of a concrete dam. Considering that the traditional methods are easily affected by external factors, noise, and boundary conditions, and the accuracy and the integrity of the temperature field cannot be satisfied simultaneously, the sensitivity of the overall temperature field accuracy to changes can be reduced, and the temperature field accuracy can be improved compared with the traditional analysis methods.

[0004] To achieve the above object, the present invention provides the following solutions:

[0005] A method for reconstructing the temperature field during the operation period of a concrete dam, the method comprising:

[0006] Construct the basic theory of the concrete temperature field, determine the initial conditions and boundary conditions of the heat conduction equation of the concrete temperature field, and perform discretization in the time domain and the space domain;

[0007] According to the spatial discretization form and the time discretization form of the heat conduction equation of the concrete temperature field, establish a method for reconstructing the steady temperature field;

[0008] According to the method for reconstructing the steady temperature field, establish a method for reconstructing the unsteady temperature field;

[0009] According to the method for reconstructing the steady temperature field and the method for reconstructing the unsteady temperature field, perform a reconstruction calculation on the temperature field during the operation period of the concrete dam.

[0010] Preferably, the spatial discretization form of the heat conduction equation of the concrete temperature field is obtained by the Galerkin method, including:

[0011] Perform spatial discretization on the heat conduction equation of the concrete temperature field using the Galerkin method to obtain

[0012]

[0013] Wherein,

[0014] T nd is the temperature value at the grid node;

[0015] is the heat conduction matrix;

[0016] is the contribution matrix of the heat release boundary to the heat conduction matrix;

[0017] R = ∫N T NdΩ is the heat capacity matrix;

[0018] is the load matrix caused by the adiabatic temperature rise;

[0019] is the load matrix caused by the heat release boundary;

[0020] N is the shape function; N T is the transposed function of the shape function; Ω is the calculation domain; Γ is the outer boundary corresponding to the region; T b is the boundary temperature value; β is the surface heat release coefficient; is the vector differential operator, n is the surface outer normal direction, α is the temperature conductivity coefficient of the concrete, c is the specific heat of the concrete, ρ is the density of the concrete, and τ is the time.

[0021] Preferably, the Newmark method is used to obtain the time-domain discrete form of the heat conduction equation of the concrete temperature field, including:

[0022]

[0023] Wherein,

[0024] is the equivalent force vector, including the external force and the initial condition correction term; is the predicted temperature vector, used to predict the temperature distribution at the next time step; p is the prediction coefficient; T τ is the temperature vector; T′ τ is the temperature rate vector; Δτ is the time step; is the Newmark parameter.

[0025] Preferably, a stable temperature field reconstruction method is established, including:

[0026] The temperature of the stable temperature field does not change with time, and the constrained node values are fixed. The temperature change of other nodes except the constrained nodes in the model is:

[0027] (H + G) (q-p)*q {T} q*1 ={Q Γ} (q-p)*1

[0028]

[0029] Wherein, {T d} m*1 is the measured value array of m measuring points, and [N] m*q is the interpolation coefficient matrix of the monitoring points;

[0030] When the temperature changes at the upstream and downstream boundaries are T wt ={T1,…,T w}, T at ={T1,…,T a} respectively, the temperature change of the measured points is expressed as:

[0031]

[0032] Wherein, T a is the air temperature;

[0033]

[0034] n=a + w;

[0035]

[0036] Preferably, an unstable temperature field reconstruction method is established, including:

[0037] The temperature change of the measured points is transformed to obtain:

[0038]

[0039] Among them,

[0040]

[0041] The calculation formula for the boundary temperature value is:

[0042]

[0043] The present invention also provides a temperature field reconstruction calculation system for the operation period of a concrete dam. The system is used to implement the foregoing method, and the system includes: a determination module, a first construction module, a second construction module, and a reconstruction module;

[0044] The determination module is used to construct the basic theory of the concrete temperature field, determine the initial conditions and boundary conditions of the heat conduction equation of the concrete temperature field, and perform time-domain discretization and space-domain discretization;

[0045] The first construction module is used to establish a stable temperature field reconstruction method according to the space-domain discretized form and time-domain discretized form of the heat conduction equation of the concrete temperature field;

[0046] The second construction module is used to establish an unstable temperature field reconstruction method according to the stable temperature field reconstruction method;

[0047] The reconstruction module is used to perform reconstruction calculation on the temperature field during the operation period of the concrete dam according to the stable temperature field reconstruction method and the unstable temperature field reconstruction method.

[0048] Preferably, in the determination module, the space-domain discretized form of the heat conduction equation of the concrete temperature field is obtained by the Galerkin method, including:

[0049] Performing spatial discretization on the heat conduction equation of the concrete temperature field by the Galerkin method to obtain

[0050]

[0051] Among them,

[0052] T nd is the temperature value at the grid node;

[0053] is the heat conduction matrix;

[0054] is the contribution matrix of the heat release boundary to the heat conduction matrix;

[0055] R = ∫NT NdΩ is the heat capacity matrix;

[0056] is the load matrix caused by adiabatic temperature rise;

[0057] is the load matrix caused by the exothermic boundary;

[0058] N is the shape function; N T is the transpose function of the shape function; Ω is the computational domain; Γ is the outer boundary corresponding to the region; T b is the boundary temperature value; β is the surface heat release coefficient; is the vector differential operator, n is the direction of the surface normal, α is the thermal conductivity of concrete, c is the specific heat of concrete, ρ is the density of concrete, and τ is time.

[0059] Preferably, in the determination module, the time domain discrete form of the heat conduction equation of the concrete temperature field is obtained using the Newmark method, including:

[0060]

[0061] in,

[0062] is the equivalent force vector, including the external force and initial condition correction terms; is the predicted temperature vector, which is used to predict the temperature distribution of the next time step; p is the prediction coefficient; T τ is the temperature vector; T′ τ is the temperature rate vector; Δτ is the time step; is the Newmark parameter.

[0063] Preferably, the first building block includes:

[0064] The temperature of the stable temperature field does not change with time. The constrained node values are fixed. The temperature changes of other nodes in the model except the constrained nodes are:

[0065] (H+G) (q-p)*q {T} q*1 ={Q Γ} (q-p)*1

[0066]

[0067] Among them, {T d} m*1 is the array of measured values of m measuring points, [N] m*q is the interpolation coefficient matrix of the monitoring points;

[0068] When the temperature changes of the upstream and downstream boundaries are Twt = {T1, …, T w}, T at = {T1, …, T a}, the temperature change of the measured point is expressed as:

[0069]

[0070] Among them, T a is the air temperature;

[0071]

[0072] n = a + w;

[0073]

[0074] Preferably, the second construction module includes:

[0075] The temperature change of the measured point is transformed to obtain:

[0076]

[0077] Among them,

[0078]

[0079] The calculation formula for the boundary temperature value is:

[0080]

[0081] Compared with the prior art, the beneficial effects of the present invention are:

[0082] Based on the influence of the unit temperature change at the boundary on the temperature at the sensor position, and using all the measured values of the sensors as the data basis, the present invention utilizes the principle of heat conduction in the temperature field, the assumption of separating the measured temperature values and the least square method to calculate the overall temperature field, providing guidance or reference for the reconstruction of the dam temperature field in similar projects, and can be used to reduce the influence of the boundary conditions on the dam temperature field and improve the calculation efficiency of the temperature field reconstruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] In order to more clearly illustrate the technical solutions of the present invention, the following briefly introduces the drawings required in the embodiments. Obviously, the following described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0084] Figure 1 It is a specific implementation flowchart of a method for reconstructing the temperature field during the operation period of a concrete dam in an embodiment of the present invention;

[0085] Figure 2 It is a schematic diagram of the temperature field calculation grid model in the embodiment of the present invention;

[0086] Figure 3 It is a schematic diagram of the numerical simulation result of the temperature field of the calculation grid model in the embodiment of the present invention;

[0087] Figure 4 It is a schematic diagram of setting the reconstruction constraint boundary of the temperature field in the embodiment of the present invention;

[0088] Figure 5 It is a schematic diagram of the comparison between the measured values and the finite element calculated values of different parts of the temperature field reconstruction model in the embodiment of the present invention. Specific embodiments

[0089] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0090] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0091] Embodiment 1

[0092] The embodiment of the present invention provides a method for reconstructing and calculating the temperature field during the operation period of a concrete dam and its application method. Considering that the traditional method is easily affected by external factors, noise, and boundary conditions, and the accuracy and integrity of the temperature field cannot be satisfied simultaneously, a method with less influence and higher accuracy is obtained to improve the calculation efficiency. The specific implementation flowchart is as shown in the appendix Figure 1 shown. It mainly includes 4 steps: S1, establishing the basic theory of the concrete temperature field; S2, establishing a method for reconstructing the steady temperature field; S3, establishing a method for reconstructing the unsteady temperature field; S4, verifying the effectiveness of the algorithm in the process of dam surface temperature inversion analysis.

[0093] It mainly includes the following steps:

[0094] The first step is to construct the basic theory of the concrete temperature field, determine the initial conditions and boundary conditions, and perform time-domain discretization and space-domain discretization.

[0095] The relationship between the temperature of an object and time and space is established through the heat conduction equation, and the initial conditions and boundary conditions are determined to find the temperature field of the target. The basic theory is as follows:

[0096] Within the region R, the concrete temperature at any point (x, y, z) satisfies the heat conduction equation:

[0097]

[0098] Where: c is the specific heat of concrete (kJ / kg·°C); ρ is the density of concrete (kg / m 3 ); θ is the adiabatic temperature rise of concrete (°C), α = λ / cρ is the thermal diffusivity of concrete (m 2 / h), is the Laplace operator; τ is time; λ is the thermal conductivity.

[0099] The initial condition satisfies one of the following two possible conditions:

[0100] (1) At the initial instant (τ = 0), the temperature field is a known function T0(x, y, z) of the coordinates (x, y, z), i.e.:

[0101] T(x, y, z, 0) = T0(x, y, z)

[0102] (2) In most cases, the temperature distribution at the initial instant can be considered constant, i.e., when τ = 0:

[0103] T(x, y, z, 0) = T0 = constant

[0104] The boundary condition satisfies one of the following three possible conditions:

[0105] (1) The first kind of boundary condition: The temperature on the concrete surface is a known function of time, i.e.:

[0106] T(τ) = f1(τ), τ > 0

[0107] (2) The second kind of boundary condition: The heat flux on the concrete surface is a known function of time, i.e.:

[0108]

[0109] (3) The third kind of boundary condition: First, assume that the heat flux through the concrete surface is proportional to the difference between the concrete surface temperature T and the air temperature T a (°C), i.e.:

[0110]

[0111] Where n is the direction of the outer normal of the surface, and β is the surface heat transfer coefficient.

[0112] The spatial domain discrete form of the heat conduction equation is obtained by the Galerkin method, and the specific method is as follows:

[0113] Performing spatial discretization on Equation (1) using the Galerkin method, we can obtain

[0114]

[0115] In the formula:

[0116] T nd is the temperature value at the grid node;

[0117] is the heat conduction matrix;

[0118] is the contribution matrix of the heat release boundary to the heat conduction matrix;

[0119] R = ∫N T NdΩ is the heat capacity matrix;

[0120] is the load matrix caused by the adiabatic temperature rise;

[0121] is the load matrix caused by the heat release boundary;

[0122] where, N is the shape function; N T is the transposed function of the shape function; Ω is the calculation domain; Γ is the outer boundary corresponding to the region; T b is the boundary temperature value; β is the surface heat release coefficient; is the vector differential operator.

[0123] Meanwhile, according to the basic formula of the Newmark method, the basic formula of the temperature field in the time domain can be obtained, that is

[0124]

[0125] T′ τ+1 = T′ τ + ΔT′ τ (3-2)

[0126] In the formula:

[0127] T τ is the temperature vector; T′ τ is the temperature rate vector; Δτ is the time step; is the Newmark parameter.

[0128] Substituting Eqs. (3-1) and (3-2) into Eq. (2), we get

[0129]

[0130] In the formula:

[0131] is the equivalent force vector, including the external force and the initial condition correction term;

[0132] is the predicted temperature vector, used to predict the temperature distribution at the next time step; p is the prediction coefficient.

[0133] In the second step, a stable temperature field reconstruction method is established, and the detailed steps are as follows:

[0134] The temperature of the stable temperature field does not change with time, and the constrained node values are fixed. The temperature change of other nodes except the constrained nodes in the model is:

[0135] (H + G) (q-p)*q {T} q*1 ={Q Γ} (q-p)*1 (5 - 1)

[0136]

[0137] Where:

[0138] {T d} m*1 is the measured value array of m measuring points;

[0139] [N] m*q is the interpolation coefficient matrix of the monitoring points

[0140] When the temperature changes at the upstream and downstream boundaries are T wt ={T1,..., T w}, T at ={T1,..., T a} respectively, the temperature change of the measured points can be expressed as:

[0141]

[0142] In the formula:

[0143]

[0144] n = a + w;

[0145]

[0146] In the third step, an unsteady temperature field reconstruction method is established, and the detailed steps are as follows:

[0147] The calculation of the unsteady temperature field is mainly to solve the reconstructed temperature field at any time.

[0148] By extending from (6 - 1) and (6 - 2), we get:

[0149]

[0150] In the formula:

[0151]

[0152] By extending from (7 - 2), the calculation formula for the reconstructed temperature field at any time is as follows:

[0153]

[0154] In the fourth step, a model is constructed for analysis to verify the effectiveness of the algorithm in the process of dam surface temperature inversion analysis. The distribution law of the concrete temperature field is obtained by using the finite element forward calculation to prepare reference data for the inversion of the surface temperature. The temperature field calculation grid model is as Figure 2 ; the numerical simulation results of the temperature field of the calculation grid model are as Figure 3 shown; based on the temperature values obtained from the simulation, the temperature field is reconstructed according to the proposed temperature field reconstruction method and the corresponding implementation program (GeHoMadrid); the constraint boundaries for the temperature field reconstruction are set as Figure 4 shown; the comparison between the measured values and the finite element calculated values at different parts of the model is as Figure 5 shown. It is found that the trends are consistent and the errors are small.

[0155] The temperature field reconstruction method is constrained by the temperature zoning on the dam surface. Taking the measured temperature values as known quantities, a finite element calculation method for reconstructing the temperature field during the operation period of the concrete dam is proposed based on the temperature heat conduction principle, and the reconstruction calculation methods for the steady temperature field and the unsteady temperature field are deduced. It provides guidance or reference for the temperature field calculation of similar projects.

[0156] Embodiment 2

[0157] The present invention also provides a calculation system for reconstructing the temperature field during the operation period of a concrete dam. The system is used to implement the foregoing method, and the system includes: a determination module, a first construction module, a second construction module, and a reconstruction module;

[0158] The determination module is used to construct the basic theory of the concrete temperature field, determine the initial conditions and boundary conditions of the heat conduction equation of the concrete temperature field, and perform discretization in the time domain and the space domain;

[0159] The first construction module is used to establish a method for reconstructing the steady temperature field according to the spatial domain discretization form and the time domain discretization form of the heat conduction equation of the concrete temperature field;

[0160] The second construction module is used to establish a method for reconstructing the unsteady temperature field according to the method for reconstructing the steady temperature field;

[0161] The reconstruction module is used to reconstruct and calculate the temperature field during the operation period of the concrete dam according to the method for reconstructing the steady temperature field and the method for reconstructing the unsteady temperature field.

[0162] In this embodiment, in the determination module, the spatial domain discrete form of the heat conduction equation of the concrete temperature field is obtained by the Galerkin method, including:

[0163] The Galerkin method is used for spatial discretization of the heat conduction equation of the concrete temperature field to obtain

[0164]

[0165] where

[0166] T nd is the temperature value at the grid node;

[0167] is the heat conduction matrix;

[0168] is the contribution matrix of the heat release boundary to the heat conduction matrix;

[0169] R = ∫N T NdΩ is the heat capacity matrix;

[0170] is the load matrix caused by adiabatic temperature rise;

[0171] is the load matrix caused by the heat release boundary;

[0172] N is the shape function; N T is the transposed function of the shape function; Ω is the calculation domain; Γ is the outer boundary corresponding to the region; T b is the boundary temperature value; β is the surface heat release coefficient; is the vector differential operator, n is the direction of the surface outer normal, α is the temperature conductivity coefficient of the concrete, c is the specific heat of the concrete, ρ is the density of the concrete, and τ is the time.

[0173] In this embodiment, in the determination module, the time domain discrete form of the heat conduction equation of the concrete temperature field is obtained by the Newmark method, including:

[0174]

[0175] where

[0176] is the equivalent force vector, including the external force and the initial condition correction term; is the predicted temperature vector, used to predict the temperature distribution at the next time step; p is the prediction coefficient; T τ is the temperature vector; T′ τ is the temperature rate vector; Δτ is the time step; is the Newmark parameter.[[ID=6G]]

[0177] In this embodiment, the first construction module includes:

[0178] The temperature of the stable temperature field does not change with time, the constrained node values are fixed, and the temperature changes of other nodes except the constrained nodes in the model are:

[0179] (H + G) (q-p)*q {T} q*1 ={Q Γ} (q-p)*1

[0180]

[0181] where {T d} m*1 is the measured value array of m measuring points, and [N] m*q is the interpolation coefficient matrix of the monitoring points;

[0182] When the temperature changes at the upstream and downstream boundaries are T wt ={T1,…,T w}, T at ={T1,…,T a} respectively, the temperature change of the measured points is expressed as:

[0183]

[0184] where T a is the air temperature;

[0185]

[0186] n = a + w;

[0187]

[0188] In this embodiment, the second construction module includes:

[0189] The temperature change of the measured points is transformed to obtain:

[0190]

[0191] where

[0192]

[0193] The calculation formula for the boundary temperature value is:

[0194]

[0195] The embodiments described above are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A calculation method for reconstructing the temperature field during the operation period of a concrete dam, characterized in that, The method includes: Construct the basic theory of the concrete temperature field, determine the initial conditions and boundary conditions of the heat conduction equation of the concrete temperature field, and perform discretization in the time domain and the spatial domain; Establish a method for reconstructing the steady temperature field according to the discretized form in the spatial domain and the discretized form in the time domain of the heat conduction equation of the concrete temperature field; Establish a method for reconstructing the unsteady temperature field according to the method for reconstructing the steady temperature field; Reconstruct and calculate the temperature field during the operation period of the concrete dam according to the method for reconstructing the steady temperature field and the method for reconstructing the unsteady temperature field.

2. The method according to claim 1, characterized in that, The discretized form in the spatial domain of the heat conduction equation of the concrete temperature field is obtained by the Galerkin method, including: Perform spatial discretization on the heat conduction equation of the concrete temperature field using the Galerkin method to obtain where, T nd is the temperature value at the grid node; is the heat conduction matrix; is the contribution matrix of the exothermic boundary to the heat conduction matrix; R = ∫N T NdΩ is the heat capacity matrix; is the load matrix caused by the adiabatic temperature rise; is the load matrix caused by the exothermic boundary; N is the shape function; N T is the transpose function of the shape function; Ω is the computational domain; Γ is the outer boundary corresponding to the region; T b is the boundary temperature value; β is the surface heat transfer coefficient; is the vector differential operator, n is the outer normal direction of the surface, α is the thermal diffusivity of concrete, c is the specific heat of concrete, ρ is the density of concrete, and τ is the time.

3. The method according to claim 2, wherein The discretized form in the time domain of the heat conduction equation of the concrete temperature field is obtained using the Newmark method, including: where, is the equivalent force vector, including the external force and the initial condition correction term; is the predicted temperature vector, used to predict the temperature distribution at the next time step; p is the prediction coefficient; T τ is the temperature vector; T τ ′ is the temperature rate vector; Δτ is the time step; is the Newmark parameter.

4. The method according to claim 3, wherein Establish a method for reconstructing the steady temperature field, including: The temperature of the steady temperature field does not change with time, the constrained node values are fixed, and the temperature changes of other nodes outside the constrained nodes in the model are: Among them, {T d} m*1 is the array of measured values of m measuring points, [N] m*q is the interpolation coefficient matrix of the monitoring points; When the temperature changes at the upstream and downstream boundaries are T wt ={T1,…,T w}, T at ={T1,…,T a}, respectively, the temperature change at the measured point is expressed as: Among them, T a is the air temperature; n = a + w; 5. The method according to claim 4, wherein Establish a method for reconstructing the unsteady temperature field, including: The temperature change of the measured points is transformed to obtain: where, The calculation formula for the boundary temperature value is:

6. A temperature field reconstruction calculation system for a concrete dam during the operation period, the system is used to implement the method described in any one of claims 1-5, characterized in that, The system includes: a determination module, a first construction module, a second construction module, and a reconstruction module; The determination module is used to construct the basic theory of the concrete temperature field, determine the initial conditions and boundary conditions of the heat conduction equation of the concrete temperature field, and perform discretization in the time domain and the spatial domain; The first construction module is used to establish a method for reconstructing the steady temperature field according to the discretized form in the spatial domain and the discretized form in the time domain of the heat conduction equation of the concrete temperature field; The second construction module is used to establish a method for reconstructing the unsteady temperature field according to the method for reconstructing the steady temperature field; The reconstruction module is used to reconstruct and calculate the temperature field during the operation period of the concrete dam according to the method for reconstructing the steady temperature field and the method for reconstructing the unsteady temperature field.

7. The system according to claim 6, characterized in that In the determination module, the discretized form in the spatial domain of the heat conduction equation of the concrete temperature field is obtained by the Galerkin method, including: Perform spatial discretization on the heat conduction equation of the concrete temperature field using the Galerkin method to obtain where, T nd is the temperature value at the grid node; is the heat conduction matrix; is the contribution matrix of the exothermic boundary to the heat conduction matrix; R = ∫N T NdΩ is the heat capacity matrix; is the load matrix caused by the adiabatic temperature rise; is the load matrix caused by the exothermic boundary; N is the shape function; N T is the transposed function of the shape function; Ω is the computational domain; Γ is the outer boundary corresponding to the region; T b is the boundary temperature value; β is the surface heat release coefficient; is the vector differential operator, n is the outer normal direction of the surface, α is the thermal diffusivity of concrete, c is the specific heat of concrete, ρ is the density of concrete, and τ is the time.

8. The system according to claim 7, wherein In the determination module, the discretized form in the time domain of the heat conduction equation of the concrete temperature field is obtained using the Newmark method, including: where, is the equivalent force vector, including the external force and the initial condition correction term; is the predicted temperature vector, used to predict the temperature distribution at the next time step; p is the prediction coefficient; T τ is the temperature vector; T τ ′ is the temperature rate vector; Δτ is the time step; is the Newmark parameter.

9. The system according to claim 8, wherein The first construction module includes: The temperature of the steady temperature field does not change with time, the constrained node values are fixed, and the temperature changes of other nodes outside the constrained nodes in the model are: Among them, {T d} m*1 is the array of measured values of m measurement points, [N] m*q is the interpolation coefficient matrix of the monitoring points; When the temperature changes at the upstream and downstream boundaries are T wt ={T1,…,T w}, T at ={T1,…,T a}, respectively, the temperature change at the measured point is expressed as: Among them, T a is the air temperature; n = a + w; 10. The system according to claim 9, characterized in that, The second construction module includes: The temperature change of the measured points is transformed to obtain: where, The calculation formula for the boundary temperature value is:

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