211 results about "Stress intensity factor" patented technology

The invention relates to the technical field of ocean engineering and mechanical engineering, in particular to a method and a device for analyzing crack propagation of a fan blade considering a real ocean environment. According to the method, the real marine environment working condition is considered, dynamic simulation analysis is conducted on the fan blade, distribution information of loads borne by the fan blade is determined and loaded on a finite element model of the fan blade, a fatigue hot spot area is determined according to a finite element fatigue damage analysis result, and crack arrangement is conducted. And calculating a stress intensity factor of a crack tip and performing crack propagation simulation according to a finite element analogue simulation result so as to evaluate the fracture damage risk of the fan blade in a real marine environment. The wind turbine blade crack propagation analysis thought under the complex stress condition is provided, equipment faults and risks caused by blade breakage can be prevented, a scientific basis is provided for overhaul and operation and maintenance of a wind turbine, and therefore economic losses caused by failure of the wind turbine blade are reduced.

The invention discloses an engine additive component service life prediction method based on modal polycondensation and expansion, and the method specifically comprises the steps: firstly, achieving the grid discretization of an initial defect structure based on a finite element method, and carrying out the local refinement of a defect region; performing modal polycondensation on the overall model to obtain a low-dimensional system model, and performing rapid calculation under the low-dimensional model to obtain modal response; establishing a conversion relation between a displacement vibration mode and a stress vibration mode, and obtaining full-field stress by utilizing modal response and based on modal extension; and solving a stress intensity factor-time history of the crack tip by adopting a stress extrapolation method, obtaining a delta K-R-n three-variable rain flow matrix by utilizing a rain flow counting method, and finally carrying out residual life evaluation through an iLAPS model. According to the method, system dynamics, fracture mechanics and modal order reduction technologies are fused, a new efficient and accurate fatigue life prediction path adapting to complex working conditions is provided for additive manufacturing components with defects, and the method has remarkable engineering application value and popularization potential.

The invention provides a metal material surface microcrack positioning method. The method comprises the following steps: applying a torsional load to a numerical model, calculating stress-strain distribution in a material, describing a crystal deformation behavior by adopting a crystal plasticity constitutive equation, and obtaining dislocation density distribution and a slip system activation condition in each crystal grain; according to the dislocation density distribution and the slip system activation condition, the position where microcracks are easy to form in the material is judged, and when the dislocation density exceeds a preset critical value and multiple activation slip systems exist, the position is determined to be the position where the microcracks are easy to form; according to the fracture mechanical parameters and the fracture toughness of the material, whether the microcracks are expanded or not is judged, when the stress intensity factor exceeds the fracture toughness, it is determined that the microcracks are expanded, and the crack expansion path is determined by calculating the direction of the maximum release rate.

The invention provides a cable bending fatigue life prediction method and system based on reinforcement learning, and relates to the technical field of cable life prediction, and the method comprises the steps: collecting cable test sample data, calculating a stress distribution field and a strain distribution field, constructing a stress intensity factor calculation module, and calculating a crack propagation track and rate. A damage evolution tensor is constructed as a state feature, a network is trained based on a deep Q learning algorithm, uncertainty is quantified by adopting a Markov chain Monte Carlo method, and a credible interval and an early warning threshold are established.

The invention discloses a fatigue crack propagation analysis method of a rocket engine turbine blade. The method comprises the following steps: establishing a fatigue crack propagation model of the rocket engine turbine blade; determining high-low cycle fatigue load and input through the working condition load; the fatigue crack propagation calculation of the turbine blade is carried out in combination with ABAQUS and FRANC3D; fatigue fracture parameters such as stress intensity factors and J integral are output, and the critical crack size of the turbine blade is determined; and according to a fatigue crack propagation model, performing high-low cycle fatigue life prediction on the rocket engine turbine blade. Compared with existing fatigue crack propagation analysis, the method has the advantages that working condition loads in the whole cycle process of starting, stopping, stable operation and overload of the rocket engine turbine blade are considered, and calculation of the high-low cycle composite fatigue problem of the rocket engine turbine blade is achieved; and the fatigue crack propagation life and the critical crack length of the rocket engine turbine blade under the real working condition can be more accurately predicted.

The invention belongs to the technical field of computer-aided manufacturing, and relates to a method and system for predicting the propagation rate of fatigue cracks across welding zones in electric arc additive remanufacturing, and the method comprises the following steps: S1, manufacturing a sample; s2, performing in-situ SEM fatigue test on the sample; s3, obtaining a corresponding relation between the crack growth rate and the stress intensity factor range of the sample; s4, fitting to obtain a fatigue crack propagation rate model of the sample; s5, establishing a CZH sample fatigue crack growth rate prediction model; and S6, predicting the fatigue crack propagation rate of the sample across the welding zone. The system further comprises an electric hydraulic fatigue test system, a data acquisition module, a database, a fitting module and a prediction module. According to the method, by using the correction coefficient, the fatigue crack growth rate is predicted by using the fatigue crack growth rate parameter of the matrix material area.

The invention discloses an in-situ characterization method for fracture toughness of a high-temperature interface of a thermal barrier coating, which comprises the following steps: taking a metal test piece with the thermal barrier coating as a sample to be tested, spraying NiAl on the surface of a ceramic layer in the thermal barrier coating to serve as a buffer layer, then spraying a reinforcing layer, and forming a mixed reinforcing layer with the buffer layer; a three-point bending experiment is carried out on a to-be-tested sample at 1000-1400 DEG C by using a three-point bending device with a digital image correlation method in-situ observation function, and the three-point bending process is recorded in real time. A strain cloud picture of an observation area is obtained through a digital image correlation method, parameters are obtained from the strain cloud picture, and the interface critical energy release rate and the stress intensity factor of a three-point bending experiment are calculated and are both in direct proportion to the high-temperature interface fracture toughness of the thermal barrier coating. Therefore, in-situ characterization of the interface fracture toughness of the thermal barrier coating can be realized in a high-temperature environment of real service of the thermal barrier coating, test data can be accurately acquired in real time, and the test period is short.

The invention discloses a method and device for predicting the fatigue life of a high-temperature alloy vacuum electron beam welding structure, and belongs to the technical field of aero-engines. The method comprises the following steps: acquiring fatigue experiment data of a target high-temperature alloy standard sample; extracting the maximum area of an initial defect, a defect shape factor and crack source position information; obtaining a stress intensity factor range considering defect morphological characteristics and a fatigue crack propagation threshold value of a material structure containing initial defects, and correcting a damage tolerance theoretical formula to obtain simulation data; fatigue test data and simulation data are fused to form an initial data set, a fatigue limit is calculated and expanded to the data set, the expanded data set serves as input, training is conducted through a support vector regression method, hyper-parameters are determined through Bayesian optimization, and a fatigue life prediction result of the high-temperature alloy vacuum electron beam welding structure is output. The method provided by the invention can well consider the influence of different morphology defects on the fatigue performance of the welded joint.

The invention relates to the technical field of structural engineering, and provides a surface crack fatigue propagation morphology and life prediction method based on machine learning, which comprises the following steps: establishing a finite element simulation model containing a surface crack, calculating a stress intensity factor of the front edge of the surface crack, and generating a finite element simulation data set; performing dimensionless processing on parameters in the simulation data set to generate a machine learning data set; optimizing the back propagation neural network through a hybrid optimization algorithm, and constructing a surface crack stress intensity factor prediction model; the surface crack stress intensity factor prediction model is combined with a fatigue crack growth rate formula to cyclically predict the surface crack growth morphology and the service life of the load bearing structure; establishing a visual interaction interface of parameter input and output and image output based on the surface crack stress intensity factor prediction model and the fatigue crack growth rate formula; a user can quickly predict the propagation morphology of the surface crack and calculate the service life without mathematical analysis and code writing.

The invention discloses an active learning and physical loss-based fatigue crack growth rate prediction method, which comprises the following steps of: splicing and fusing a preprocessed stress intensity factor, a stress ratio, pre-strain and stress amplitude, and taking the fused characteristics as the input of a model; embedding the Jones model into a loss function of the neural network, constructing a physical information time sequence model based on the Jones model, setting a parameter set, selecting a most valuable training sample from a training set by using active learning, retraining the model by using the selected most valuable training sample, selecting an optimal model, and evaluating the optimal model by using a test set; fusing the actually measured stress intensity factor, stress ratio, pre-strain and stress amplitude of the to-be-predicted material, and inputting into the obtained prediction model to obtain a predicted value of the fatigue crack growth rate. By adopting the technical scheme of the invention, the fatigue crack growth rate of the material in the whole life period can be efficiently and accurately predicted at low cost.

The invention belongs to the technical field of aircraft strength experiments, and particularly relates to a hybrid-driven metal multi-fatigue crack propagation fusion prediction method. The method comprises the following steps: establishing a stress intensity factor expression under multiple fatigue cracks; initial distribution of material parameters in the Paris physical model is obtained, and posterior distribution of the material parameters is adjusted; based on the stress intensity factor expression under the multi-fatigue crack and the posterior distribution of the material parameters, obtaining an improved Paris physical model for describing the multi-fatigue crack propagation process; a depth encoder network model is established, and a network bottleneck layer is utilized to extract guided wave deep features with strong correlation with the fatigue crack length; establishing a guided wave data driven multi-fatigue crack length online monitoring model; and building a particle filter fusion framework, and correcting and improving a distribution interval of uncertain material parameters in the Paris physical model according to guided wave monitoring data to realize dynamic tracking and prediction of metal multi-fatigue crack propagation.

The invention discloses a PSO-SVR-based FSW joint fatigue crack propagation life prediction method and electronic equipment, and the method comprises the steps: simulating a crack propagation process of an FSW joint through a finite element simulation technology, obtaining a crack tip stress intensity factor, a corresponding loading load size and a crack length of the FSW joint in the process as a group of data, and constructing a data set; performing standardization processing on the constructed data set, and then dividing the data set into a training set and a test set; and training a machine learning model by using the training set, evaluating the trained model by using the test set, and performing hyper-parameter optimization on the model until an optimal crack tip stress intensity factor prediction model is obtained. According to the PSO-SVR-based FSW joint fatigue crack propagation life prediction method and the electronic equipment provided by the embodiment of the invention, finite element simulation data and test data are fused, so that the time cost and expense for constructing the fatigue crack propagation life model are effectively reduced, and the method and the electronic equipment have the advantages of high calculation efficiency, high prediction precision and the like.

The invention discloses a test-based crystal plasticity and cohesion model coupling hydrogen induced cracking simulation method, which comprises the following steps: carrying out a hydrogen filling mechanical property test on a metal material to obtain a true stress-true strain curve of the metal material in a hydrogen environment; carrying out a hydrogen-filled fracture toughness test on the metal material to obtain a stress intensity factor of the metal material in a hydrogen environment; constructing a cohesion constitutive model; a metal material electron back scattering diffraction microscopic characterization test is carried out, microstructure characteristics are obtained, and a polycrystalline model is constructed; constructing a crystal plastic constitutive model; coupling crystal plasticity constitutive and cohesion constitutive, and calibrating crystal plasticity to-be-determined parameters by adopting a trial-and-error method; and carrying out finite element simulation analysis on hydrogen-induced cracking behaviors with different microstructure characteristics in a hydrogen environment to obtain stress-strain data and crack data of the hydrogen-induced cracking behaviors. According to the invention, high-precision simulation of the hydrogen-induced cracking micromechanism of the metal material in the hydrogen environment is realized.

The invention discloses a design method of a periodically-arranged porous thin-wall combustion chamber flame tube characteristic simulation piece, which comprises the following steps: carrying out fluid-thermal-solid coupling analysis in a real structure service environment, obtaining the temperature field distribution of a combustion chamber flame tube and the size and direction of a first principal stress, and determining a part with the maximum first principal stress as a dangerous part; inserting an initial crack into a dangerous part of a real component, carrying out crack propagation numerical simulation, and extracting a stress intensity factor change rule on a crack propagation path; on the basis of keeping key geometric characteristics of a periodically arranged porous structure, a simulation piece is configured and designed into a biaxial flat plate stretching piece, and stress gradient distribution of a real component is matched through porous array parameter optimization; a biaxial tensile testing machine is adopted to apply a multi-axial load to the simulation part, and it is ensured that the stress intensity factor amplitude under different crack lengths is kept consistent with that of a real component. The method has important engineering value for damage tolerance evaluation and life prediction of the aero-engine combustion chamber.

The invention provides a crack-containing pipeline failure analysis software system, and belongs to the field of crack-containing pipeline failure evaluation. The system comprises a parameter import module, a random sampling module, a penetration crack length module, a leakage rate module, a failure analysis module and a display module. The parameter import module imports pipeline material parameters, operation environment parameters and the like into the computer; the random sampling module is used for carrying out random sampling according to a common distribution function on the basis of importing parameters; the fatigue crack propagation module is used for calculating a stress intensity factor and fatigue crack propagation; the leakage rate module is used for calculating a detectable leakage length; and the result analysis module is used for integrating all calculation results and input parameters into a failure probability analysis chart. According to the method, the probability fracture mechanics method is adopted, the detection accuracy is improved, and the failure probability of equipment can be evaluated more quickly and visually.

The invention provides an asphalt pavement life prediction model establishment method based on environment and load coupling analysis, which comprises the following steps: establishing a three-dimensional finite element model of an asphalt pavement by using Abaqus software, simulating dynamic response of a pavement structure under the action of moving load and temperature, and obtaining the maximum tensile strain value of the bottom of each layer of an asphalt surface layer; in combination with a temperature correction coefficient, a humidity correction coefficient and a thickness correction coefficient, the model is corrected to improve the prediction precision; simulating the expansion process of the reflection crack under the load action by adopting an expansion finite element method, and calculating a composite stress intensity factor and the influence of the composite stress intensity factor on crack expansion; referring to a Paris formula, introducing an equivalent crack damage rate, and constructing a service life prediction model considering the damage of crack propagation to the pavement structure; influences of temperature, humidity, load, asphalt layer overall strain accumulation, pavement structure layer thickness and reflection cracks are comprehensively considered, and an asphalt pavement life prediction model based on finite elements is established and used for accurately predicting the service life of an asphalt pavement.

The invention belongs to the technical field of constructional engineering, and particularly relates to a laminated component joint crack propagation judgment method based on fracture mechanics, which comprises the following steps: establishing a weak joint surface inclined crack coordinate system based on a weak joint surface at a joint of a laminated component, and calculating a stress intensity factor of a weak joint surface inclined crack tip; calculating the tip circumferential stress of the inclined crack along the weak junction surface by combining a crack tip circumferential stress expression constructed on the basis of fracture mechanics; based on the circumferential stress of the tip of the oblique crack along the weak joint surface, determining the joint crack propagation and propagation direction of the laminated component in combination with the maximum circumferential stress criterion; and based on the concrete strength of the prefabricated component and the strength of post-poured concrete, comparing the circumferential stress of the tip of the inclined crack along the weak joint surface, and determining the propagation priority in the joint crack propagation process of the laminated component. The method can be used for judging whether the joint of the laminated component is cracked or not and judging the crack propagation direction and priority, so that the safety, stability and reliability of the structure are ensured.

The invention discloses a 42CrMo fatigue crack propagation rate prediction method based on machine learning, and the method comprises the steps: obtaining a corresponding relation among a stress intensity factor, a stress ratio and a fatigue crack propagation rate of a 42CrMo material through a fatigue crack propagation test, and taking the corresponding relation as an original data set; dividing the preprocessed original data set into a training set and a test set, constructing a fatigue crack growth rate prediction model, training the model by adopting the training set, and evaluating the trained model by adopting the test set; and inputting the actually measured stress intensity factor and stress ratio of the 42CrMo material to be predicted into the prediction model obtained in the step 3, and outputting through the prediction model to obtain a predicted value of the fatigue crack growth rate of the 42CrMo material to be predicted. According to the method, the fatigue crack growth rate of the 42CrMo material can be efficiently and accurately predicted at low cost, so that the service life of the wind power bearing is prolonged, and potential safety hazards are reduced.

The invention provides a method and system for evaluating fatigue crack life of a welding structure under a random load, and relates to the technical field of rail transit, and the method comprises the steps: recognizing a load peak value and a load valley value through a point-by-point extreme value extraction method, and generating an equivalent variable-amplitude load data set; initial crack propagation rate parameters C and m and stress intensity factor distribution are calculated, and then a deterministic crack propagation increment result is output; a hierarchical Bayesian framework is combined with an MCMC sampling method, and global parameter distribution considering material heterogeneity and observation noise is generated through a posterior distribution formula; predicting crack depth evolution curves under different confidence coefficients, and outputting fatigue life probability distribution and confidence intervals; and finally generating a fatigue life reliability evaluation report of the welding structure under the random load. The method has the beneficial effects that the problem of fatigue crack propagation of the railway vehicle welding structure under the action of the complex random load can be better solved, and more accurate and reasonable technical support is provided for reliability evaluation of the welding structure.

The application discloses a brake interface wear and fatigue crack prediction method based on complete thermal-mechanical coupling, comprising the following steps: S1, establishing a finite element model, and discretizing total analysis time into multiple time periods; S2, starting finite element analysis, and calculating interface node contact pressure and node slip rate; S3, performing transient thermal-mechanical coupling analysis; S4, calculating node wear depth and wear direction, and updating grid information by using ALE technology; S5, judging whether the interface contact state is stable convergence; S6, ending analysis, unloading brake load, and obtaining brake disc residual stress; and S7, presetting a crack at the maximum residual stress, simulating crack propagation behavior, calculating stress intensity factor and brake disc fatigue life. The application can simulate tribological behaviors such as contact stress, temperature and wear, and realizes brake disc fatigue life prediction by taking residual stress after the thermal-mechanical coupling process as load input.

The invention discloses a method for evaluating rock mass fracture freeze-thaw fracture damage risk based on surface temperature, which comprises the following steps: S1, carrying out data acquisition on a target area based on a multi-source sensor carried by an unmanned aerial vehicle platform, and obtaining fracture geometric parameters, daily surface minimum temperature, daily surface maximum temperature, daily temperature difference and fracture moisture conditions; s2, on the basis of the geometric parameters of the crack, constructing a crack frost heaving force analytical model; obtaining a quantitative relation between the stress intensity factor and the environment temperature; s3, the I-type fracture toughness of the target rock mass is measured, and the critical crack initiation temperature of the rock mass is determined; determining the number of critical freezing and thawing cycles; s4, on the basis of the daily earth surface minimum temperature, the daily temperature difference, the fracture moisture condition and the critical crack initiation temperature, the annual accumulated effective freezing and thawing cycle number is obtained; and calculating a freeze-thaw damage ratio, and carrying out risk quantification and grading. According to the invention, the problem of inaccurate evaluation caused by limitation to local monitoring and lack of an environment factor and material parameter integrated evaluation framework in the prior art is solved.

The invention discloses a method for predicting the service behavior of an oil and gas pipeline under a stress corrosion cracking condition, and belongs to the field of material performance analysis and prediction. Firstly, based on a convection diffusion equation, a real stress intensity factor of an oil and gas pipeline crack tip is used as an unknown quantity to obtain a stress distribution condition; then, applying boundary conditions and a crack propagation criterion in fracture mechanics, and performing preliminary calculation to obtain crack propagation behavior characteristics of the one-dimensional semi-analytical model; and finally, calibrating and calculating the diffusion coefficient of the material parameter in the one-dimensional semi-analytical model to obtain real full-life service time information of the oil and gas pipeline material. According to the method, the full-life behavior information of stress corrosion cracking can be quickly obtained, and a partial differential equation does not need to be solved; on the basis of fracture mechanics, the mechanism of repeated fracture and reconstruction of the passivation layer in the fracture process can be reproduced; the full-life service time of the oil and gas pipeline can be effectively predicted, and the parameter calibration method can be applied to other conditions and is wide in application range.

The invention discloses a crack stress intensity factor calculation method based on a three-dimensional weight function method, and belongs to the technical field of reliability. Based on a complex variable function Taylor series expansion method, a complex variable finite element program is operated to obtain a weight function of given crack geometry, and then a stress intensity factor of the crack is obtained through stress on a crack surface and weight function integration. Specifically, the method comprises the following steps: establishing a crack-containing finite element model and dividing grids; carrying out perturbation on a crack tip unit node on an imaginary axis; running a complex variable finite element program to obtain an imaginary part of a node crack opening direction on the crack surface so as to obtain a weight function on the crack surface; and solving the stress intensity factor of the corner of the connecting pipe by integrating the weight function of the crack surface and the stress of the crack surface. Compared with a two-dimensional weight function, the method is expanded to three-dimensional elliptical cracks, and the application range is wider; by adopting the method, the calculation result of solving the stress intensity factor of the corner of the connecting pipe under the action of complex load is accurate, and the use is simple and effective.

The invention belongs to the technical field of tunnel water inrush monitoring, and particularly relates to a tunnel water inrush monitoring and early warning method under a water-rock coupling effect, which comprises the following steps: S1, obtaining tunnel data and rainfall data of a historical time sequence, carrying out data processing, and training a preset logistic regression model; s2, acquiring a position cross-section diagram of the water-containing fracture of the tunnel by using a high-density electrical method; s3, selecting the maximum K water-containing fractures based on the position cross-section diagram in the S2, respectively calculating effective method corresponding force sigma'n and shear stress tau'n, and then calculating a stress intensity factor K II; corresponding cracking early warning judgment is carried out; s4, current tunnel data and rainfall data are obtained and processed, and the trained logistic regression model is used for predicting the current water inrush risk probability; and corresponding water inrush early warning judgment is carried out. According to the method, multi-source data can be fused, a water-rock coupling action mechanism is considered, and tunnel water inrush monitoring and early warning are efficiently carried out in real time.

The invention relates to a method for evaluating the crack initiation probability of an RPV surface crack under a transient working condition, and belongs to the field of safety analysis of nuclear pressure-bearing equipment. The method comprises the following steps: sampling a random variable and determining a sampled multivariate sample; calculating a stress intensity factor of the crack evaluation point caused by multiple loads under the transient condition; calculating a stress intensity factor of the crack evaluation point after the influence of the crack tip plastic zone is brought into the transient condition; calculating the reference temperature of the crack evaluation point after neutron irradiation embrittlement is considered under the transient condition; constructing a fracture toughness probability distribution model of the crack evaluation points under the transient condition; calculating the crack initiation probability of the crack at the current moment under the transient condition; judging whether the current moment is the last moment of the transient working condition, if so, ending the calculation process of the crack initiation probability under the transient working condition, and otherwise, updating the transient moment; and evaluating the crack initiation probability of the RPV surface cracks under all samples. According to the method, the crack initiation probability of the RPV surface crack under the transient working condition can be efficiently and accurately evaluated.

The invention relates to the technical field of structural engineering, and provides a surface crack stress intensity factor prediction method and device based on machine learning, and the method comprises the steps: building a finite element simulation model containing a surface crack, calculating the stress intensity factor of the front edge of the surface crack, verifying through an empirical formula, and generating a finite element simulation data set; performing dimensionless processing on the size of the surface crack, the size of the load bearing structure and the stress intensity factor of the front edge of the surface crack in the finite element simulation data set to generate a machine learning data set; optimizing the back propagation neural network through a hybrid optimization algorithm, and constructing a stress intensity factor prediction model based on machine learning; adjusting hyper-parameters of the neural network, and verifying a fitting effect of the stress intensity factor prediction model based on machine learning; based on the stress intensity factor prediction model, establishing a visual interaction interface for related parameter input, image output, prediction result output and comparison result output; while the calculation efficiency is maintained, the calculation precision and the application range are improved.

A risk assessment and control method for radial cracking and crack propagation and transfixion of cement sheath in fracturing wells is provided. Based on the thermo-solid coupling theoretical model of casing-cement sheath-formation combination and thick-walled cylinder theory, the tangential stress distribution of crack-free cement sheath when fracturing is obtained, the maximum tensile stress criterion is used to judge whether the cement sheath has radial initial cracking when fracturing and calculate the initial cracking length, based on the weight function method, the stress intensity factor of the tip of the radial initial cracking of the cement sheath when fracturing is calculated, the fracture mechanics criterion is used to judge whether the radial crack propagation and transfixion will occur in the cement sheath, and the performance parameters of the cement sheath are controlled by the double standards of preventing the radial cracking of the cement sheath and controlling the crack propagation.

The invention discloses a data processing method for segmented fitting of a fatigue crack propagation rate curve, which belongs to the technical field of metal material fatigue crack propagation rate tests, and comprises the following steps: obtaining a data curve to be fitted, determining the amplitude of a stress intensity factor, and setting the range interval of segmented fitting. Fitting data points in the range interval subjected to piecewise fitting to obtain a linear equation, converting the obtained linear equation into a power function form of a Paris formula, and substituting the stress intensity factor amplitude into the power function form of the Paris formula to calculate the corresponding fatigue crack growth rate. According to the method, the calculated fatigue crack growth rate under the specified stress intensity factor amplitude is closer to a real test value, and the fatigue crack growth rate serving as a material engineering application basis is more reliable.

The invention relates to the technical field of metal material fatigue crack prediction, in particular to a method for predicting a metal material fatigue crack growth rate. The method comprises the following steps: introducing an equivalent factor # imgabs0 # to obtain a fatigue crack propagation rate model; the method comprises the following steps: carrying out a fatigue crack growth rate test on a metal material at room temperature, measuring a fatigue crack growth curve under a stress ratio # imgabs1 # in a steady-state stage, and fitting the obtained fatigue crack growth curve based on a Paris formula to obtain values # imgabs2 # and # imgabs3 # and an equivalent factor # imgabs6 # corresponding to stress intensity factor change ranges # imgabs4 # and # imgabs5 #; the # imgabs7 # is multiplied by the # imgabs8 #, and the # imgabs10 # when the stress ratio of the # imgabs9 # is obtained; the # imgabs 11 # is divided by the # imgabs 13 # under the target stress ratio # imgabs 12 #, and the fatigue crack growth rate under the stress ratio # imgabs 14 # is obtained. According to the method, the technical problem of large prediction result error caused by large calculation amount and complex steps of a metal material fatigue crack propagation prediction method in the prior art is effectively solved.

The invention relates to a fatigue crack propagation simulation and life prediction method considering a crack closing effect. The method comprises the following steps: constructing a finite element model; assembling crack sizes in the finite element model according to user requirements, refining regional grids of the cracks, expanding the cracks in the finite element model, extracting a displacement field of the regional grids at the tips of the cracks, performing nonlinear calculation considering a crack closing effect on the basis of the displacement field, and calculating the crack closing effect. Obtaining an I-type stress intensity factor and an II-type stress intensity factor at the tip of the crack; calculating a crack propagation angle based on the I type stress intensity factor and the II type stress intensity factor and based on a maximum circumferential stress criterion, and calculating a new crack tip coordinate based on the crack tip coordinate, the crack propagation angle and a user-defined crack propagation increment; and updating historical crack tip coordinates based on the new crack tip coordinates to update the cracks, and assembling the finite element model until the I-type stress intensity factor is greater than the fracture toughness, and outputting a result in a table form.