A calculation method and system for early temperature non-load construction design value of a wall

Abstract

The application relates to a calculation method and system for wall early temperature non-load construction design value, and belongs to the technical field of construction control. The calculation method comprises the following steps: obtaining geometric parameters, material parameters, environmental parameters and hydration heat parameters of a concrete continuous wall; calculating a thermal diffusion coefficient according to the material parameters, and generating a heat generation rate function changing with time; calculating a Biot number based on the geometric parameters, the material parameters and the environmental parameters, and defining a dimensionless coordinate and a dimensionless time; solving a characteristic equation according to the Biot number to obtain a characteristic value sequence and a corresponding mode function sequence; calculating weight coefficients of each mode based on an initial temperature distribution and the mode function sequence; solving a time domain ordinary differential equation and applying convolution integration to generate a time-varying mode amplitude function sequence, synthesize a dimensionless temperature field, determine a convergent solution by truncating a mode number, and convert the dimensionless temperature field into a physical temperature field for output. The application can accurately capture the early temperature gradient distribution law of the wall.

Description

Technical Field

[0001] This application relates to the field of construction control technology, and in particular to a calculation method and system for the early temperature non-load structural design value of a wall. Background Technology

[0002] In the construction of large-volume structures such as continuous concrete walls, the heat generated by the cement hydration reaction causes a sharp rise in the internal temperature of the structure, while the heat lost from the surface to the environment creates a temperature difference between the inside and outside. This uneven temperature field will induce thermal stress, and when the tensile stress exceeds the tensile strength of the concrete, cracks will occur, seriously affecting the durability and safety of the structure. Therefore, accurately predicting the early temperature field distribution of concrete is a key prerequisite for crack prevention and control.

[0003] Currently, temperature calculation models for large-volume concrete are commonly used in engineering practice for prediction. These models are derived based on the assumption of bidirectional symmetrical heat dissipation, with boundary conditions set as uniform heat dissipation from both sides and a simplified heat transfer path of symmetrical diffusion from the center of the cross-section to the surface. However, the actual working conditions of continuous walls in underground spaces differ fundamentally from these models: First, the thickness of continuous walls is much smaller than that of large-volume concrete structures, and their high specific surface area leads to a significant increase in heat dissipation efficiency, with the cooling rate increasing sharply as the wall thickness decreases; second, the thin-walled nature causes the temperature gradient to exhibit a strongly nonlinear distribution along the thickness direction, with a gradient value much higher than that of large-volume concrete at the same temperature difference. These differences in boundary conditions and heat transfer paths cause the calculation results of existing models to deviate systematically from the measured temperature field of continuous walls. In particular, existing models cannot accurately capture the early temperature gradient distribution of the wall in the coupling effect of rapid surface cooling and lag in core temperature rise, leading to inaccurate crack risk assessments. Summary of the Invention

[0004] In order to accurately capture the early temperature gradient distribution law of the wall, this application provides a calculation method and system for the early temperature non-load structural design value of the wall.

[0005] Firstly, this application provides a method for calculating the early-stage temperature of a wall under non-load structural design, employing the following technical solution:

[0006] A method for calculating the early-stage temperature of a wall under non-load structural design, the method comprising:

[0007] Obtain the geometric parameters, material parameters, environmental parameters, and heat of hydration parameters of the concrete continuous wall;

[0008] Based on the material parameters, the thermal diffusivity is calculated, and a heat generation rate function that varies with time is generated based on the heat of hydration parameters.

[0009] The Biwo number is calculated based on the geometric parameters, material parameters, and environmental parameters, and dimensionless coordinates and dimensionless time are defined based on the geometric parameters and thermal diffusivity.

[0010] Solve the characteristic equation based on the Biot number to obtain the eigenvalue sequence and the corresponding mode shape function sequence;

[0011] Based on the initial temperature distribution and the mode shape function sequence, the weighting coefficients of each mode are calculated by orthogonal integration;

[0012] Based on the heat production rate function, eigenvalue sequence and weighting coefficients, solve the time-domain ordinary differential equation and apply convolution integral to generate a time-varying modal amplitude function sequence;

[0013] A dimensionless temperature field is synthesized using the time-varying modal amplitude function sequence and mode shape function sequence. The convergent solution is determined by truncating the mode number, and the dimensionless temperature field is converted into a physical temperature field output.

[0014] By adopting the above technical solution, an asymmetric heat dissipation boundary model for concrete continuous walls, a coupled computational framework of time-varying hydration heat source terms and eigenvalue expansion method is established, solving the boundary condition mismatch problem in the application of traditional large-volume concrete formulas to continuous walls. The characteristic equation is used to accurately characterize unilateral convective heat dissipation, spatial discretization is achieved through orthogonal mode decomposition, and the transient effect of hydration heat release is captured by Duhamel integration. Finally, the temperature field T(x,t) at any location and time is output with adaptive series truncation. Compared with empirical formulas, the method in this application improves the temperature prediction accuracy to the theoretical solution level, significantly reducing the risk of cracks caused by temperature rise estimation errors, and providing a reliable data-driven decision-making basis for early maintenance of underground engineering projects.

[0015] Secondly, this application provides a calculation system for the early-stage temperature of walls under non-load structural design, employing the following technical solution:

[0016] A calculation system for determining the early-stage temperature of a wall under non-load structural design, the calculation system comprising:

[0017] The acquisition module is used to acquire the geometric parameters, material parameters, environmental parameters, and hydration heat parameters of the concrete continuous wall.

[0018] The heat generation rate function generation module is used to calculate the thermal diffusivity based on the material parameters and generate a heat generation rate function that varies with time based on the heat of hydration parameters.

[0019] The Biot number calculation module is used to calculate the Biot number based on the geometric parameters, material parameters, and environmental parameters.

[0020] A dimensionless definition module is used to define dimensionless coordinates and dimensionless time based on the geometric parameters and thermal diffusivity.

[0021] The feature solving module is used to solve the characteristic equation based on the Biot number to obtain the eigenvalue sequence and the corresponding mode shape function sequence;

[0022] The weighting coefficient calculation module is used to calculate the weighting coefficient of each mode by orthogonal integration based on the initial temperature distribution and the mode shape function sequence.

[0023] The modal amplitude function sequence generation module is used to solve the time-domain ordinary differential equation and apply convolution integral based on the heat generation rate function, eigenvalue sequence and weight coefficients to generate a time-varying modal amplitude function sequence;

[0024] A dimensionless temperature field synthesis module is used to synthesize a dimensionless temperature field using the time-varying modal amplitude function sequence and mode shape function sequence;

[0025] The physical temperature field output module is used to determine the convergent solution by truncating the mode number and convert the dimensionless temperature field into a physical temperature field output. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the first process of a method for calculating the early temperature non-load structural design value of a wall according to one embodiment of this application.

[0027] Figure 2 This is a second flowchart illustrating a method for calculating the early-stage temperature of a wall under non-load structural design, according to one embodiment of this application.

[0028] Figure 3 This is a schematic diagram of the third process of a method for calculating the early temperature non-load structural design value of a wall according to one embodiment of this application. Detailed Implementation

[0029] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figure 1-3 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0030] This application discloses a method for calculating the early-stage temperature of a wall under non-load structural design.

[0031] Reference Figure 1 A method for calculating the early-stage temperature of a wall under non-load structural design, the calculation method including:

[0032] Step S101: Obtain the geometric parameters, material parameters, environmental parameters, and heat of hydration parameters of the concrete continuous wall;

[0033] Among them, geometric parameters include wall thickness L, material parameters include density ρ, specific heat capacity C and thermal conductivity k, environmental parameters include ambient temperature Te and surface heat exchange coefficient h, and hydration heat parameters include cementitious material consumption per cubic meter W, total hydration heat Q and time coefficient z.

[0034] Specifically, four types of essential physical parameters of the concrete continuous wall are systematically collected to construct a complete input domain for the temperature field. Geometric parameters (wall thickness L) define the spatial scale of heat conduction and directly affect the dimensionless process; material parameters (ρ, C, k) jointly characterize the thermal inertia (product of density and specific heat capacity) and thermal conductivity of concrete, and their ratio derives the thermal diffusivity α; environmental parameters (Te, h) quantify the boundary heat dissipation intensity, where the heat exchange coefficient h is related to Newton's law of surface cooling; hydration heat parameters (W, Q, z) are based on cement chemical kinetics and obtained through an exponential decay model. Describe the time-varying characteristics of the exothermic hydration of cementitious materials.

[0035] Understandably, this step is essentially about establishing a digital mapping of the physical world. For example, W (amount of adhesive material) directly determines the total heat release W×Q, while z (time coefficient) controls the heat release rate. Together, they constitute the core driving force of the internal heat source.

[0036] Step S102: Calculate the thermal diffusivity α based on the material parameters, and generate a heat generation rate function that varies with time based on the heat of hydration parameters;

[0037] The formula for the thermal diffusivity α is α = k / (ρ·C);

[0038] In the above formula, k is thermal conductivity, ρ is density, and C is specific heat capacity.

[0039] Specifically, the thermal diffusivity α is the core control parameter for unsteady-state heat conduction. Its physical meaning is the propagation speed of temperature disturbances in the medium. Calculating this value simplifies the Fourier heat conduction equation to the standard diffusion form. The heat production rate function q v The generation of (t) depends on the engineering modeling of hydration thermodynamics:

[0040] Step S103: Calculate the Biwo number Bi based on geometric parameters (wall thickness L), material parameters (thermal conductivity k), and environmental parameters (surface heat exchange coefficient h), and define dimensionless coordinates and dimensionless time based on geometric parameters (wall thickness L) and thermal diffusivity α.

[0041] Specifically, the formula for calculating the Bivouac number Bi is: The Biwoe number, Bi, is a competing parameter between boundary heat dissipation and internal heat conduction. Its value determines the temperature distribution pattern: when Bi→0, the surface temperature is uniform (ideal insulation); when Bi→∞, the surface temperature equals the ambient temperature (ideal heat dissipation). This parameter embeds the third type of boundary condition (convective heat transfer) into the eigenvalue problem, which is the core feature distinguishing it from the symmetrical heat dissipation of large-volume concrete. Furthermore, the dimensionless coordinate is defined as X=x / L, compressing the spatial scale to [0,1] and eliminating the influence of the absolute size of the wall thickness L; the dimensionless time is defined as τ=αt / L. 2 The time α / L required for heat diffusion through the wall 2 The time process is based on the benchmark scale.

[0042] In the above formula, h is the surface heat exchange coefficient, L is the wall thickness, k is the thermal conductivity, x is the spatial coordinate, and t is the time.

[0043] Step S104: Solve the characteristic equation based on the Biwo number Bi to obtain the eigenvalue sequence and the corresponding mode shape function sequence;

[0044] Specifically, the formula for solving the characteristic equation based on the Biwo number Bi is as follows:

[0045] ;

[0046] in, The nth term of the eigenvalue sequence represents the spatial frequency of different modes, while the mode shape function describes the spatial morphology of the corresponding mode; the corresponding mode shape function sequence is:

[0047] ;

[0048] Among them, the mode shapes satisfy orthogonality. , and These are the mode shape function sequences corresponding to the nth and mth terms, respectively, where m and n are integers greater than or equal to 1.

[0049] Step S105: Based on the initial temperature distribution and mode shape function sequence, calculate the weighting coefficients of each mode through orthogonal integration;

[0050] Specifically, the weighting coefficient C n The calculation formula is:

[0051] ;

[0052] Where θ0(X) is the initial dimensionless temperature distribution. For mode shape function, Let Nn be the norm. In the above formula, the physical essence of the weighting coefficients is the projection decomposition of the initial temperature field in the mode space. Through the generalized Fourier series expansion in Hilbert space, any initial distribution is represented as a linear combination of orthonormal bases, and the coefficients C... n This refers to the energy proportion weight of each mode. The integration process utilizes modal orthogonality to extract independent components. The numerator is the inner product of the initial temperature distribution and the mode shape function Xn, representing their spatial correlation. The denominator is the modulus square of the mode shape function, used to normalize the contribution weights of different modes. This step is essentially a Fourier series expansion, which can transform any initial conditions into the initial values ​​of the superposition of characteristic modes.

[0053] Step S106: Based on the heat generation rate function, eigenvalue sequence and weighting coefficient, solve the time domain ordinary differential equation and apply convolution integral to generate a time-varying mode amplitude function sequence.

[0054] Specifically, the formula for the time-domain ordinary differential equation is:

[0055] ;

[0056] The expression for generating the time-varying modal amplitude function sequence by solving the time-domain ordinary differential equation and applying the convolution integral is as follows:

[0057] .

[0058] It should be noted that the core of this step lies in establishing a dynamic mapping relationship between the heat release from hydration and temperature evolution. Its mathematical basis is the modal amplitude ordinary differential equation derived by the method of separation of variables. This equation reveals the dual composite response mechanism of the heat conduction system: on the one hand, eigenvalues... Characterizing the inherent thermal decay characteristics of each mode, higher-order modes correspond to rapidly decaying high-frequency components, while lower-order modes dominate long-term temperature rise behavior; on the other hand, the source term f n (τ) projects the spatially distributed heat source onto the characteristic mode space, quantifying the energy input of hydration heat release to a specific mode.

[0059] The specific solution process utilizes the Duhamel convolution principle, whose physical essence is to characterize the thermal memory effect of the system: the modal amplitude at the current moment depends not only on the intensity of the transient heat source, but also on the cumulative effect of historical heat sources. The convolution kernel function... As a decaying memory factor, recent heat sources are given higher weight. Under this modeling approach: when the hydration heat release rate decays exponentially (controlled by the time coefficient z), the convolution integral can be analytically obtained, completely avoiding numerical iteration; while for complex heat release curves, efficient calculation can be achieved through piecewise integration. This mechanism ultimately generates a sequence of time-varying modal amplitude functions, the physical meaning of which is to decouple the continuous spatiotemporal coupling problem into the time-domain evolution of independent modes, laying the foundation for temperature field reconstruction.

[0060] Step S107: The dimensionless temperature field is synthesized using the time-varying modal amplitude function sequence and the mode shape function sequence. The convergent solution is determined by truncating the mode number, and the dimensionless temperature field is converted into a physical temperature field output.

[0061] Specifically, the conversion formula for transforming a dimensionless temperature field into a physical temperature field output is as follows:

[0062] .

[0063] In the above formula, T e The ambient temperature is used. Holographic reconstruction of the temperature field is achieved through the superposition of orthogonal modes. Its mathematical principle stems from a core corollary of the Sturm-Liouville theory: a complete orthogonal function system can accurately represent any physical field distribution. The time-varying amplitude Tn(τ) is then compared with the spatial mode shape. Modal superposition essentially involves performing a generalized inverse Fourier transform in Hilbert space, reconstructing a dimensionless temperature field that strictly satisfies the heat conduction control equations and boundary conditions. The adaptive determination of the truncated mode number N is crucial for ensuring engineering accuracy: based on the eigenvalue spectrum distribution characteristics, the contribution of higher-order modes decreases exponentially with increasing n. Truncating is controlled by a relative error threshold, achieving a dynamic balance between computational efficiency and accuracy. The transformation of the physical temperature field relies on the principle of dimensional consistency. When the dimensionless solution is reassigned to actual physical units, the construction of the characteristic temperature difference integrates three key parameters: material thermal inertia, thermal conductivity, and heat generation intensity, ensuring that the output temperature T(x,t) strictly corresponds to the actual physical process. This process ultimately forms a spatially continuous, time-evolving three-dimensional temperature field cloud map, which can be directly input into the stress calculation module to assess cracking risk.

[0064] In the above embodiments, an asymmetric heat dissipation boundary model for continuous concrete walls, a coupled computational framework of time-varying hydration heat source terms and eigenvalue expansion methods is established, solving the boundary condition mismatch problem in the application of traditional large-volume concrete formulas to continuous walls. The characteristic equation is used to accurately characterize unilateral convective heat dissipation, spatial discretization is achieved through orthogonal mode decomposition, and the transient effect of hydration heat release is captured by Duhamel integration. Finally, the temperature field T(x,t) at any location and time is output with adaptive series truncation. Compared with empirical formulas, the method of this application improves the temperature prediction accuracy to the theoretical solution level, significantly reducing the risk of cracks caused by temperature rise estimation errors, and providing a reliable data-driven decision-making basis for early maintenance of underground engineering projects.

[0065] Reference Figure 2 As one embodiment of step S102, the step of generating a heat production rate function that varies with time based on the heat of hydration parameters includes:

[0066] Step S201: Calculate the adiabatic temperature rise function T based on the hydration heat parameters. ad (t):

[0067] ;

[0068] In the above formula, W is the amount of cementitious material used per cubic meter, Q is the total heat of hydration, z is the time coefficient, and t is the time.

[0069] Understandably, the adiabatic temperature rise is first calculated using the formula in the "Standard for Construction of Mass Concrete". This model uses the exponential term e... -zt Approaching the self-decelerating characteristics of cement hydration;

[0070] Step S202: Differentiate the adiabatic temperature rise function to obtain the heat production rate function:

[0071] .

[0072] Specifically, its physical essence is the heat release power (W / z³) of a unit volume of concrete per unit time. This derivative relationship originates from the first law of thermodynamics: under adiabatic conditions, the increase in internal energy equals the heat release.

[0073] Reference Figure 3 As one implementation of the truncated mode number in step S107, the step of determining the truncated mode number includes:

[0074] Step a, set the initial number of modes n=1 and the preset error threshold. ;

[0075] Among them, the fundamental mode (n=1) corresponds to the lowest order vibration mode and occupies the dominant part of the temperature field energy. Starting from this mode ensures that the iteration path conforms to the energy decay priority of the physical system. A preset error threshold is set. (Usually 10) −3 ~10 −5 The setting is based on a balance between engineering accuracy requirements and numerical stability: when the temperature field magnitude is 10... 2 At ℃, =10 −3 The corresponding absolute error is 0.1℃, meeting the sensitivity requirements for crack control in concrete temperature control specifications. This threshold is essentially an upper bound control parameter for truncating the residual term; its mathematical meaning is equivalent to requiring the relative residual of the truncated series to be less than... .

[0076] Step b: Calculate the modal amplitude function under the current mode number n. and mode shape function ;

[0077] Among them, the modal amplitude function is essentially the time-domain energy weight of the nth mode, which is determined by the Duhamel convolution solution; the mode shape function is the spatial eigenfunction of the Sturm-Liouville eigenvalue problem, and its physical meaning is to describe the standing wave distribution pattern of temperature along the wall thickness direction.

[0078] Step c, synthesize the approximate solution of the temperature field:

[0079] ;

[0080] In the above equation, the essence of the approximate solution of the synthesized temperature field is a finite-dimensional Hilbert space projection; the characteristic function system {Φn} constitutes a complete orthogonal basis, and any temperature field satisfying the boundary conditions can be expanded in this space. The approximate solution truncated to the nth order is equivalent to the optimal subspace approximation in the sense of energy norm, and its convergence is guaranteed by the amplitude decay characteristics and mode orthogonality.

[0081] Step d, calculate the relative error between adjacent modal solutions:

[0082] , where θ (0) ≡0;

[0083] Among them, the essence of defining relative error is online diagnosis of series convergence. When When the time is right, it indicates that the energy contribution of the new mode is negligible compared to the existing solution, satisfying the sufficient condition for numerical convergence. The underlying reason for using relative error (rather than absolute error) here is that the magnitude of the temperature field changes drastically with time and space (e.g., the temperature rise at the center can reach 50℃ in the early stage of curing, while the surface temperature is only 10℃), and relative quantity can adaptively match local sensitivity.

[0084] Step e, if If the condition is met, proceed to step f; otherwise, proceed to step g.

[0085] Step f: Determine the number of truncated modes N = n;

[0086] Step g: Let n = n + 1, and return to step b.

[0087] In the above steps, as the Bi number increases (e.g., due to thick walls or weak convection), the eigenvalues ​​λn become more concentrated, requiring more modes to capture boundary layer effects. The iterative mechanism automatically matches this need. The loop structure in this step essentially constructs a greedy algorithm framework: scanning from low-order to high-order modes step by step, locking the cutoff point with minimal computational cost while satisfying accuracy requirements.

[0088] In the above implementation, a closed-loop control mechanism of asymptotic mode expansion, incremental error diagnosis, and adaptive truncation is used. Based on strict series convergence criteria, the computational load is reduced to 1 / 10 to 1 / 50 of the full-modal solution while ensuring the accuracy of temperature field calculation. When the hydration heat release rate changes, the system automatically adjusts the number of modes to capture the transient details of the rapid temperature rise process. When the wall thickness L increases, the number of modes is adaptively increased through the redistribution of eigenvalue λn to avoid overfitting of thin walls and underfitting of thick walls.

[0089] This application also discloses a calculation system for the early temperature non-load structural design value of a wall.

[0090] A calculation system for determining the early-stage temperature of a wall under non-load structural design conditions, the calculation system comprising:

[0091] The acquisition module is used to acquire the geometric parameters, material parameters, environmental parameters, and hydration heat parameters of the concrete continuous wall.

[0092] The heat generation rate function generation module is used to calculate the thermal diffusivity based on material parameters and generate a heat generation rate function that varies with time based on hydration heat parameters.

[0093] The Biot number calculation module is used to calculate the Biot number based on geometric parameters, material parameters, and environmental parameters.

[0094] The dimensionless definition module is used to define dimensionless coordinates and dimensionless time based on geometric parameters and thermal diffusivity.

[0095] The characteristic solution module is used to solve the characteristic equation based on the Biot number to obtain the eigenvalue sequence and the corresponding mode shape function sequence;

[0096] The weighting coefficient calculation module is used to calculate the weighting coefficients of each mode based on the initial temperature distribution and mode shape function sequence through orthogonal integration.

[0097] The modal amplitude function sequence generation module is used to solve the time-domain ordinary differential equation and apply convolution integral based on the heat generation rate function, eigenvalue sequence and weight coefficients to generate a time-varying modal amplitude function sequence.

[0098] The dimensionless temperature field synthesis module is used to synthesize a dimensionless temperature field using time-varying modal amplitude function sequences and mode shape function sequences.

[0099] The physical temperature field output module is used to determine the convergent solution by truncating the mode number and convert the dimensionless temperature field into a physical temperature field output.

[0100] The calculation system for early-stage temperature non-load structural design of walls according to an embodiment of this application can implement any of the above calculation methods, and the specific working process of each module in the calculation system can refer to the corresponding process in the above method embodiments.

[0101] In the several embodiments provided in this application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for example, the division of a certain module is merely a logical functional division, and in actual implementation there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0102] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A method for calculating the early-stage temperature of a wall under non-load structural design, characterized in that, The calculation method includes: Obtain the geometric parameters, material parameters, environmental parameters, and heat of hydration parameters of the concrete continuous wall; Based on the material parameters, the thermal diffusivity is calculated, and a heat generation rate function that varies with time is generated based on the heat of hydration parameters. The Biwo number is calculated based on the geometric parameters, material parameters, and environmental parameters, and dimensionless coordinates and dimensionless time are defined based on the geometric parameters and thermal diffusivity. Solve the characteristic equation based on the Biot number to obtain the eigenvalue sequence and the corresponding mode shape function sequence; Based on the initial temperature distribution and the mode shape function sequence, the weighting coefficients of each mode are calculated by orthogonal integration; Based on the heat production rate function, eigenvalue sequence and weighting coefficients, solve the time-domain ordinary differential equation and apply convolution integral to generate a time-varying modal amplitude function sequence; A dimensionless temperature field is synthesized using the time-varying modal amplitude function sequence and mode shape function sequence. The convergent solution is determined by truncating the mode number, and the dimensionless temperature field is converted into a physical temperature field output. The formula for the time-domain ordinary differential equation is: Solving the time-domain ordinary differential equation and applying the convolution integral, the expression for generating the time-varying modal amplitude function sequence is as follows:

2. The calculation method for the early-stage temperature of a wall under non-load structural design according to claim 1, characterized in that: The formula for the thermal diffusivity α is α=k / (ρ·C); where k is thermal conductivity, ρ is density, and C is specific heat capacity.

3. The calculation method for the early-stage temperature non-load structural design value of a wall according to claim 2, characterized in that, The steps for generating a heat production rate function that varies with time based on the hydration heat parameters include: Calculate the adiabatic temperature rise function T based on the hydration heat parameters. ad (t): In the above formula, W is the amount of cementitious material used per cubic meter, Q is the total heat of hydration, z is the time coefficient, and t is the time. Differentiating the adiabatic temperature rise function yields the heat production rate function as follows:

4. The calculation method for the early-stage temperature non-load structural design value of a wall according to claim 3, characterized in that, The formula for calculating the Bivouac number Bi is: Bi = (h·L) / k; the dimensionless coordinate is defined as X = x / L; the dimensionless time is defined as τ = α·t / L. 2 ; In the above formula, h is the surface heat exchange coefficient, L is the wall thickness, k is the thermal conductivity, x is the spatial coordinate, and t is the time.

5. The calculation method for the early-stage temperature non-load structural design value of a wall according to claim 4, characterized in that, The formula for solving the characteristic equation based on the Bi of the Bi number is as follows: Where, λ n For the nth term of the eigenvalue sequence, the corresponding mode shape function sequence is: Among them, the mode shapes satisfy orthogonality. Φ n (X) and Φ m (X) are the mode function sequences corresponding to the nth and mth terms, respectively, where m and n are integers greater than or equal to 1.

6. The calculation method for the early-stage temperature non-load structural design value of a wall according to claim 5, characterized in that, The weighting coefficient C n The calculation formula is: Where θ0(X) is the initial dimensionless temperature distribution, Φ n (X) is the mode shape function. Let N be the norm.

7. The calculation method for the early-stage temperature non-load structural design value of a wall according to claim 6, characterized in that, The steps for determining the number of truncated modes include: Step a. Set the initial number of modes n = 1 and the preset error threshold ε; Step b. Calculate the modal amplitude function a under the current mode number n. n (τ) and mode shape function Φ n (X); Step c. Synthesize the approximate solution of the temperature field: Step d. Calculate the relative error between adjacent modal solutions: Where θ (0) ≡0; Step e. If δ n If <∈, then determine the number of truncated modes N=n; otherwise, let n=n+1 and return to step b.

8. The calculation method for the early-stage temperature non-load structural design value of a wall according to claim 7, characterized in that, The conversion formula for converting a dimensionless temperature field into a physical temperature field output is as follows: In the above formula, T e The ambient temperature.

9. A calculation system for determining the early-stage temperature of a wall under non-load structural design, characterized in that, The computing system includes: The acquisition module is used to acquire the geometric parameters, material parameters, environmental parameters, and hydration heat parameters of the concrete continuous wall. The heat generation rate function generation module is used to calculate the thermal diffusivity based on the material parameters and generate a heat generation rate function that varies with time based on the heat of hydration parameters. The Biot number calculation module is used to calculate the Biot number based on the geometric parameters, material parameters, and environmental parameters. A dimensionless definition module is used to define dimensionless coordinates and dimensionless time based on the geometric parameters and thermal diffusivity. The feature solving module is used to solve the characteristic equation based on the Biot number to obtain the eigenvalue sequence and the corresponding mode shape function sequence; The weighting coefficient calculation module is used to calculate the weighting coefficient of each mode by orthogonal integration based on the initial temperature distribution and the mode shape function sequence. The modal amplitude function sequence generation module is used to solve the time-domain ordinary differential equation and apply convolution integral based on the heat generation rate function, eigenvalue sequence and weight coefficients to generate a time-varying modal amplitude function sequence; A dimensionless temperature field synthesis module is used to synthesize a dimensionless temperature field using the time-varying modal amplitude function sequence and mode shape function sequence; The physical temperature field output module is used to determine the convergent solution by truncating the mode number and convert the dimensionless temperature field into a physical temperature field output. The formula for the time-domain ordinary differential equation is: Solving the time-domain ordinary differential equation and applying the convolution integral, the expression for generating the time-varying modal amplitude function sequence is as follows:

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