Dam material transient-creep parameter progressive optimization inversion method

Abstract

The application discloses a dam material transient-creep parameter progressive optimization inversion method and belongs to the technical field of dam material parameter inversion, which comprises the following steps: through alternating progressive optimization inversion of a multi-objective function set of transient parameters and creep parameters, until the inversion accuracies corresponding to optimal solutions of inversion parameters obtained by two times of continuous inversion are the same, and the optimal solution of the transient parameters and the creep parameters obtained by current inversion is taken as a transient-creep parameter inversion result. The application realizes efficient and accurate identification of dam transient and creep parameters, thereby improving inversion accuracy and calculation efficiency, guaranteeing the physical rationality of the result, and providing reliable support for dam operation period safety monitoring and risk assessment.

Description

Technical Field

[0001] This invention belongs to the field of dam material parameter inversion technology, specifically involving a progressive optimization inversion method for transient-creep parameters of dam materials. Background Technology

[0002] High dams exist and operate in complex environments with large hydraulic loads and high stress levels, resulting in complex material parameter evolution mechanisms. Influenced by multiple factors such as construction technology, environmental factors, the scaling effect of indoor tests, and fitting errors in experimental data, it is difficult to directly obtain material parameters reflecting the dam's true service state during design. Dam deformation typically includes instantaneous deformation and creep deformation, which are coupled and mutually influential. When inverting the material parameters of high dams, the dam body and foundation materials exist in several zones, with different material parameters for concrete or foundation in different areas. Furthermore, multiple models are involved, including the Drucker-Prager (DP) model and creep models, leading to a large number of instantaneous-creep inversion parameters for the dam and foundation materials.

[0003] An excessive number of inversion parameters not only affects efficiency but also reduces inversion accuracy. The main problems include: ① Significantly increased computational load. Considering more parameters means increasing the number of experimental designs, which greatly increases the computational load of finite element methods, resulting in low computational efficiency; ② Increased optimization difficulty. More parameter combinations lead to a larger parameter optimization space, thus increasing the difficulty of optimization and resulting in low optimization accuracy; ③ Confusion between parameters and deformation response. Different constitutive parameters correspond to different deformation components. If all parameters are optimized simultaneously, the response relationship between parameters and deformation components may be confused, thereby affecting the accuracy and physical interpretability of the inversion results.

[0004] Therefore, fully utilizing deformation safety monitoring data during dam operation to identify the true transient-creep parameters of dam and foundation materials is fundamental to the safety assessment of high dam operations. Currently, domestic and international scholars have conducted extensive research on dam material parameter inversion methods, mostly based on single-objective function inversion, primarily focusing on transient parameters, resulting in abundant findings. Further research is needed on progressive optimization inversion methods for transient-creep parameters of high dam and foundation materials. This involves iteratively updating the transient and creep parameters of dam and foundation materials to more realistically characterize the stress-deformation response of the dam structure, providing theoretical and technical support for high dam operational performance simulation and safety monitoring. Summary of the Invention

[0005] To address the aforementioned shortcomings in existing technologies, the dam material transient-creep parameter progressive optimization inversion method provided by this invention solves the problems in existing dam material parameter inversion processes, which are prone to low inversion efficiency, insufficient accuracy, and confusion between parameters and deformation response due to the large number of transient and creep parameters, large computational load, and complex optimization space, making it difficult to obtain true and reliable material parameters.

[0006] To achieve the aforementioned objectives, the technical solution adopted by this invention is: a progressive optimization inversion method for transient-creep parameters of dam materials, comprising: By alternating progressive optimization inversion of the multi-objective function set of transient and creep parameters until the inversion accuracy corresponding to the optimal solution of the inversion parameters obtained by two consecutive inversions is the same, the optimal solution of the transient and creep parameters obtained by the current inversion is taken as the transient-creep parameter inversion result. In the alternating progressive optimization inversion process: The multi-objective function set of the current inversion parameters is updated based on the inversion results of the previous inversion parameters. During the current inversion process, the solution set of inversion parameters is obtained by inversion based on the nonlinear mapping relationship between the inversion parameters and the deformation response. Then, the optimal solution of the current inversion parameters is determined by multivariate composite quantitative decision index. The inversion parameters are creep parameters or transient parameters.

[0007] Furthermore, in the multi-objective function set of the transient / creep parameters, each objective function is constructed based on the sum of squared relative errors between the measured displacement values ​​and the calculated displacement response values ​​of the transient / creep parameters at typical times for different measuring points.

[0008] Furthermore, the multi-objective function set of the transient / creep parameters Represented as: In the formula, Let j be the objective function. Let be the measured displacement value of measuring point j at time i. Let X be the calculated displacement response value of measuring point j at time i, and let X be the inversion parameter. k represents the number of typical moments.

[0009] Furthermore, the nonlinear mapping relationship between the inversion parameters and the deformation response is expressed as follows: In the formula, The values ​​are the finite element calculation values ​​for the dam displacement. For transient / creep parameters, For transient / creep parameter index, a i b i c represents the first, second, and third undetermined coefficients.

[0010] Furthermore, the multi-objective function set is inverted and optimized using a multi-objective particle swarm optimization algorithm to determine the inversion parameter solution set.

[0011] Furthermore, the multivariate composite quantitative decision index includes the statistical deviation between the inversion parameter solution set and the corresponding experimental and detection data, as well as the inversion accuracy of the inversion parameter solution set.

[0012] Furthermore, the statistical bias includes the Z-score determined based on the objectively existing random characteristics of the dam and foundation inversion parameters, and the multi-zone inversion parameters of the dam and foundation. index; The Z-score is represented as: In the formula, These are the transient / creep parameter values ​​for the dam body or foundation material in the inversion parameter solution. and The mean and standard deviation of the corresponding creep / transient parameter test and detection data sequences; The indicator is expressed as: In the formula, For the first The inversion parameters are the parameter values ​​in this set of inversion parameter solutions. and For the first The mean and standard deviation of the experimental and detection data sequences of each inversion parameter. This represents the number of inversion parameters.

[0013] Furthermore, the inversion accuracy of the inversion parameter solution set Represented as: In the formula, These are the inversion parameters for the dam and foundation. For measuring points The objective function value, The number of objective functions.

[0014] Furthermore, the alternating progressive optimization inversion process of the transient parameters and creep parameters is expressed as follows: In the formula, , These are the inversion results for transient and creep parameters, respectively. These are the transient parameter inversion values ​​obtained from the second inversion. For the solution process of multi-objective particle swarm optimization algorithm, It is a multi-objective function. , , These are the transient component separation results of measurement point j at time i, the measured deformation and the results based on... The difference between the transient positive analysis results and the measured deformation, The deformation of the response surface surrogate model at measurement point j at time i is calculated. , These are transient and creep parameter test groups designed based on engineering data. Based on Designed transient parameter test group, This indicates an assignment operation. This indicates the design of a parameter test group.

[0015] The beneficial effects of this invention are as follows: The present invention proposes a progressive optimization inversion method for transient-creep parameters of dam materials, which has significant advantages such as high computational efficiency, low dependence on network resources, high inversion accuracy, and strong physical interpretability.

[0016] The multi-objective function and progressive optimization strategy constructed based on the separation of transient and creep components in this invention enhance the ability to identify key parameters and the physical rationality of the results.

[0017] The lightweight alternating progressive inversion process constructed in this invention can be deployed in a local computing environment without relying on high-performance clusters or external network support, ensuring the independence and security of data, and has significant engineering application value and promotion prospects. Attached Figure Description

[0018] Figure 1 The flowchart of the dam material transient-creep parameter progressive optimization inversion method provided by the present invention is shown.

[0019] Figure 2 The three-dimensional finite element model diagram of the DG arch dam provided by this invention.

[0020] Figure 3 A schematic diagram of the vertical arrangement of the DG arch dam body provided by the present invention.

[0021] Figure 4 A comparison chart of the calculated and measured radial displacement values ​​of PL10-1 provided by this invention.

[0022] Figure 5 A comparison chart of the calculated and measured radial displacement values ​​of PL14-1 provided by this invention.

[0023] Figure 6The diagram shows a comparison between the calculated and measured values ​​of the inversion parameters provided by this invention; wherein, (a) measured value (low temperature); (b) measured value (high temperature); (c) deformation calculation result based on the first inversion result (low temperature); (d) deformation calculation result based on the first inversion result (high temperature); (e) deformation calculation result based on the final inversion result (low temperature); and (f) deformation calculation result based on the final inversion result (high temperature). Detailed Implementation

[0024] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0025] This embodiment provides a progressive optimization inversion method for transient-creep parameters of dam materials; See Figure 1 ,include: By alternating progressive optimization inversion of the multi-objective function set of transient and creep parameters until the inversion accuracy corresponding to the optimal solution of the inversion parameters obtained by two consecutive inversions is the same, the optimal solution of the transient and creep parameters obtained by the current inversion is taken as the transient-creep parameter inversion result. In the alternating progressive optimization inversion process: The multi-objective function set of the current inversion parameters is updated based on the inversion results of the previous inversion parameters. During the current inversion process, the solution set of inversion parameters is obtained by inversion based on the nonlinear mapping relationship between the inversion parameters and the deformation response. Then, the optimal solution of the current inversion parameters is determined by multivariate composite quantitative decision index. The inversion parameters are creep parameters or transient parameters.

[0026] In this embodiment, in the multi-objective function set of transient / creep parameters, each objective function is constructed based on the sum of squared relative errors between the measured displacement values ​​and the calculated displacement response values ​​of the transient / creep parameters at typical times for different measuring points.

[0027] Specifically, in this embodiment, by constructing a multi-objective function set, multiple constraints and trade-offs among multiple objectives can be handled, and a set of optimal solutions can be returned to determine the optimal solution; wherein, the optimal solution is represented as a solution that is not dominated by each other, that is, there is no solution that is no worse than other solutions on all objectives and is strictly superior to other solutions on at least one objective.

[0028] In this embodiment, a multi-objective function set for transient / creep parameters is constructed. Represented as: In the formula, Let j be the objective function. Let be the measured displacement value of measuring point j at time i. Let X be the calculated displacement response value of measuring point j at time i, and let X be the inversion parameter. k represents the number of typical moments.

[0029] In this embodiment, during the dam material parameter inversion process, after determining the inversion target value and the material parameters to be inverted, it is necessary to construct a nonlinear mapping relationship between the material parameters and the deformation response based on the finite element calculation results. To balance accuracy and computational efficiency, a quadratic polynomial without cross terms is used to construct the response surface equation between the parameters to be inverted and the dam deformation, which is expressed as: In the formula, The values ​​are the finite element calculation values ​​for the dam displacement. For transient / creep parameters, For transient / creep parameter index, a i b i c represents the first, second, and third undetermined coefficients.

[0030] In this embodiment, the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is used to invert and optimize the multi-objective function set to determine the inversion parameter solution set. The MOPSO algorithm is an improvement on the Particle Swarm Optimization (PSO) algorithm. It introduces Pareto dominance to guide the search process and uses a global repository (REP) to maintain the non-dominated solutions generated during the optimization process to guide particle motion. Furthermore, the MOPSO algorithm uses multiple hypercubes to divide the search space, with particles distributed in different hypercubes, effectively exploring different regions and maintaining solution diversity, thereby obtaining the solution set of the multi-objective function.

[0031] In this embodiment, each objective function in the multi-objective function set represents the sum of squared relative errors between the measured displacement and the calculated displacement at each typical moment of the corresponding measuring point. Therefore, the material parameter solution set obtained by the MOPSO algorithm consists of several Pareto solutions that are mutually non-dominated. In this embodiment, by integrating the accuracy of experiments, detection, and inversion, a multi-dimensional composite quantitative decision index for the inversion of high dam and foundation material parameters is proposed to determine the optimal solution of the inversion parameters in the inversion parameter solution set.

[0032] In this embodiment, the multivariate composite quantitative decision indicators include the statistical deviation between the inversion parameter solution set and the corresponding experimental and detection data, as well as the inversion accuracy of the inversion parameter solution set.

[0033] In this embodiment, the statistical bias includes the Z-score determined based on the objectively existing random characteristics of the dam and foundation inversion parameters, and the multi-zone inversion parameters of the dam and foundation. index.

[0034] Specifically, during the design, construction, and operation of high dams, numerous laboratory tests and in-situ inspections of the physical and mechanical properties of materials are typically conducted. The statistical characteristics of these tests, compared to methods for determining design parameters, better reflect the mechanical properties of the dam body and foundation materials. This provides crucial foundational data for multi-objective inversion parameter decision-making. Therefore, using experimental and inspection data as decision information during parameter inversion helps improve the authenticity and reliability of material parameter identification results. Since the parameters of dam and foundation materials objectively exhibit randomness, the Z-score is used here to quantify the statistical deviation between the Pareto solution and the experimental and inspection data sequence, expressed as: In the formula, These are the transient / creep parameter values ​​for the dam body or foundation material in the inversion parameter solution. and The mean and standard deviation of the corresponding creep / transient parameter test and detection data sequences.

[0035] For multi-zone material parameters of dams and foundations, the statistical deviation index between Pareto solutions and material parameter test and verification information is used. It is represented as: In the formula, For the first The inversion parameters are the parameter values ​​in this set of inversion parameter solutions. and For the first The mean and standard deviation of the experimental and detection data sequences of each inversion parameter. This represents the number of inversion parameters.

[0036] As can be seen from the above formula, the smaller the statistical deviation index value, the lower the possibility that the current parameter combination deviates from the actual mechanical properties of the material, and the better the solution when other decision conditions remain unchanged.

[0037] In this embodiment, the sum of multiple objective function values ​​is used as the inversion accuracy index of the Pareto solution. Inversion accuracy index The smaller the value, the higher the overall inversion accuracy of the Pareto solutions, and the better the solution is when other decision conditions remain unchanged; inversion accuracy index Represented as: In the formula, These are the inversion parameters for the dam and foundation. For measuring points The objective function value, The number of objective functions.

[0038] In this embodiment, by calculating and analyzing the statistical deviation index and inversion accuracy index of each Pareto solution and experimental and detection data in the solution set, a multi-dimensional composite quantitative decision index for material parameters is obtained, thereby realizing the reasonable identification of material parameters in multiple zones of high dams and foundations.

[0039] In this embodiment, the material parameter inversion results can be obtained based on the multi-objective function set and optimal solution set solution method constructed above. However, dam deformation typically includes instantaneous deformation and creep deformation, which are coupled and mutually influential. Furthermore, the number of instantaneous and creep parameters is enormous, the computational load is high, and the optimization space is complex, easily leading to low inversion efficiency, insufficient accuracy, and confusion between parameters and deformation response, making it difficult to obtain truly reliable material parameters. Therefore, parameter sensitivity analysis can be provided to obtain key creep and instantaneous parameters for inversion. Based on the instantaneous and creep parameters to be inverted, this embodiment employs alternating progressive optimization inversion to approximate the true material parameters and improve inversion accuracy.

[0040] In this embodiment, the alternating progressive optimization inversion process of transient parameters and creep parameters is represented as follows: In the formula, , These are the inversion results for transient and creep parameters, respectively. These are the transient parameter inversion values ​​obtained from the second inversion. For the solution process of multi-objective particle swarm optimization algorithm, It is a multi-objective function. , , These are the transient component separation results of measurement point j at time i, the measured deformation and the results based on... The difference between the transient positive analysis results and the measured deformation, The deformation of the response surface surrogate model at measurement point j at time i is calculated. , These are transient and creep parameter test groups designed based on engineering data. Based on Designed transient parameter test group, This indicates an assignment operation. This indicates the design of a parameter test group.

[0041] Based on the above formula, the specific process of alternating progressive optimization inversion is as follows: 1) Based on the design values ​​of creep parameters and transient parameters, keeping the creep parameters constant, an orthogonal design test method is used to design experiments for the transient parameters to be inverted based on sensitivity analysis. Batch calculations are then performed based on the finite element model of the dam and foundation to construct a multi-objective function for transient parameter inversion and obtain the optimal solution. Based on design values ​​of creep parameters and inversion values ​​of transient parameters. Finite element analysis was performed, and the results were compared with measured values ​​to obtain the inversion accuracy index. .

[0042] 2) Based on the aforementioned optimal solution of transient parameters An orthogonal design experiment method was used to design experiments for the creep parameters to be inverted based on sensitivity analysis. Batch calculations were performed based on the finite element model of the dam and foundation to construct a multi-objective function for creep parameter inversion and to obtain the optimal solution. Inversion values ​​based on transient parameters and creep parameter inversion values Finite element analysis was performed, and the results were compared with measured values ​​to obtain the inversion accuracy index. .

[0043] 3) Based on the aforementioned creep parameter inversion values Orthogonal design experiment method was used to retrieve the transient parameter inversion values. Experimental design was conducted, and batch calculations were performed based on the finite element model of the dam and foundation. A multi-objective function for transient parameter inversion was constructed, and the optimal solution was obtained. Inversion values ​​based on transient parameters and creep parameter inversion values The inversion accuracy index is obtained by comparing it with the measured value. .

[0044] 4) Based on the aforementioned optimal solution of transient parameters The inversion values ​​of creep parameters were obtained using orthogonal design experiments. Experimental design was conducted, and batch calculations were performed based on the finite element model of the dam and foundation. A multi-objective function for creep parameter inversion was constructed, and the optimal solution was obtained. Inversion values ​​based on transient parameters and creep parameter inversion values Finite element analysis was performed, and the results were compared with measured values ​​to obtain the inversion accuracy index. .

[0045] 5) Repeat steps 2) to 4) until the accuracy target is reached. and The parameters remain almost unchanged, and the inversion is stopped. The creep parameters and transient parameters obtained at this point are the final inversion results.

[0046] Example 2: This embodiment is a specific application example of the progressive optimization inversion method for transient-creep parameters of dam materials in Embodiment 1, to demonstrate the advantages of the method of the present invention in the field of transient-creep parameter inversion.

[0047] In this embodiment, a three-dimensional finite element model of the dam is constructed. The maximum height of the DG high-concrete double-curvature arch dam is 210m, the normal reservoir water level is 1130.00m, the dead water level is 1120.00m, and the check flood level is 1132.73m. The dam body concrete is divided into three zones: A, B, and C, with design strength grades of C18036, C18030, and C18025, respectively. The foundation rock mass is classified into Class IV, III, and II rock masses from top to bottom, and also contains dikes such as β4, β8, β20, β21, β40, β43, β44, β47, β62, and β63, as well as faults such as f1, f54, f145, and f231. Based on the structural characteristics, material zoning, deformation monitoring layout, and topographic and geological conditions of the DG arch dam, a three-dimensional finite element model is constructed, as follows: Figure 2 As shown. The arch dam has 28 transverse joints, dividing it into 29 dam sections. Five vertical lines are installed along the dam body, located at dam sections 6, 10, 14 (arch crown beam), 19, and 24, providing 18 measuring points to measure the radial and tangential displacements of the arch dam. Figure 3 As shown.

[0048] Based on the design data, relevant reports, and concrete thermal performance tests of the DG arch dam project, and referring to similar projects, the elastoplastic parameters (elastic modulus E, Poisson's ratio μ, density ρ, cohesion c, internal friction angle φ) and thermodynamic parameters (thermal conductivity λ, specific heat s, linear expansion coefficient α) of the dam body and foundation were determined, as detailed in Table 1. Referring to the creep parameters of similar geotechnical engineering projects, the creep parameters of the dam body and foundation were proposed, as detailed in Table 2.

[0049] Table 1. DP Elastoplastic Model and Thermodynamic Parameters of Dam Body and Foundation Table 2 Parameters of the Strain Hardening Creep Model for Dam Body and Foundation The finite element method (FEM) calculations considered the effects of the dam's self-weight, hydrostatic pressure, uplift pressure, sediment pressure, and temperature load. The water load was applied based on measured upstream and downstream water level data at typical moments selected through parameter inversion. The sediment pressure was calculated using a sediment elevation of 1050.00 m upstream of the dam and a sediment buoyancy density of 0.5 t / m³.3 .

[0050] Temperature load has a significant impact on the deformation of arch dams. Based on the measured temperature data of the DG arch dam, the transient temperature field of the arch dam is calculated, and then the temperature load is determined. The year is divided into 36 periods, and the multi-year ten-day average temperature of the measured air temperature at the dam site and the dam surface temperature during the period from 2016 to 2022 is calculated.

[0051] In the parameter inversion process, the elastic modulus (E1~E3) of the concrete in zones A, B, and C of the dam body, the elastic modulus (E5, E6) of the Class III and IV bedrock near the dam foundation, and the cohesion and internal friction angle (c6, φ6) of the Class IV bedrock were mainly selected as the parameters to be inverted. Since the first transient parameter inversion process did not involve creep deformation calculation, its inversion results were mainly used as the initial input for the progressive optimization inversion method of material parameters. Therefore, in order to improve the calculation efficiency and more quickly approximate the real material parameters, this study adopted the transient parameter inversion results already available from the research group as the results of the first transient parameter inversion, and the inversion results are shown in Table 3.

[0052] Table 3 Results of the first transient parameter inversion Based on the inversion results in Table 3, inversion analysis was performed on the material creep parameters. Six measuring points (PL10-1, PL14-1, PL14-2, PL14-3, PL14-4, and PL19-1) from sections 10#, 14# (arch crown beam), and 19# of the DG arch dam were selected as typical measuring points for the inversion analysis. Since the Class II bedrock of the dam foundation has high strength and is buried at a depth of 120m from the foundation surface, its creep behavior has a relatively limited impact on the dam deformation. Therefore, the creep parameters of Class III and IV bedrock near the dam bottom were selected as the parameters to be inverted, and the results are shown in Table 4.

[0053] Table 4. Results of material creep parameter inversion Based on the parameter inversion results in Tables 3 and 4, finite element analysis was performed. The maximum relative error between the calculated values ​​and the measured displacements at each typical measuring point was 10.25% (2022 / 7 / 25, PL10-1), and the minimum was 0.43% (2021 / 8 / 23, PL14-1). The average relative error for all typical measuring points was 4.56%, indicating that the inversion accuracy needs further improvement. Therefore, based on the initial inversion results of transient and creep parameters, progressive optimization inversion of transient and creep parameters was performed until the inversion error met the requirements. The results are shown in Table 5.

[0054] Table 5 Results of the second transient parameter inversion Finite element analysis was performed using the inversion results of the second transient parameters and the first creep parameters, followed by accuracy analysis. The results show that the maximum relative error between the calculated and measured displacements at each typical measuring point is 5.99%, and the minimum is 0.01%. The average relative error for all typical measuring points is only 1.79%, a 61% reduction compared to the average relative error in the previous total deformation accuracy verification, indicating a significant improvement in accuracy. A comparison of the calculated and measured radial displacement values ​​at each typical measuring point from January 1, 2016 to September 1, 2022 is shown below. Figures 4-5 As shown in Table 6, the error comparison is as follows. Table 6 shows that the calculated and measured radial displacement values ​​are basically consistent, with the average absolute percentage error ranging from 1.59% to 5.48%. Based on this, a second creep parameter inversion was performed. The results showed no significant improvement in inversion accuracy; therefore, the transient-creep parameter progressive optimization inversion was completed.

[0055] Table 6 Errors between calculated and measured values ​​of typical measurement points inversion results Based on the initial transient and creep parameter inversion results, as well as the final inversion results, the total deformation (displacement along the river) of each vertical measuring point was calculated under the conditions of low temperature and high water level (January 18, 2022) and high temperature and high water level (August 23, 2021), and compared with the measured values. The results are as follows: Figure 6 As shown in the figure, under both low-temperature and high-temperature conditions, the dam deformation cloud map based on the final inversion results is closer to the measured values. The inversion accuracy of each measuring point is on average 19% higher than that of the first inversion result, verifying the reliability of the proposed inversion method.

[0056] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0057] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A progressive optimization inversion method for transient-creep parameters of dam materials, characterized in that, include: By alternating progressive optimization inversion of the multi-objective function set of transient and creep parameters until the inversion accuracy corresponding to the optimal solution of the inversion parameters obtained by two consecutive inversions is the same, the optimal solution of the transient and creep parameters obtained by the current inversion is taken as the transient-creep parameter inversion result. In the alternating progressive optimization inversion process: The multi-objective function set of the current inversion parameters is updated based on the inversion results of the previous inversion parameters. During the current inversion process, the solution set of the inversion parameters is obtained by inversion based on the nonlinear mapping relationship between the inversion parameters and the deformation response. Then, the optimal solution of the current inversion parameters is determined by multivariate composite quantitative decision index. The inversion parameters are creep parameters or transient parameters. The multivariate composite quantitative decision index includes the statistical deviation between the inversion parameter solution set and the corresponding experimental and detection data, as well as the inversion accuracy of the inversion parameter solution set; The alternating progressive optimization inversion process of the transient parameters and creep parameters is expressed as follows: In the formula, , These are the inversion results for transient and creep parameters, respectively. These are the transient parameter inversion values ​​obtained from the second inversion. For the solution process of multi-objective particle swarm optimization algorithm, It is a multi-objective function. , , These are the transient component separation results of measurement point j at time i, the measured deformation and the results based on... The difference between the transient positive analysis results and the measured deformation, The deformation of the response surface surrogate model at measurement point j at time i is calculated. , These are transient and creep parameter test groups designed based on engineering data. For based on Designed transient parameter test group, This indicates an assignment operation. This indicates the design of a parameter test group.

2. The method for progressive optimization and inversion of transient-creep parameters of dam materials according to claim 1, characterized in that, In the multi-objective function set of the transient / creep parameters, each objective function is constructed based on the sum of squared relative errors between the measured displacement values ​​and the calculated displacement response values ​​of the transient / creep parameters at typical times for different measuring points.

3. The method for progressive optimization and inversion of transient-creep parameters of dam materials according to claim 1, characterized in that, The multi-objective function set of transient / creep parameters Represented as: In the formula, Let j be the objective function. Let be the measured displacement value of measuring point j at time i. Let X be the calculated displacement response value of measuring point j at time i, and let X be the inversion parameter. For the 1st to nth inversion parameters, k represents the number of typical moments.

4. The method for progressive optimization and inversion of transient-creep parameters of dam materials according to claim 1, characterized in that, The nonlinear mapping relationship between the inversion parameters and the deformation response is expressed as follows: In the formula, The values ​​are the finite element calculation values ​​for the dam displacement. For the first One inversion parameter, For the inversion parameter index, a p b p c represents the first, second, and third undetermined coefficients.

5. The method for progressive optimization and inversion of transient-creep parameters of dam materials according to claim 1, characterized in that, The multi-objective function set is inverted and optimized using a multi-objective particle swarm optimization algorithm to determine the inversion parameter solution set.

6. The method for progressive optimization and inversion of transient-creep parameters of dam materials according to claim 1, characterized in that, The statistical bias includes the Z-score determined based on the objectively existing random characteristics of the dam and foundation inversion parameters, and the multi-zone inversion parameters of the dam and foundation. index; The Z-score is represented as: In the formula, These are the inversion parameter values ​​corresponding to the transient / creep changes of the dam body or foundation material in the inversion parameter solution. and The mean and standard deviation of the corresponding creep / transient parameter test and detection data sequences; The indicator is expressed as: In the formula, For the first The inversion parameters are the parameter values ​​in this set of inversion parameter solutions. and For the first The mean and standard deviation of the experimental and detection data sequences of each inversion parameter, where n is the number of inversion parameters.

7. The method for progressive optimization and inversion of transient-creep parameters of dam materials according to claim 3, characterized in that, Inversion accuracy of the inversion parameter solution set Represented as: In the formula, For the 1st to nth inversion parameters, For measuring points The objective function, The number of objective functions.

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