A turbine blade multi-damage coupling life evaluation method and system

Abstract

The present application relates to the technical field of equipment life evaluation, and discloses a turbine blade multi-damage coupling life evaluation method and system, comprising the following steps: obtaining air path boundary parameters to solve and calibrate dynamic aerodynamic thermodynamic boundary conditions; based on the boundary conditions, fluid-solid coupling transient solution is carried out to obtain transient three-dimensional temperature field and stress field distribution data set; according to the data set, the dangerous area is located and the target node is extracted, and the temperature and stress history curve in the complete operation condition cycle is generated; the fatigue damage item, the oxidation damage item and the creep strain accumulation of the target node are calculated respectively; the fatigue and oxidation damage items are added to form a basic cycle damage variable, the creep strain accumulation is used to construct an amplification multiplier, and nonlinear combination product operation is carried out with the basic cycle damage variable, and the total damage coefficient is output. The present application realizes nonlinear algebraic coupling mapping of multiple damage mechanisms, and improves the accuracy of turbine blade life evaluation.

Description

Technical Field

[0001] This invention relates to the field of equipment life assessment technology, specifically to a method and system for assessing the life of turbine blades with multiple damage coupling. Background Technology

[0002] Gas turbine blades operate under harsh environments with high temperatures, high pressures, and complex aerodynamic loads for extended periods. Their failure modes primarily manifest as a combination of creep, fatigue, and oxidation corrosion. The life assessment of turbine blades directly impacts the operational safety of the gas turbine and the economic efficiency of maintenance decisions.

[0003] Current blade life assessment methods largely rely on offline non-destructive testing or empirical formulas, making it difficult to capture dynamic damage accumulation under varying operating conditions in real time. Although some existing assessment schemes combine finite element simulation and computational fluid dynamics for stress and temperature field analysis, the input of simulation boundary conditions often depends on simplified assumptions or interpolation of local measured data, lacking a closed-loop coupling with the overall thermodynamic process of the turbine. This approach leads to a significant deviation between the simulation input boundary and the actual operating conditions of the turbine, reducing the accuracy of blade temperature and stress field calculations. Furthermore, at the damage calculation level, existing life assessment models often use a single creep or fatigue formula for linear superposition, failing to fully consider the physical processes of internal microstructure degradation and surface microcrack propagation evolution in turbine blades under high-temperature environments. They also underscore the complex nonlinear coupling interactions of creep, fatigue, and oxidation, resulting in calculation results that cannot accurately reflect the actual failure physics of turbine blades during high-temperature service, thus limiting further improvements in life prediction accuracy. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for assessing the life of turbine blades with multiple damage coupling. This method solves the problem that traditional turbine blade life assessments suffer from low life prediction accuracy because the simulated boundary conditions deviate from actual operating conditions and fail to accurately reflect the nonlinear coupling effects of fatigue, oxidation, and creep damage.

[0005] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of the present invention provides a method for assessing the coupled lifespan of a turbine blade with multiple damages, comprising:

[0006] Obtain the gas path boundary parameters, and solve the dynamic aerodynamic and thermodynamic boundary conditions at the turbine blade inlet based on the gas path boundary parameters; Based on dynamic aero-thermodynamic boundary conditions, transient fluid-structure interaction solutions are performed to obtain transient three-dimensional temperature field distribution datasets and transient three-dimensional stress field distribution datasets for turbine blades. Based on the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset, the hazardous area is located and the target node is extracted. The temperature history curve and stress history curve of the target node are generated within a complete operating cycle. Based on the temperature history curve and stress history curve, the fatigue damage term, oxidation damage term and creep strain accumulation of the target node are calculated respectively. The fatigue damage term and the oxidative damage term are algebraically added together to form the basic cyclic damage variable; A creep interaction effect term is constructed based on the cumulative creep strain. This creep interaction effect term is then used as an amplification multiplier and nonlinearly combined with the basic cyclic damage variable to perform a product operation, outputting the total damage coefficient. A life assessment is then performed based on the total damage coefficient.

[0007] The turbine blade multi-damage coupled life assessment method of this invention may also have the following additional technical features: In one embodiment of the present invention, the step of obtaining the gas path boundary parameters and solving the dynamic aerodynamic-thermodynamic boundary conditions at the turbine blade inlet based on the gas path boundary parameters includes: Obtain historical operating log data of the gas turbine, calculate the first residual value between the exhaust temperature calculated by the thermodynamic calculation model and the historical measured exhaust temperature, and the second residual value between the power calculated by the model and the historical measured unit power; When the first residual value is greater than or equal to the preset temperature residual threshold, and / or the second residual value is greater than or equal to the preset power residual threshold, the isentropic efficiency coefficients of the compressor module and the turbine module are adjusted to complete the calibration of the thermodynamic calculation model, and the calibrated thermodynamic calculation model is obtained. The gas path boundary parameters of the entire gas turbine are input into the calibrated thermodynamic calculation model to solve for the dynamic aero-thermodynamic boundary conditions.

[0008] In one embodiment of the present invention, the transient solution of fluid-structure interaction based on the dynamic aero-thermodynamic boundary conditions includes: The dynamic aerodynamic thermodynamic boundary conditions are input into the computational fluid dynamics model to calculate and obtain the convective heat transfer coefficient distribution data and adiabatic wall temperature distribution data on the turbine blade surface. The convective heat transfer coefficient distribution data and the adiabatic wall temperature distribution data are mapped and loaded onto the surface shell nodes of the finite element structural model using a spatial interpolation algorithm, and a third type of heat transfer boundary condition is applied. A rotor centrifugal force load is applied to the finite element structural model, the thermo-mechanical coupled finite element control equations are solved, and the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset are output.

[0009] In one embodiment of the present invention, the step of locating the hazardous area and extracting the target node based on the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset, and generating the temperature history curve and stress history curve of the target node over a complete operating cycle, includes: Extract the nodes in the transient three-dimensional temperature field distribution dataset whose maximum temperature value is greater than a preset first temperature threshold and whose maximum temperature gradient value is greater than a preset second temperature threshold, and calculate the spatial intersection as the first type of target nodes; The local curvature radius of the geometric surface is read to extract the geometric transition surface. The intersection of the geometric transition surface and the node whose maximum equivalent Mises stress value in the transient three-dimensional stress field distribution dataset is greater than a preset stress threshold is used as the second type of target node. The first type of target nodes and the second type of target nodes are merged to form a target node set. Scalar values ​​are extracted according to the time series to achieve dimensionality reduction transformation, thereby generating the temperature history curve and the stress history curve.

[0010] In one embodiment of the present invention, the step of calculating the fatigue damage term, oxidation damage term, and creep strain accumulation of the target node based on the temperature history curve and the stress history curve includes: The rainflow counting algorithm is called to strip the closed path of the time domain signal of the stress history curve, extract the local total strain amplitude, and combine it with the preset strain life fatigue equation to solve the reciprocal of the failure cycle number under pure fatigue load as the fatigue damage term. The oxidation rate in the temperature history curve is calculated by time-domain integration using the Arrhenius equation to determine the thickness of the surface oxide layer. The ratio of the surface oxide layer thickness to the critical crack length of the material is then used as the oxidation damage term. During the high-temperature load stage, the transient creep strain rate is calculated based on the real-time stress and real-time temperature, and time integration is performed to obtain the cumulative creep strain.

[0011] In one embodiment of the present invention, constructing a creep interaction term based on the accumulated creep strain includes: Obtain a preset first material constant that reflects the rate of material degradation; The cumulative creep strain is multiplied by the preset first material constant to obtain a product. The number 1 is then algebraically added to the product to generate the creep interaction effect term, which characterizes the accelerated effect of creep void damage on crack propagation.

[0012] In one embodiment of the present invention, the life assessment based on the total damage coefficient includes: The total damage coefficient is compared with the failure threshold set to the number 1; If the total damage coefficient is greater than or equal to 1, the solid structure is determined to have reached the state of macroscopic crack initiation and an interruption control signal is generated. If the total damage coefficient is less than 1, the current cumulative damage scalar is recorded and passed on as the initial damage increment to the next continuous running cycle.

[0013] A second aspect of the present invention provides a multi-damage coupled lifetime assessment system for turbine blades, applied to the multi-damage coupled lifetime assessment method for turbine blades provided in the first aspect above. The system includes: The boundary extraction module is used to obtain the gas path boundary parameters and solve the dynamic aerodynamic and thermodynamic boundary conditions of the turbine blade inlet based on the gas path boundary parameters. The field coupling simulation module is used to perform fluid-structure interaction transient solutions based on the dynamic aero-thermodynamic boundary conditions, and obtain transient three-dimensional temperature field distribution dataset and transient three-dimensional stress field distribution dataset of the turbine blade. The data dimensionality reduction and extraction module is used to locate dangerous areas and extract target nodes based on the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset, and generate the temperature history curve and stress history curve of the target node within a complete operating cycle. The damage coupling and verification module is used to calculate the fatigue damage term, oxidation damage term, and creep strain accumulation of the target node based on the temperature history curve and the stress history curve, respectively. The fatigue damage term and the oxidation damage term are algebraically added together to form the basic cyclic damage variable; A creep interaction effect term is constructed based on the accumulated creep strain. The creep interaction effect term is used as an amplification multiplier and nonlinearly combined with the basic cyclic damage variable to perform a product operation, outputting a total damage coefficient. A life assessment is then performed based on the total damage coefficient.

[0014] This invention provides a method and system for assessing the coupled lifespan of turbine blades due to multiple damages. It offers the following advantages: 1. This invention obtains historical operating data of the gas turbine, calculates the residual value between exhaust temperature and unit power, and adjusts the isentropic efficiency coefficients of the compressor and turbine module accordingly. This achieves closed-loop coupling calibration of the whole-machine thermodynamic calculation model with the computational fluid dynamics and finite element structural model. This technical feature overcomes the initial boundary deviation defect caused by conventional ideal design condition input, making the aerodynamic and thermodynamic boundary conditions of the subsequent fluid-structure interaction transient solution closer to the actual operating conditions of the unit, and improving the calculation accuracy of the transient three-dimensional temperature field and stress field distribution dataset of the turbine blades.

[0015] 2. This invention constructs a basic cyclic damage variable by algebraically adding the fatigue damage term and oxidation damage term of the target node, and uses the creep interaction effect term constructed based on the creep strain accumulation as an amplification multiplier to perform a nonlinear combination product operation with the basic cyclic damage variable. This technical feature constructs a coupled damage model covering multiple mechanisms of creep, fatigue and oxidation, reflecting the acceleration mechanism of internal grain boundary creep voids on the inward propagation rate of surface cracks during the high-temperature bearing stage, thus improving the accuracy of life assessment.

[0016] 3. This invention acquires standard material test data containing actual physical measured values, calculates actual Larssen-Müller parameters, and maps discrete point markers in a two-dimensional coordinate system. Simultaneously, it extracts the actual total strain amplitude under calibration temperature conditions to generate discrete test points. This technical feature utilizes standardized physical spectrum characterization methods in the field of materials testing to judge the absolute numerical deviation between the predicted curves and parameter scalar values ​​solved by the continuous model and the actual physical test discrete data under the same stress or strain benchmark. It performs closed-loop tolerance verification on the fatigue and creep calculation results, providing a physical dimension of verification basis for the output conclusions of the multi-damage coupled life model and improving the overall credibility of the evaluation system. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the system architecture of the present invention; Figure 3 A schematic diagram comparing Larson-Miller parameters for verifying the lifetime model of this invention; Figure 4 Validation of the lifetime model of this invention A diagram showing the curve comparison. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] This invention discloses a method and system for assessing the multi-damage coupled life of turbine blades, which is implemented in electronic devices such as computers, workstations, servers, or distributed cloud computing clusters with high-performance computing capabilities. The hardware of the electronic device includes at least: one or more computing cores such as central processing units (CPUs) and graphics processing units (GPUs) for performing numerical calculations of thermodynamic system cycles, fluid-structure interaction transient matrices, and multi-damage nonlinear coupled equations; non-volatile memory (such as hard disks or solid-state drives) and volatile memory (such as RAM) for persistently storing or temporarily storing gas path boundary parameters, three-dimensional temperature / stress field datasets, one-dimensional history curve arrays, and intermediate variables of damage coefficients; and a system data bus and external communication interface for realizing data transfer between various computing modules or receiving historical operating log data of the entire gas turbine.

[0020] At the software environment level, electronic devices run an operating system and are equipped with data processing and simulation calculation software platforms (including, but not limited to, thermodynamic simulation tools, computational fluid dynamics (CFD) solvers, finite element structural analysis (FEA) software, and mathematical matrix operation programming environments).

[0021] See attached document Figure 1 This invention provides a method for assessing the coupled lifespan of a turbine blade with multiple damages, which may include the following steps: Step 101: Obtain the gas path boundary parameters and solve the dynamic aerodynamic and thermodynamic boundary conditions at the turbine blade inlet based on the gas path boundary parameters. Step 102: Perform fluid-structure interaction transient solution based on dynamic aero-thermodynamic boundary conditions to obtain transient three-dimensional temperature field distribution dataset and transient three-dimensional stress field distribution dataset of turbine blade; Step 103: Locate the hazardous area and extract the target node based on the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset, and generate the temperature history curve and stress history curve of the target node within a complete operating cycle. Step 104: Based on the temperature history curve and stress history curve, calculate the fatigue damage term, oxidation damage term and creep strain accumulation of the target node, respectively. Step 105: Add the fatigue damage term and the oxidative damage term algebraically to form the basic cyclic damage variable; Step 106: Construct a creep interaction effect term based on the cumulative creep strain, use the creep interaction effect term as an amplification multiplier, perform a nonlinear combination product operation with the basic cyclic damage variable, output the total damage coefficient, and perform life assessment based on the total damage coefficient.

[0022] Obtain the gas path boundary parameters of the entire gas turbine, including ambient temperature, ambient pressure, gas turbine speed, fuel mass flow rate, and unit output power.

[0023] The gas path boundary parameters are input into a preset thermodynamic calculation model for solution, and the dynamic aerodynamic thermodynamic boundary conditions at the turbine blade inlet are output. The dynamic aerodynamic thermodynamic boundary conditions include the inlet gas temperature, inlet gas pressure, and gas mass flow rate.

[0024] Obtain historical operating data of the gas turbine. Use this historical operating data to calibrate the parameters of the thermodynamic calculation model.

[0025] Establish computational fluid dynamics and finite element structural models for turbine blades.

[0026] The dynamic aerodynamic thermodynamic boundary conditions are input into the computational fluid dynamics model to calculate and obtain the convective heat transfer coefficient distribution data and adiabatic wall temperature distribution data on the turbine blade surface.

[0027] The convective heat transfer coefficient distribution data and the adiabatic wall temperature distribution data are mapped and loaded into the finite element structural model as thermal boundary conditions, and the rotor centrifugal force load is applied in the finite element structural model.

[0028] By using fluid-structure interaction transient solutions, temperature field distribution data and stress field distribution data of turbine blades in the three-dimensional spatial domain are obtained.

[0029] Based on temperature and stress field distribution data, the critical areas are located within the three-dimensional spatial domain of the turbine blade. These critical areas include the leading edge, exhaust edge, and root radius of the turbine blade.

[0030] Extract dynamic parameter change data of target nodes within a complete operating cycle from hazardous areas.

[0031] Temperature history curves and stress history curves are generated based on dynamic parameter change data.

[0032] The total damage coefficient of the turbine blade is calculated based on the temperature and stress history curves. The total damage coefficient is determined by the creep effect term, fatigue damage term, and oxidation damage term.

[0033] The creep effect term is calculated based on the cumulative creep strain and the first material constant. The fatigue damage term is calculated based on the number of failure cycles under pure fatigue loading. The oxidation damage term is calculated based on the thickness of the oxide layer formed at high temperatures and the critical crack length.

[0034] The steps for obtaining the gas path boundary parameters of the entire gas turbine and outputting the dynamic aerodynamic and thermodynamic boundary conditions at the turbine blade inlet include the specific processes of constructing a thermodynamic calculation model of the entire gas turbine, inputting the gas path boundary parameters for solution, and calibrating the model parameters.

[0035] A thermodynamic calculation model of the entire gas turbine is established. This model includes a compressor module, a combustion chamber module, and a turbine module. Based on the laws of conservation of mass and energy, the data transfer connections between the compressor module, combustion chamber module, and turbine module are constructed.

[0036] Obtain the gas path boundary parameters as input conditions, and construct an input parameter vector based on the gas path boundary parameters. Its formula is expressed as follows: ; In the formula, Indicates ambient temperature; Indicates environmental pressure; Indicates the speed of the gas turbine; Indicates fuel mass flow rate; Indicates the unit's output power; superscript This represents the transpose of a vector.

[0037] input parameter vector Input the thermodynamic calculation model. The thermodynamic calculation model performs a gas path cycle solution. In the compressor module, based on the ambient temperature... Environmental pressure and gas turbine speed Calculate the air temperature and pressure at the compressor outlet. Then transmit the air temperature and pressure from the compressor outlet to the combustion chamber module.

[0038] In the combustion chamber module, combined with fuel mass flow rate The energy balance is calculated based on the preset lower heating value of the fuel to obtain the combustion gas state at the combustion chamber outlet. This combustion gas state at the combustion chamber outlet is then used as the aerodynamic and thermodynamic boundary condition at the turbine blade inlet.

[0039] Extract the aerodynamic and thermodynamic boundary conditions at the turbine blade inlet and construct the output parameter vector. Its formula is expressed as follows: ; In the formula, Indicates the inlet gas temperature; Indicates the inlet gas pressure; This indicates the mass flow rate of the gas.

[0040] In one embodiment of the present invention, historical operating data of the gas turbine can also be used to calibrate the parameters of the thermodynamic calculation model. Specifically, historical operating data of the gas turbine is obtained. This historical operating data includes historical measured exhaust temperature and historical measured unit power. The historical operating data of the gas turbine is used to calibrate the parameters of the thermodynamic calculation model. The input parameter vector is then... Input the thermodynamic calculation model to obtain the calculated exhaust temperature and calculated power.

[0041] The computational model calculates the first residual value between the exhaust temperature and the historical measured exhaust temperature. The computational model calculates the second residual value between the power and the historical measured unit power.

[0042] The system checks whether the first and second residual values ​​are less than preset temperature and power residual thresholds, respectively. If the conditions are not met, the isentropic efficiency coefficients of the compressor module and turbine module are adjusted, and the gas path loop solution is re-executed until the first and second residual values ​​are less than their corresponding thresholds. This completes the model calibration, resulting in a calibrated thermodynamic calculation model. Finally, the calibrated output parameter vector is output from the calibrated thermodynamic calculation model. Then proceed with the fluid-structure interaction simulation process.

[0043] The steps of inputting dynamic aero-thermodynamic boundary conditions into a computational fluid dynamics model to calculate and obtain the convective heat transfer coefficient distribution data and adiabatic wall temperature distribution data on the turbine blade surface include the specific processes of constructing a three-dimensional flow field mesh, assigning boundary conditions, and extracting thermal boundary parameters.

[0044] This involves establishing a fluid domain geometric model for turbine blade hydrodynamic calculations. The fluid domain geometric model is then meshed to generate a fluid domain mesh. A boundary layer mesh is generated in the wall region of the turbine blade to capture the near-wall flow separation and heat transfer characteristics.

[0045] Obtain the turbulence calculation equations from the computational fluid dynamics model. The turbulence calculation equations employ a two-equation turbulence model that incorporates shear stress transport characteristics, used to close the Reynolds-averaged Navier-Stokes equations.

[0046] Obtain the dynamic aerodynamic-thermodynamic boundary conditions output from the aforementioned steps, i.e., the output parameter vector. Extract the output parameter vector. Inlet gas temperature Inlet gas pressure and gas mass flow .

[0047] Inlet gas temperature Set the inlet total temperature boundary condition as a fluid domain mesh. Set the inlet gas pressure... The inlet total pressure boundary condition is set as a fluid domain grid. This is based on the gas mass flow rate. Set the inlet flow boundary conditions for the fluid domain mesh. Set the turbine blade wall as a no-slip fluid physical boundary.

[0048] After setting the boundary conditions, the three-dimensional Reynolds-averaged Navier-Stokes equations and energy conservation equations within the fluid domain are solved to obtain steady-state or transient flow field data around the turbine blades. The flow field data includes the fluid velocity field, pressure field, and gas temperature field.

[0049] Based on flow field data, the adiabatic wall temperature distribution data of the turbine blade surface is extracted. The adiabatic wall temperature is set as the temperature of the fluid immediately adjacent to the wall when the heat flux density at the wall surface is zero.

[0050] Calculate the convective heat transfer coefficient distribution data on the turbine blade surface. Obtain the local wall heat flux density and local wall temperature at the nodes of the turbine blade wall. Establish a convective heat transfer calculation model based on Newton's law of cooling, the formula of which is as follows: ; In the formula, Indicates the local convective heat transfer coefficient; This represents the local wall heat flux density; Indicates the localized insulated wall temperature; This indicates the local wall temperature.

[0051] By traversing all fluid-side mesh nodes on the turbine blade surface, complete convective heat transfer coefficient distribution data are calculated. The adiabatic wall temperature distribution data and convective heat transfer coefficient distribution data are output as thermal boundary parameters for subsequent cross-physics mapping to the finite element structural model.

[0052] The steps of mapping and loading the convective heat transfer coefficient distribution data and the adiabatic wall temperature distribution data as thermal boundary conditions into the finite element structural model, and applying rotor centrifugal force load in the finite element structural model, specifically include the process of finite element model construction, multi-field data spatial mapping, and determination of thermo-mechanical coupling boundary.

[0053] Establish a solid geometric model of the turbine blade. Perform 3D mesh generation on the solid geometric model to generate a structural finite element mesh containing internal nodes and surface shell nodes.

[0054] Obtain the physical parameters of the turbine blade's matrix material. These parameters are nonlinear physical quantities that vary with temperature, including material density, Young's modulus, Poisson's ratio, thermal conductivity, and coefficient of linear expansion. Assign these physical parameters to the structure's finite element mesh.

[0055] Obtain the adiabatic wall temperature distribution data and convective heat transfer coefficient distribution data output from the computational fluid dynamics model. Obtain the node coordinates of the fluid wall mesh in the computational fluid dynamics model. Obtain the node coordinates of the outer shell surface of the structural finite element mesh.

[0056] Using a spatial interpolation algorithm, the adiabatic wall temperature distribution data and the convective heat transfer coefficient distribution data are mapped from the fluid wall grid nodes to the surface shell nodes that match the location.

[0057] A third type of heat transfer boundary condition is applied to the surface shell nodes. The third type of heat transfer boundary condition specifies the convective heat transfer behavior between the blade surface and the external flow field, so that the mapped local convective heat transfer coefficient and local adiabatic wall temperature are used as heat loads input into the finite element calculation domain.

[0058] Obtain the gas turbine speed from the gas path boundary parameters Calculate the rotor angular velocity corresponding to the gas turbine's rotational speed.

[0059] Based on the rotor angular velocity, the radial distance vector of each node in the finite element mesh in the three-dimensional rotating coordinate system, and the material density, the centrifugal force vector acting on each node is calculated. This centrifugal force vector is then applied as a distributed volumetric force load throughout the entire finite element mesh, forming the rotor centrifugal force load.

[0060] Extract the set of contact surface nodes corresponding to the leaf root tenon positions from the finite element mesh of the structure. Apply displacement-fixed boundary conditions to the set of contact surface nodes to restrict the translational degrees of freedom of this region in three orthogonal spatial directions.

[0061] Based on the third type of heat transfer boundary condition, rotor centrifugal force load, and displacement-fixed constraint boundary condition, a thermo-mechanical coupled finite element control equation is constructed for the turbine blade. This equation is used to simultaneously calculate the thermal strain and thermal stress components excited by the local temperature gradient, as well as the mechanical strain and mechanical stress components excited by centrifugal rotation.

[0062] The steps to obtain temperature and stress field distribution data of turbine blades in a three-dimensional spatial domain through fluid-structure interaction transient solution include transient heat conduction calculation and thermo-mechanical coupling mechanical calculation.

[0063] Obtain the complete operating cycle, including turbine blade start-up, shutdown, or load variation processes. Divide the total time of the complete operating cycle into multiple discrete time steps.

[0064] Within each discrete time step, the distribution data of the convective heat transfer coefficient and the distribution data of the adiabatic wall temperature that change dynamically with time are extracted, and the thermal boundary conditions of the turbine blade surface shell nodes are updated.

[0065] Based on the updated thermal boundary conditions, the three-dimensional transient heat conduction equation of the finite element structural model is solved. The formula for the three-dimensional transient heat conduction equation is as follows: ; In the formula, This indicates the density of the matrix material of the turbine blade; This indicates the specific heat capacity of the matrix material of the turbine blade; This represents the three-dimensional temperature of the turbine blade. Indicates runtime; Represents the Hamiltonian operator; This indicates the thermal conductivity of the matrix material of the turbine blade.

[0066] By solving the three-dimensional transient heat conduction equation, the temperature values ​​of the internal nodes and the outer shell nodes of the turbine blade at the current discrete time step are obtained, thus forming the temperature field distribution data at the current moment.

[0067] Calculate the thermal strain load based on the current temperature field distribution data. Calculate the thermal strain tensor at each node, expressed by the following formula: ; In the formula, Represents the thermal strain tensor; This represents the coefficient of linear expansion of the turbine blade matrix material; This indicates the reference temperature under no thermal stress conditions. This represents a second-order unit tensor.

[0068] By incorporating the thermal strain tensor into the solid mechanics equilibrium equations of the finite element structural model, and combining this with the rotor centrifugal force load applied in the preceding steps, a coupled constitutive equation incorporating both thermal and mechanical loads is established. The formula for the coupled constitutive equation is as follows: ; In the formula, The three-dimensional stress tensor of a turbine blade; This represents the elastic stiffness tensor of the turbine blade matrix material. This represents the total strain tensor.

[0069] Solve the geometric equations that satisfy the conditions for spatial nodal displacement compatibility and mechanical equilibrium, and calculate the displacement vectors of each node of the turbine blade.

[0070] Based on the displacement vector and the coupled constitutive equation, the stress values ​​of the internal nodes and the outer shell nodes of the turbine blade at the current discrete time step are calculated, forming the stress field distribution data at the current moment. The stress field distribution data includes the first principal stress distribution, the equivalent Mises stress distribution, and multiaxial stress components.

[0071] The system iterates through all discrete time steps in chronological order, storing the temperature and stress field distribution data obtained at each step. This data is then compiled to generate transient three-dimensional temperature and stress field distribution datasets for the turbine blade in the three-dimensional spatial domain.

[0072] Based on temperature and stress field distribution data, the process involves locating hazardous areas within the three-dimensional spatial domain of the turbine blade, extracting dynamic parameter change data of the target node within a complete operating cycle from the hazardous areas, and generating temperature and stress history curves based on the dynamic parameter change data. This process includes steps such as local extreme value search, hazardous area delineation, and time series data extraction.

[0073] Obtain the transient three-dimensional temperature field distribution dataset and transient three-dimensional stress field distribution dataset generated in the preceding steps. Obtain the complete operating cycle time axis containing each discrete time step of the turbine blade.

[0074] Calculate the maximum temperature value and maximum temperature gradient value of each spatial node in the transient 3D temperature field distribution dataset along the entire time axis. Extract nodes whose maximum temperature value is greater than a preset first temperature threshold and nodes whose maximum temperature gradient value is greater than a preset second temperature threshold, and calculate the spatial intersection set of the two.

[0075] The physical locations of the spatial intersection set are mapped to the 3D solid model of the turbine blade, and labeled as the leading edge region and the exhaust edge region of the turbine blade. Within the leading edge region and the exhaust edge region of the turbine blade, all nodes are traversed, and the nodes with the highest local temperature values ​​are extracted as the first type of target nodes. The first type of target nodes are used to characterize the locations with the most severe thermal fatigue and oxidation damage.

[0076] Calculate the maximum equivalent Mises stress value for each spatial node in the transient 3D stress field distribution dataset over the entire time axis. Extract the set of nodes whose maximum equivalent Mises stress value is greater than a preset stress threshold.

[0077] Read the geometric topology information of the finite element structural model and calculate the local radius of curvature of each surface. Extract the geometric surfaces with a local radius of curvature smaller than a preset curvature threshold and mark them as geometric transition surfaces.

[0078] The spatial intersection of the set of nodes whose maximum equivalent Mises stress value exceeds a preset stress threshold and the set of nodes corresponding to the geometric transition surface is calculated. The physical location corresponding to this spatial intersection is marked as the blade root transition fillet region. Within the blade root transition fillet region, the nodes corresponding to the maximum equivalent Mises stress value are extracted as second-type target nodes. These second-type target nodes are used to characterize the location of the most severe mechanical fatigue and stress concentration.

[0079] The first type of target nodes and the second type of target nodes are merged to establish a target node set for dimensionality reduction analysis.

[0080] For each target node in the target node set, traverse all discrete time steps on the time axis of the complete operating cycle in chronological order.

[0081] At each discrete time step, the discrete temperature scalar value of the corresponding target node is read from the transient three-dimensional temperature field distribution dataset, and all the discrete temperature scalar values ​​are arranged in time series to generate a one-dimensional array of node temperatures.

[0082] At each discrete time step, the discrete equivalent Mises stress scalar value or the first principal stress scalar value of the corresponding target node is read from the transient three-dimensional stress field distribution dataset. All discrete stress scalar values ​​are arranged in time series to generate a one-dimensional array of nodal stresses.

[0083] Using runtime as the x-axis and the values ​​in the one-dimensional array of node temperatures as the y-axis, a temperature history curve for the target node over a complete operating cycle is generated. This temperature history curve function is denoted as... ,in Indicates the runtime.

[0084] Using runtime as the x-axis and the values ​​in the one-dimensional array of nodal stresses as the y-axis, a stress history curve for the target node over a complete operating cycle is generated. This stress history curve function is denoted as... .

[0085] By extracting the temporal state values ​​of specific spatial coordinate points, the dimensionality reduction transformation from four-dimensional spatiotemporal field data to two-dimensional history curve data is completed, and the temperature history curve is output. and stress history curve At most damage coupling calculation model.

[0086] The process of calculating the total damage coefficient of a turbine blade based on temperature history curves and stress history curves includes steps such as fatigue damage base extraction, quantification of microscopic oxidation damage, creep interaction multiplier calculation, and nonlinear multi-mechanism coupling solution.

[0087] Obtain the stress history curve of the target node over a complete operating cycle. Temperature history curve .

[0088] Calculate fatigue damage terms. Use the rainflow counting algorithm to analyze the stress history curve. Closed-path stripping of the time-domain signal is performed to extract the stress amplitude and mean stress of independent cycles. Using a local strain approximation algorithm, the stress amplitude is converted into a local total strain amplitude. The mean nodal temperature within the corresponding time period of each independent cycle is extracted, and the fatigue elastic and plastic influence coefficients at the corresponding temperature are retrieved from a material property database. The local total strain amplitude is input into a preset strain-life fatigue equation to solve for the failure cycle number at the critical point under pure fatigue loading. The fatigue damage term, which characterizes the damage accumulation rate caused by alternating mechanical loads, is calculated and its mathematical expression is: .

[0089] Calculate the oxidation damage term. Read the temperature history curve. This study aims to obtain the dynamic process of solid oxidation evolution on the surface of turbine blades under high-temperature conditions. An integral function varying with transient temperature is constructed using the Arrhenius equation. The oxidation rate is then integrated over the entire operating cycle in the time domain to calculate the current oxide layer thickness on the surface. Retrieve the critical crack length for curing from the initial physical properties of the matrix material in the system database. The oxidation damage term used to quantify the reduction in effective cross-section caused by high-temperature oxidation erosion is calculated, and its mathematical expression is as follows: .

[0090] Calculate the creep interaction term. Traverse the stress history curve. Temperature history curve During the high-temperature load-bearing phase, the transient creep strain rate is calculated based on real-time stress and temperature. Time integration is then performed during the load-bearing period of the complete operating cycle to obtain the cumulative microscopic creep strain within a single operating cycle. Obtain a preset first material constant that reflects the rate of material degradation. A nonlinear creep interaction term is constructed using algebraic operations to characterize the accelerating effect of creep void damage on crack propagation. Its mathematical expression is as follows: .

[0091] A multi-damage nonlinear coupling calculation equation is constructed. The fatigue damage term and the oxidation damage term are algebraically added to form the basic cyclic damage variable; the creep interaction term is used as an amplification multiplier and nonlinearly combined with the basic cyclic damage variable for product operation. The formula for the multi-damage nonlinear coupling calculation equation is expressed as follows: ; In the formula, This represents the total damage coefficient of the corresponding target node; This represents the cumulative creep strain within a single cycle; Represents the first material constant; This indicates the failure cycle number under pure fatigue loading. Indicates the thickness of the generated oxide layer; This indicates the critical crack length of the material.

[0092] The total damage coefficient is calculated based on the multi-damage nonlinear coupling calculation equation. The total damage coefficient The comparison is made with the solidification failure threshold, which is set to the number 1. If the total damage coefficient... If the value is greater than or equal to 1, it indicates that the turbine blade's lifespan has been exhausted. Therefore, the physical structure at the target node is determined to have reached the state of macroscopic crack initiation. The system generates an interrupt control signal characterizing material failure and outputs it to the external hardware terminal. If the total damage coefficient is... If the value is less than 1, it means that the turbine blade still has remaining lifespan. In this case, the current cumulative damage scalar value is recorded and used as the initial damage increment to be passed to the life assessment process of the next continuous operating cycle.

[0093] See attached document Figure 3 The process involves obtaining discrete Larsson-Müller parameters of the turbine blade, generating a curve showing the relationship between Larsson-Müller parameters and stress, comparing the curve with the physical test data of the first standard material, and verifying the creep calculation results in the total damage coefficient. Specifically, this includes the steps of mapping physical test data, calculating model prediction data, and verifying and comparing deviations.

[0094] Obtain the physical test data of the first standard material. The physical test data of the first standard material includes the physical measured values ​​of the actual creep fracture time of the turbine blade matrix material under multiple discrete constant stress load levels and a set constant high temperature environment.

[0095] Based on the physically measured values ​​of actual creep rupture time, the temperature scalar value under constant high temperature conditions, and the pre-obtained second constant of the matrix material, the actual Larssen-Müller parameter scalar values ​​for each constant stress load level are calculated. The calculation logic for the actual Larssen-Müller parameter scalar values ​​is the product of the temperature scalar value and the sum of the logarithmized physically measured values ​​of actual creep rupture time and the second constant.

[0096] The test data coordinate points are constructed by mapping each constant stress load level to the corresponding actual Larssen-Müller parameter scalar values. In such cases... Figure 3 In the two-dimensional coordinate system shown, the horizontal axis is configured as the numerical axis representing the Larssen-Müller parameters, and the vertical axis is configured as the numerical axis representing the stress scalar values, with the unit set to megapascals. The set of experimental data coordinate points is mapped to Type I discrete point identifiers in the two-dimensional coordinate system, corresponding to... Figure 3 The test discrete points are represented by circles.

[0097] Obtain simulation boundary condition parameters consistent with the first standard material physics test data. Input the same constant stress load level and constant high temperature environment parameters into the aforementioned constructed multi-damage coupling calculation equation. Extract the computational logic module related to the creep effect term in the multi-damage coupling calculation equation, and calculate the predicted creep fracture time of the turbine blade matrix material under the corresponding stress and temperature conditions.

[0098] Based on the predicted creep rupture time, the temperature scalar value of the constant high-temperature environment, and the second constant, the same Larsen-Müller parameter calculation logic is executed to calculate the Larsen-Müller parameter scalar value of the model.

[0099] The set of coordinate points for model calculation is constructed by relating each constant stress load level to the corresponding Larsen-Müller parameter scalar values ​​calculated by the model. In such cases... Figure 3 In the same two-dimensional coordinate system shown, the set of coordinate points calculated by the model is mapped to the second type of discrete point identifiers, corresponding to Figure 3 The model's discrete points are represented by squares.

[0100] By mapping coordinate points, a spectrum of the relationship between Larssen-Müller parameters and stress, containing first-type and second-type discrete point identifiers, is generated in a two-dimensional coordinate system.

[0101] Extract the same stress scalar value along the vertical axis as a reference, and read the corresponding actual Larssen-Müller parameter scalar values ​​and the model-calculated Larssen-Müller parameter scalar values ​​respectively. Calculate the absolute numerical deviation between the two values ​​under the same stress scalar value reference.

[0102] Determine whether all absolute numerical deviations obtained under various set constant stress load levels are within the preset creep tolerance range. When it is determined that all absolute numerical deviations fall within the preset creep tolerance range, confirm that the second type of discrete point markers and the first type of discrete point markers achieve a physical correspondence in the two-dimensional coordinate system.

[0103] Based on the corresponding results, the model parameters used to calculate the cumulative creep strain in the multi-damage coupling calculation equation were verified. The output signal characterizing the creep model calculation results objectively reflects the physical evolution law of the material under high-temperature loading, confirming the verification pass.

[0104] See attached document Figure 4 The process involves obtaining the total strain amplitude and fatigue life cycle number of the turbine blade, generating a strain-life relationship curve, and comparing the strain-life relationship curve with the physical test data of the second standard material under a preset temperature condition to verify the fatigue calculation results in the total damage coefficient. Specifically, this includes the steps of reading physical test data, solving fatigue model parameters, and verifying the overlap of distribution trends.

[0105] Obtain the second standard material physics test data. This data includes actual failure test results of the turbine blade matrix material under low-cycle fatigue alternating strain loading. Extract the test subset corresponding to the preset temperature conditions from the second standard material physics test data. The preset temperature conditions include a first calibration temperature condition and a second calibration temperature condition. Specifically, the first calibration temperature condition is 650℃, and the second calibration temperature condition is 800℃.

[0106] Under various set calibrated temperature conditions, the actual total strain amplitude scalar value applied to the physical test sample and the actual fatigue life cycle value recorded in the test are extracted.

[0107] Establish a two-dimensional rectangular coordinate system. Configure the horizontal axis of the two-dimensional rectangular coordinate system as a numerical axis representing the number of fatigue life cycles, and set the scale distribution of this horizontal axis to a logarithmic coordinate scale. Configure the vertical axis of the two-dimensional rectangular coordinate system as a numerical axis representing the total strain amplitude.

[0108] The actual total strain amplitude scalar value under the 650℃ condition and the corresponding actual fatigue life cycle value are combined to form a first set of coordinate points, which are then mapped to a two-dimensional rectangular coordinate system to generate the first type of discrete test points. The actual total strain amplitude scalar value under the 800℃ condition and the corresponding actual fatigue life cycle value are combined to form a second set of coordinate points, which are then mapped to a two-dimensional rectangular coordinate system to generate the second type of discrete test points.

[0109] Obtain simulation input boundary conditions consistent with those of the physical test samples. Input the same scalar values ​​of the calibration temperature condition and the continuously varying theoretical total strain amplitude into the previously constructed multi-damage coupled calculation equation. Call the internal strain-life equation module in the multi-damage coupled calculation equation used to calculate the fatigue damage term.

[0110] The module for solving the internal strain life equation obtains the fatigue life cycle values ​​calculated by the continuous model at an input temperature of 650℃. Based on the theoretical total strain amplitude and the corresponding fatigue life cycle values ​​calculated by the continuous model, a first model prediction curve is constructed. The module for solving the internal strain life equation again obtains the fatigue life cycle values ​​calculated by the continuous model at an input temperature of 800℃, and a second model prediction curve is constructed.

[0111] The prediction curves of the first model and the second model are mapped to the same two-dimensional rectangular coordinate system containing discrete points of the first and second types of experiments.

[0112] Multiple reference total strain amplitude scalar values ​​are extracted along the vertical axis of a two-dimensional rectangular coordinate system. Under the same reference total strain amplitude scalar value, the first distance deviation value between the horizontal axis value of the discrete points in the first type of test and the horizontal axis value of the corresponding position of the predicted curve of the first model is calculated. Similarly, under the same reference total strain amplitude scalar value, the second distance deviation value between the horizontal axis value of the discrete points in the second type of test and the horizontal axis value of the corresponding position of the predicted curve of the second model is calculated.

[0113] Determine whether all extracted first distance deviation values ​​and second distance deviation values ​​are less than a preset fatigue life tolerance threshold. When it is determined that all distance deviation values ​​are less than the fatigue life tolerance threshold, confirm that the geometric distribution characteristics of the first model prediction curve coincide with the discrete points of the first type of test, and that the geometric distribution characteristics of the second model prediction curve coincide with the discrete points of the second type of test.

[0114] Based on the overlap determination results, the computational parameters used to obtain the failure cycle number under pure fatigue load in the multi-damage coupling calculation equation were verified. A verification signal command was output to confirm that the fatigue model prediction calculation module accurately reflects the high-temperature alternating mechanical degradation characteristics of the material.

[0115] See attached document Figure 2 This invention provides a multi-damage coupled life assessment system for turbine blades, which may include: a boundary extraction module, a field coupling simulation module, a data dimensionality reduction extraction module, and a damage coupling and verification module. The modules communicate and transmit data with each other via a system data bus. The damage coupling and verification module is internally equipped with a dedicated multi-mechanism product matrix operator for performing creep fatigue oxidation nonlinear co-degradation.

[0116] The boundary extraction module is equipped with an external data receiving interface to acquire the gas path boundary parameters and historical operation log data of the entire gas turbine. Internally, the boundary extraction module integrates a thermodynamic calculation model program, which includes interconnected compressor sub-models, combustion chamber sub-models, and turbine sub-models. The boundary extraction module runs the thermodynamic calculation model program to perform gas path cycle solving calculations, generating dynamic aerodynamic and thermodynamic boundary conditions at the turbine blade inlet. The parameter calibration unit then iteratively converges and calibrates the model residuals based on historical operation log data before outputting the results to the next-level module.

[0117] The field-coupled simulation module communicates with the boundary extraction module to receive calibrated dynamic aerodynamic-thermodynamic boundary conditions. Internally, the field-coupled simulation module constructs both a fluid dynamics computational domain and a solid structure finite element computational domain. The module activates its built-in computational fluid dynamics solver to extract convective heat transfer coefficient distribution data and adiabatic wall temperature distribution data from the turbine blade surface; it then calls a spatial interpolation algorithm function to map the extracted heat flow boundary data onto the shell nodes of the solid structure finite element computational domain. The module further activates its built-in finite element structural solver, superimposing centrifugal volumetric force loads calculated based on the rotor angular velocity, and solves the matrix equations through transient coupling to generate and store transient three-dimensional temperature field distribution datasets and transient three-dimensional stress field distribution datasets of the turbine blade in the three-dimensional spatial domain.

[0118] The data dimensionality reduction and extraction module communicates with the field coupling simulation module to read the generated multidimensional field distribution dataset. Through its internal threshold judgment logic unit and geometric topology retrieval unit, the data dimensionality reduction and extraction module locates dangerous areas such as the leading edge, exhaust edge, and blade root transition fillet of the turbine blade in the three-dimensional spatial domain, and extracts target nodes that satisfy local extremum conditions. For each selected target node, the temperature scalar value and stress scalar value at discrete time steps are extracted sequentially according to the time axis of the complete operating cycle, and converted into two-dimensional time series temperature history curves and stress history curves for output.

[0119] The damage coupling and verification module communicates with the data dimensionality reduction and extraction module to receive the dimensionality-reduced history curve data and perform material degradation logic operations. The damage coupling and verification module includes independent fatigue loss analysis units, high-temperature oxidation calculation units, micro-creep accumulation units, cooperative product coupling units, and verification and comparison sub-modules.

[0120] The fatigue loss analysis unit is equipped with a rainflow counter and a strain conversion controller. The rainflow counter extracts discrete stress cycles within a complete operating cycle. The strain conversion controller utilizes the nonlinear constitutive parameters of the material as a function of temperature to convert the stress of each cycle into an equivalent local total strain amplitude, and calls the system's built-in strain life equation to solve for the pure fatigue failure life cycles, outputting a fatigue damage term characterizing the mechanical alternating physical damage substrate.

[0121] The high-temperature oxidation calculation unit is equipped with a time integrator and a section reduction evaluator. The time integrator calls the built-in Arrhenius rate function to perform time-domain cumulative integration on the dynamic high-temperature environment in the history curve, and outputs the real-time generated oxide layer thickness. The section reduction evaluator retrieves the critical crack length parameter of curing, calculates the ratio of the oxide layer thickness to the critical crack length, and outputs an oxidation damage term characterizing physical erosion damage.

[0122] The micro-creep accumulation unit comprises a time-series load-holding segmenter and a strain rate integrator. The time-series load-holding segmenter identifies long-term high-temperature load periods. The strain rate integrator calculates the transient creep strain rate based on real-time stress and real-time temperature and performs time integration to obtain the cumulative creep strain within a single operating cycle. This cumulative creep strain is then combined with a pre-stored first material constant and constructed using an algebraic summation algorithm to output the creep interaction term.

[0123] The input terminals of the collaborative product coupling unit are connected to the output terminals of the fatigue loss analysis unit, the high-temperature oxidation calculation unit, and the micro-creep accumulation unit, respectively. The collaborative product coupling unit internally contains two cascaded operational bus circuits. The first-stage adder circuit algebraically sums the fatigue damage term and the oxidation damage term to establish the cyclic total damage base. The second-stage multiplier circuit uses the creep interaction effect term output from the micro-creep accumulation unit as a multiplier and performs a nonlinear product operation with the cyclic total damage base to generate the overall physical damage coefficient of the target node. The output terminal of the collaborative product coupling unit is connected to a logic threshold comparator, which performs a threshold logic judgment between the overall physical damage coefficient and the internally stored number 1. If the overall physical damage coefficient is greater than or equal to 1, an interrupt control signal representing blade structural failure is generated and output to the external hardware terminal; if it is less than 1, the coefficient is written to non-volatile memory for subsequent accumulation cycle calls.

[0124] The verification and comparison submodule connects to an external database, reads standard material physical test data, and calculates the geometric distance deviation between the model-predicted feature points and the test points by constructing the Larsen-Müller parameter curve coordinate system and the double logarithmic strain-life coordinate system. When the geometric distance deviation is within the set tolerance range, it outputs a judgment signal that the evaluation system model has passed physical verification.

Claims

1. A method for assessing the coupled lifespan of a turbine blade due to multiple damages, characterized in that, Includes the following steps: Obtain the gas path boundary parameters, and solve the dynamic aerodynamic and thermodynamic boundary conditions at the turbine blade inlet based on the gas path boundary parameters; Based on the dynamic aero-thermodynamic boundary conditions, a fluid-structure interaction transient solution is performed to obtain a transient three-dimensional temperature field distribution dataset and a transient three-dimensional stress field distribution dataset for the turbine blade. Based on the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset, the hazardous area is located and the target node is extracted, and the temperature history curve and stress history curve of the target node are generated within a complete operating cycle. Based on the temperature history curve and the stress history curve, the fatigue damage term, oxidation damage term and creep strain accumulation of the target node are calculated respectively. The fatigue damage term and the oxidation damage term are algebraically added together to form the basic cyclic damage variable; A creep interaction effect term is constructed based on the accumulated creep strain. The creep interaction effect term is used as an amplification multiplier and nonlinearly combined with the basic cyclic damage variable to perform a product operation, outputting a total damage coefficient. A life assessment is then performed based on the total damage coefficient.

2. The method for assessing the coupled lifespan of a turbine blade according to claim 1, characterized in that, The process of acquiring gas path boundary parameters and solving for the dynamic aerodynamic-thermodynamic boundary conditions at the turbine blade inlet based on these parameters includes: Obtain historical operating log data of the gas turbine, calculate the first residual value between the exhaust temperature calculated by the thermodynamic calculation model and the historical measured exhaust temperature, and the second residual value between the power calculated by the model and the historical measured unit power; When the first residual value is greater than or equal to the preset temperature residual threshold, and / or the second residual value is greater than or equal to the preset power residual threshold, the isentropic efficiency coefficients of the compressor module and the turbine module are adjusted to complete the calibration of the thermodynamic calculation model, and the calibrated thermodynamic calculation model is obtained. The gas path boundary parameters of the entire gas turbine are input into the calibrated thermodynamic calculation model to solve for the dynamic aero-thermodynamic boundary conditions.

3. The method for assessing the coupled lifespan of a turbine blade according to claim 1, characterized in that, The transient solution of fluid-structure interaction based on the dynamic aero-thermodynamic boundary conditions includes: The dynamic aerodynamic thermodynamic boundary conditions are input into the computational fluid dynamics model to calculate and obtain the convective heat transfer coefficient distribution data and adiabatic wall temperature distribution data on the turbine blade surface. The convective heat transfer coefficient distribution data and the adiabatic wall temperature distribution data are mapped and loaded onto the surface shell nodes of the finite element structural model using a spatial interpolation algorithm, and a third type of heat transfer boundary condition is applied. A rotor centrifugal force load is applied to the finite element structural model, the thermo-mechanical coupled finite element control equations are solved, and the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset are output.

4. The method for assessing the coupled lifespan of a turbine blade under multiple damages as described in claim 1, characterized in that, The step of locating hazardous areas and extracting target nodes based on the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset, and generating temperature history curves and stress history curves of the target nodes over a complete operating cycle, includes: Extract the nodes in the transient three-dimensional temperature field distribution dataset whose maximum temperature value is greater than a preset first temperature threshold and whose maximum temperature gradient value is greater than a preset second temperature threshold, and calculate the spatial intersection as the first type of target nodes; The local curvature radius of the geometric surface is read to extract the geometric transition surface. The intersection of the geometric transition surface and the node whose maximum equivalent Mises stress value in the transient three-dimensional stress field distribution dataset is greater than a preset stress threshold is used as the second type of target node. The first type of target nodes and the second type of target nodes are merged to form a target node set. Scalar values ​​are extracted according to the time series to achieve dimensionality reduction transformation, thereby generating the temperature history curve and the stress history curve.

5. The method for assessing the coupled lifespan of a turbine blade according to claim 1, characterized in that, The calculation of the fatigue damage term, oxidation damage term, and creep strain accumulation of the target node based on the temperature history curve and the stress history curve includes: The rainflow counting algorithm is called to strip the closed path of the time domain signal of the stress history curve, extract the local total strain amplitude, and combine it with the preset strain life fatigue equation to solve the reciprocal of the failure cycle number under pure fatigue load as the fatigue damage term. The oxidation rate in the temperature history curve is calculated by time-domain integration using the Arrhenius equation to determine the thickness of the surface oxide layer. The ratio of the surface oxide layer thickness to the critical crack length of the material is then used as the oxidation damage term. During the high-temperature load stage, the transient creep strain rate is calculated based on the real-time stress and real-time temperature, and time integration is performed to obtain the cumulative creep strain.

6. The method for assessing the coupled lifespan of a turbine blade according to claim 1, characterized in that, The step of constructing a creep interaction effect term based on the accumulated creep strain includes: Obtain a preset first material constant that reflects the rate of material degradation; The cumulative creep strain is multiplied by the preset first material constant to obtain a product. The number 1 is then algebraically added to the product to generate the creep interaction effect term, which characterizes the accelerated effect of creep void damage on crack propagation.

7. The method for assessing the coupled lifespan of a turbine blade according to claim 1, characterized in that, The life assessment based on the total damage coefficient includes: The total damage coefficient is compared with the failure threshold set to the number 1; If the total damage coefficient is greater than or equal to 1, the solid structure is determined to have reached the state of macroscopic crack initiation and an interruption control signal is generated. If the total damage coefficient is less than 1, the current cumulative damage scalar is recorded and passed on as the initial damage increment to the next continuous running cycle.

8. A multi-damage coupled life assessment system for turbine blades, characterized in that, The method for assessing the multi-damage coupled life of a turbine blade as described in any one of claims 1-7 includes: The boundary extraction module is used to obtain the gas path boundary parameters and solve the dynamic aerodynamic and thermodynamic boundary conditions of the turbine blade inlet based on the gas path boundary parameters. The field coupling simulation module is used to perform fluid-structure interaction transient solutions based on the dynamic aero-thermodynamic boundary conditions, and obtain transient three-dimensional temperature field distribution dataset and transient three-dimensional stress field distribution dataset of the turbine blade. The data dimensionality reduction and extraction module is used to locate dangerous areas and extract target nodes based on the transient three-dimensional temperature field distribution dataset and the transient three-dimensional stress field distribution dataset, and generate the temperature history curve and stress history curve of the target node within a complete operating cycle. The damage coupling and verification module is used to calculate the fatigue damage term, oxidation damage term, and creep strain accumulation of the target node based on the temperature history curve and the stress history curve, respectively. The fatigue damage term and the oxidation damage term are algebraically added together to form the basic cyclic damage variable; A creep interaction effect term is constructed based on the accumulated creep strain. The creep interaction effect term is used as an amplification multiplier and nonlinearly combined with the basic cyclic damage variable to perform a product operation, outputting a total damage coefficient. A life assessment is then performed based on the total damage coefficient.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-7.

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