CN116933603B - CMC fatigue life dispersion prediction method considering thermosetting coupling effect - Google Patents
CMC fatigue life dispersion prediction method considering thermosetting coupling effect Download PDFInfo
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Abstract
The invention discloses a CMC fatigue life dispersion prediction method considering thermosetting coupling effect, comprising the following steps: constructing an RVE geometric model of CMC; performing grid division on the model and setting material parameters; applying temperature load, periodic boundary condition and initial mechanical external load, analyzing stress-fatigue life and extracting unit stress result; calculating the number of cyclic loads which can be born by each unit under the load action born by the unit through the fatigue life distribution function of the small composite material of CMC, carrying out unit failure judgment by combining with Miner accumulated damage failure criteria, carrying out model failure judgment, updating the material attribute of the failed unit if the model is not failed, and circularly executing subsequent steps after reapplying the initial mechanical external load until the model fails, so as to obtain the fatigue life of the model; drawing a stress-fatigue life curve of the model; fitting a plurality of stress-fatigue life curves of the model, fitting a plurality of fatigue life results into Weibull distribution, and observing the dispersion of fatigue performance. The invention can realize thermosetting coupling analysis considering CMC fatigue life performance dispersibility, and is easy to realize.
Description
Technical Field
The invention belongs to the technical field of CMC fatigue life analysis, and particularly relates to a CMC fatigue life dispersibility prediction method considering thermosetting coupling effect.
Background
The ceramic matrix composite (Ceramic Matrix Composites, CMC) is a novel composite with wide application prospect, high temperature resistance, corrosion resistance, small density, high specific strength and the like, and is very suitable for being applied to aerospace hot end components. In order to ensure the usable conditions and the service time within a safe range of the CMC component under various temperature working conditions, a more accurate fatigue life prediction result of the CMC is required to be obtained. Because CMC components are very different in design from traditional metal components, the method of predicting their fatigue life is also different. In CMC performance analysis, material performance dispersibility caused by composite material structure dispersibility is considered, and characteristics of CMC structural component heterogeneity, anisotropy and the like are considered, so that the fatigue life prediction of CMC is difficult.
In the current research, the fatigue life of the ceramic matrix composite under the random load is predicted by obtaining the material performance parameter changes such as strength, shear stress and the like through experiments and observation and bringing the material performance parameter changes into a given failure criterion based on the fatigue hysteresis energy consumption of CMC from a macroscopic angle; CMC fatigue life prediction at normal temperature under consideration of structural dispersibility has also been studied; the method is characterized by further comprising the steps of developing a strain-based failure criterion, considering progressive damage and distinguishing the difference of composite material fibers and non-fiber directions in a cyclic degradation model, considering the influence of fatigue layering damage on the service life, and establishing a fatigue service life prediction method of the composite material; in addition, from the perspective of a mesoscopic model, mesoscopic geometric parameters of CMC are obtained through electron microscope scanning, corresponding material parameters are input to establish an RVE model, and cycle skip algorithm is adopted to finish the calculation of the CMC fatigue life span; in addition to the above, studies have been based on micromechanics and have predicted fatigue life of composite materials at different temperatures by introducing a linear dependence of the fatigue parameters of the individual components of the composite materials on temperature.
According to the scheme, a plurality of modes for predicting the fatigue life of the composite material are provided, but simulation analysis is performed by constructing an RVE model through a macro-micro combination mode and combined with macroscopic test data verification, CMC fatigue life prediction research based on comprehensive consideration of the influence of material dispersibility and the influence of material temperature working conditions is few. Accordingly, the accuracy of CMC fatigue life predictions remains to be improved, and current methods are not sufficient to widely cover CMC of different preform structures.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a CMC fatigue life dispersion prediction method considering the thermosetting coupling effect, which comprehensively considers the different temperature working conditions of CMC service and the dispersion of higher degree on the structure and performance thereof based on progressive damage simulation, analyzes the progressive damage process of CMC under the scale of Representative Voxels (RVE), predicts the stress-fatigue life relation of CMC, and realizes CMC fatigue life dispersion analysis prediction considering the thermosetting coupling effect.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
a CMC fatigue life dispersion prediction method taking into account thermosetting coupling effects, comprising:
step 1: according to the geometric characteristics of the CMC actual preform, neglecting the non-uniformity of the mesostructure by combining with specific calculation requirements, and constructing an RVE geometric model of the CMC;
step 2: grid division is carried out on the RVE geometric model of the CMC, material parameters are set for each grid unit, and an RVE finite element model of the CMC with the material parameters is obtained;
step 3: applying temperature load, periodic boundary condition and initial mechanical external load to RVE finite element model of CMC after setting material parameters, carrying out thermosetting coupling mechanical analysis of stress-fatigue life and extracting unit stress result;
step 4: the fatigue life dispersion of the components was determined. According to the small composite material pulling-pulling fatigue life distribution function of CMC, the fatigue life distribution of CMC material fiber bundles is determined, and the failure criterion N of fiber bundle units in RVE model is given, namely the fatigue life of each unit under the self-bearing load. Similarly, the failure criterion N for matrix units in the RVE model is given by the fatigue life distribution of the matrix in the CMC material.
Step 5: based on the stress results of each unit extracted in the step 3 and in combination with the failure criterion in the step 4, the fatigue life of each unit under the action of the stress load born by each unit is obtained, namely the number of times of cyclic load born by each unit under the action of the stress load born by each unit;
step 6: judging whether each unit fails or not based on the number of cyclic loads born by each unit obtained in the step 5 and a Miner accumulated damage failure criterion, calculating the actual number of cyclic loads to be overlapped at the stage, judging whether the current model volume failure ratio meets the model failure criterion, if yes, indicating that the RVE finite element model fails, otherwise, updating the material property of the failed unit, returning to the step 3, applying the initial mechanical external load again, and then circularly executing the subsequent steps until the RVE finite element model fails, and obtaining the fatigue life of the RVE finite element model, namely the total actual number of cyclic loads accumulated at all stages when the model fails;
step 7: and (3) continuing the model established in the step (1) and the step (2), only changing the initial mechanical external load applied in the step (3), keeping the temperature load and boundary conditions born in the step (3) unchanged and continuing the continuous use, repeating the steps (5) to (6) to obtain a plurality of groups of stress-fatigue life data combinations, and finally performing curve fitting on the plurality of groups of stress-fatigue life data combinations to obtain a stress-fatigue life curve of the RVE model of the CMC;
step 8: the fatigue life distribution of the material is determined. And (3) along the models obtained in the step (1) and the step (2), when different positions of CMC are scanned based on XCT, the geometric parameters in the step (1) are changed along with the scanning, the steps (3) to (6) are repeatedly executed, the stress-fatigue life curves of the finite element RVE models of a plurality of CMCs are calculated and fitted, and the fatigue life dispersion distribution rule of the CMC is determined.
In the step 1, the geometric characteristics of the CMC actual preform are obtained based on the XCT scanning image, and the sectional shape, the fiber trend and the pore of the CMC are approximated under the condition that the basic characteristics required by calculation can be reserved in the construction process of the geometric model.
The material parameters described in step 2 include at least elastic modulus, shear modulus, poisson's ratio and density.
Step 3, determining temperature load distribution of the RVE geometric model according to the temperature working condition, and applying periodic boundary conditions and initial mechanical external load to the RVE geometric model;
the initial mechanical external load is in the proportion range of 60% -80% of the static strength of the material.
Step 6 carries out unit failure judgment based on the number of times of cyclic load which can be born by each unit obtained in step 5 and Miner accumulated damage failure criterion;
wherein the Miner cumulative damage failure criteria is:
d represents the damage sum of stress amplitude of each level;
X i representing the actual number of cycles reached at the i-th level of stress amplitude;
N i the number of allowed loads when fatigue failure is reached at the i-th level of stress amplitude is expressed and can be found from the fatigue life distribution function of the small composite material of CMC.
The method for updating the material property of the failure unit in the step 6 is as follows:
and carrying out rigidity reduction treatment on the material property of the failure unit: the units are progressively stiffness-reduced in percent reduction to a minimum of about zero.
In the step 8, the same load may correspond to one fatigue life in the stress-fatigue life curves of the finite element RVE models of the CMC respectively, and the fatigue life corresponding to the stress-fatigue life curves is fitted into Weibull distribution by using a least square method to determine the fatigue life dispersion distribution rule of the CMC.
The invention has the following beneficial effects:
according to the method, by establishing the RVE geometric model of the CMC, the dispersion of the fatigue life of the microstructure of the CMC is considered, the thermosetting coupling analysis is carried out on the progressive damage process of the CMC under different temperature working conditions, and the defect that the material performance dispersion and the thermosetting coupling effect of the CMC are not considered at the same time in the conventional method is overcome. The CMC fatigue life dispersion analysis method considering the thermosetting coupling effect can realize thermosetting coupling analysis considering the CMC fatigue life performance dispersion, and is easy to realize.
Drawings
Figure 1 is a schematic view of the RVE geometric model of a 2.5D woven CMC;
FIG. 2 is a schematic representation of RVE partitioning finite element mesh results for a 2.5D woven CMC;
FIG. 3 is a graphical illustration of stress-fatigue life curves for different components of a 2.5D woven CMC;
FIG. 4 is a flow chart of a fatigue life calculation based on a progressive damage analysis specific to RVE of a 2.5D woven CMC;
FIG. 5 is a RVE stress-fatigue life graph of a 2.5D woven CMC;
FIG. 6 is an overall flow chart analysis of the invention taking into account thermoset coupling effects and fatigue dispersion.
In the figure, a and b refer to warp and weft yarns, respectively, of 2.5D woven CMC fiber bundles, and c refers to the matrix in the fiber bundle space; any point on the stress-fatigue life curve represents the corresponding fatigue life of the RVE of the 2.5D woven CMC under a cyclic load.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Although the steps of the present invention are arranged by reference numerals, the order of the steps is not limited, and the relative order of the steps may be adjusted unless the order of the steps is explicitly stated or the execution of a step requires other steps as a basis. It is to be understood that the term "and/or" as used herein relates to and encompasses any and all possible combinations of one or more of the associated listed items.
The invention provides a CMC fatigue life dispersion analysis method considering thermosetting coupling effect, taking 2.5D woven CMC as an example and an implementation object, comprising the following steps:
step 1: establishing an analysis model: according to the geometric characteristics of the CMC actual preform, combining specific calculation requirements and simulation purposes, neglecting part of microscopic non-uniformity with little influence on simulation calculation, and constructing an RVE geometric model of the CMC;
further, CMC actual preform geometry can be obtained based on XCT scan images. In the construction process of the geometric model, the microscopic structures such as the cross-section shape, the fiber trend, the pores and the like of the geometric model are approximated under the condition that the basic characteristics required by calculation can be reserved, so that the geometric model is convenient to analyze.
As shown in fig. 1, according to the geometric characteristics of the actual 2.5D woven CMC preform, for the purpose of analyzing the overall fatigue life, neglecting part of the fine non-uniformity, a geometric model of the 2.5D woven CMC material RVE is built, which model is composed of CMC radial fiber bundles (a), weft fiber bundles (b) and matrix (c) in fiber bundle intervals arranged in warp and weft directions, and the matrix (c) is the holes because a large number of large-size holes are always present in the matrix (c) in the material, so the porosity between fiber bundles is approximately 100%.
Step 2: the RVE geometric model of CMC is grid-partitioned, and the partitioning result is shown in fig. 2. Model initial material parameters are determined, and material parameters are given to each grid cell, including elastic modulus, shear modulus, poisson's ratio, density and the like.
Step 3: applying temperature load, periodic boundary condition and initial mechanical external load to RVE finite element model of CMC after setting material parameters, carrying out thermosetting coupling mechanical analysis of stress-fatigue life and extracting unit stress result;
further, determining RVE temperature load distribution according to temperature working conditions in the step 3, applying periodic boundary conditions and initial external load to an RVE geometric model of CMC, and carrying out finite element analysis;
the temperature working condition is the temperature distribution of the macroscopic component at a certain point under the working condition of the macroscopic component, the initial mechanical external load is in the proportion range of 60% -80% of the static strength of the material, and the specific proportion range slightly changes according to different materials.
Periodic boundary conditions are imposed on the RVE geometric model of CMC:
(v x＝LC -v x＝0 ) y,z ＝0
(w x＝LC -w x＝0 ) y,z ＝0
(u y＝WC -u y＝0 ) x,z ＝0
(w y＝WC -w y＝0 ) x,z ＝0
(u z＝HC -u z＝0 ) x,y ＝0
(v z＝HC -v z＝0 ) x,y ＝0
wherein u is i 、v i 、w i Displacement of the specified point in RVE in the three orthogonal directions X, Y, Z, respectively, the specified point being indicated by a subscript, e.g. (u) x＝LC -u x＝0 ) y,z Representing the subtraction of the displacement in the X direction at (LC, 0) and (0, 0);
strain at three representative points rp1, rp2, rp3 in three directions of X, Y, Z, respectively;
and an initial mechanical external load with the magnitude of 60-80% of the static strength of the material is applied for stress-fatigue life analysis.
Step 4: the fatigue life dispersion of the components was determined. FIG. 3 is a schematic S-N curve of the various components of CMC, with three points marked to indicate that the fatigue life of the three components under the same load are different, highlighting the dispersion characteristics of the fatigue life of the components. Small composite material pull-pull fatigue life distribution functions based on CMC, e.g. Weibull distribution functionsIn N 0 、N a And b is three parameters describing Weibull distribution, N 0 Is a minimum lifetime parameter; n (N) a As a scale parameter, the dispersibility of the data N is reflected; b is a shape parameter, the shape of the density function curve can be controlled, and when b=1, the density function is in exponential distribution, when b=2, the density function is in Reyleigh distribution, and when b is 3-4, the shape of the density function curve is very close to normal distribution; the fatigue life distribution of the CMC material fiber bundles is determined. According to this distribution, the failure criterion N of the fiber bundle units in the RVE model, i.e. the fatigue life of the individual units under the load they are subjected to, is given. Similarly, the failure criterion N for matrix units in the RVE model is given by the fatigue life distribution of the matrix in the CMC material.
Step 5: based on the stress results of the units extracted in the step 3, and combined with the failure criterion N in the step 4, the fatigue life value of each unit under the action of the load born by each unit can be obtained, namely the number of times of cyclic load born by each unit under the action of the load born by each unit;
step 6: judging whether each unit fails or not based on the number of cyclic loads born by each unit obtained in the step 5 and a Miner accumulated damage failure criterion, calculating the actual number of cyclic loads to be overlapped at the stage, judging whether the current model volume failure ratio meets the model failure criterion, if yes, indicating that the RVE finite element model fails, otherwise, updating the material property of the failed unit, returning to the step 3, applying the initial mechanical external load again, and then circularly executing the subsequent steps until the RVE finite element model fails, and obtaining the fatigue life of the RVE finite element model, namely the total actual number of cyclic loads accumulated at all stages when the model fails;
step 6 achieves progressive lesion analysis. According to the number of cyclic loads which each unit mentioned in step 5 can bear and combining Miner cumulative damage failure criterionAnd (3) judging the failure of the unit, carrying out rigidity reduction treatment on the material property of the failed unit, then applying a load to the RVE model of the material again, carrying out stress-fatigue life analysis and unit failure judgment again, and repeating the process until the whole fatigue of the material fails.
Further, miner cumulative damage failure criterion
D represents the damage sum of stress amplitude of each level;
X i representing the actual number of cycles reached at the i-th level of stress amplitude;
N i the number of allowed loads when fatigue failure is reached at the i-th level of stress amplitude is expressed and can be found from the fatigue life distribution function of the small composite material of CMC.
Further, the unit material property reduction treatment in the step 6 means that the unit is gradually reduced in rigidity in a percentage reduction manner until the unit reaches a minimum value of about zero.
For example, as shown in fig. 4, a specific computational analysis flow of the present invention is shown. According to the number of cyclic loads which each unit mentioned in step 5 can bear and combining Miner cumulative damage failure criterionAnd (3) judging the failure of the unit, carrying out rigidity reduction treatment on the material property of the failed unit, then applying a load to the RVE model of the material again, carrying out stress-fatigue life analysis and unit failure judgment again, and repeating the process until the whole fatigue of the material fails. The rigidity of the unit materials is reduced in a percentage reduction mode, and the unit materials are gradually reducedThe material stiffness is reduced to a minimum of about zero.
Judging unit failure based on the number of times of cyclic load which can be born by each unit obtained in the step 5 and Miner accumulated damage failure criterionThe specific mode for judging the unit failure is as follows:
in simulation data analysis, after initial mechanical external load is applied for the first time, the stress of each unit can be obtained, and then the fatigue life N corresponding to the stress of each unit can be obtained by combining the tensile-tensile fatigue life distribution function of the CMC small composite material mentioned in the step 4, namely the number of times of cyclic load which can be born by any unit under the action of the stress load born by the unit can be obtained. Therefore, after the external load of the machine is applied for the first time, based on Miner accumulated damage failure criterion, whether each unit fails or not can be judged respectively, namely D=1 is respectively given for each unit, and the calculation formula at this stage can be listed asN of each unit 1 Can be calculated by the distribution function of the tensile fatigue life of the CMC small composite material respectively, when the actual circulation times X of each unit 1 Equal to N 1 When the unit fails, the X corresponding to each unit is compared 1 The magnitude of the value, the smallest X 1 I.e. the actual cyclic load number at this stage, with minimum X 1 The corresponding unit is the corresponding failure unit after the load is applied in the first stage. Immediately updating the material property of the failure unit, updating the stress of the unit after the load equal to the initial external load is applied for the second time, and calculating and judging based on Miner accumulated damage failure criterion for each unit, wherein D=1 is respectively calculated according to the calculation formula at the stage of the step of calculating the stress of the failure unit, wherein the calculation formula can be expressed as ++> N 1 X is the number of cyclic loads that each unit can withstand in the first stage 1 For the number of actual cyclic loads to which each unit is subjected in the first stage, N 2 X is the number of cyclic loads which each unit can bear under the load of the second stage 2 For the number of actual cyclic loads to which each unit is subjected in the second stage, each unit X is then compared 2 The magnitude of the value, the smallest X 2 I.e. the actual cyclic load number at this stage, with minimum X 2 The corresponding unit is the corresponding failure unit after the load is applied in the second stage. The judging mode of the later failure unit is the same as that of the former two, the calculation formula of each stage is listed based on Miner accumulated damage failure criterion, and the process is circulated until the integral fatigue failure of the material is met.
Step 7: the model established in the step 1 and the step 2 is used, only the initial mechanical external load applied in the step 3 is changed for a plurality of times, the temperature load and the boundary conditions born in the step 3 are kept unchanged and continue to be used, the finite element analysis in the steps 4 to 5 is repeated to obtain a plurality of groups of stress-fatigue life data combinations, and finally the plurality of groups of stress-fatigue life data combinations are subjected to curve fitting to obtain the stress-fatigue life curve of the finite element RVE model of the CMC; wherein the stress refers to the initial external mechanical load applied in the step 3, and the corresponding fatigue life can be obtained through calculation by changing the initial external mechanical load.
The fatigue life of the material RVE model can be determined by step 7:
according to the stress-fatigue life result of the model simulation experiment, a material stress-fatigue life graph is drawn, as shown in fig. 5, and each point on the graph represents the fatigue life of the RVE under the corresponding cyclic load.
Step 8: the fatigue life distribution of the material is determined. And (3) along the models obtained in the step (1) and the step (2), when the CMC is scanned at different positions based on XCT, the geometric parameters in the step (1) are changed, the steps (3) to (7) are repeatedly executed (when the steps (3) to (7) are repeatedly executed, the variables are the geometric parameters in the step (1)), the stress-fatigue life curves (the stress and fatigue life curves obtained by fitting the steps (7)) of the finite element RVE model of a plurality of CMCs are calculated, any fatigue load with the size within the range of 60% -80% of the static strength of the material is selected, one fatigue life can be respectively corresponding to one fatigue life in the stress-fatigue life curves, the fatigue life results of the plurality of groups are fitted into Weibull distribution by using a least square method, and the fatigue life dispersion distribution rule of the 2.5D woven CMC is determined.
The material fatigue life distribution can be determined by step 8:
the overall analysis flow is shown in FIG. 6; repeating the simulation experiments from the step 3 to the step 7 along the models established in the step 1 and the step 2;
the fatigue load with the magnitude within the range of 60% -80% of the static strength of the material is applied at will, one fatigue life can be respectively corresponding to the stress-fatigue life curves, the fatigue life results are fitted into Weibull distribution by a least square method, and the distribution probability density function is thatWherein: b is a shape parameter, N p For sample fatigue life, η is the scale parameter, η=n a -N 0 ，N a To be characterized by fatigue life, N 0 As a position parameter b>0,η>0,N 0 Not less than 0; when b=1, f (N p ) When b=3 to 4, f (N p ) Approximating a normal distribution density function. Thereby determining the fatigue life distribution rule of the 2.5D weaving CMC.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (7)
1. A CMC fatigue life dispersion prediction method considering thermosetting coupling effect, comprising:
step 1: according to the geometric characteristics of the CMC actual preform, neglecting the non-uniformity of the mesostructure by combining with specific calculation requirements, and constructing an RVE geometric model of the CMC;
step 2: grid division is carried out on the RVE geometric model of the CMC, material parameters are set for each grid unit, and an RVE finite element model of the CMC with the material parameters is obtained;
step 3: applying temperature load, periodic boundary condition and initial mechanical external load to RVE finite element model of CMC after setting material parameters, carrying out thermosetting coupling mechanical analysis of stress-fatigue life and extracting unit stress result;
step 4: determining the fatigue life distribution of the fiber bundles of the CMC material according to the small composite material pull-pull fatigue life distribution function of the CMC, and giving a failure criterion N of the fiber bundle units in the RVE model, namely the fatigue life of each unit under the action of load born by the unit; setting a failure criterion N of matrix units in the RVE model according to the fatigue life distribution of the matrix in the CMC material;
step 5: based on the stress results of each unit extracted in the step 3 and in combination with the failure criterion in the step 4, the fatigue life of each unit under the action of the stress load born by each unit is obtained, namely the number of times of cyclic load born by each unit under the action of the stress load born by each unit;
step 6: judging whether each unit fails or not based on the number of cyclic loads born by each unit obtained in the step 5 and a Miner accumulated damage failure criterion, calculating the actual number of cyclic loads to be overlapped at the stage, judging whether the current model volume failure ratio meets the model failure criterion, if yes, indicating that the RVE finite element model fails, otherwise, updating the material property of the failed unit, returning to the step 3, applying the initial mechanical external load again, and then circularly executing the subsequent steps until the RVE finite element model fails, and obtaining the fatigue life of the RVE finite element model, namely the total actual number of cyclic loads accumulated at all stages when the model fails;
step 7: and (3) continuing the model established in the step (1) and the step (2), only changing the initial mechanical external load applied in the step (3), keeping the temperature load and boundary conditions born in the step (3) unchanged and continuing the continuous use, repeating the steps (5) to (6) to obtain a plurality of groups of stress-fatigue life data combinations, and finally performing curve fitting on the plurality of groups of stress-fatigue life data combinations to obtain a stress-fatigue life curve of the RVE model of the CMC;
step 8: and (3) along the models obtained in the step (1) and the step (2), when different positions of CMC are scanned based on XCT, the geometric parameters in the step (1) are changed along with the scanning, the steps (3) to (6) are repeatedly executed, the stress-fatigue life curves of the finite element RVE models of a plurality of CMCs are calculated and fitted, and the fatigue life dispersion distribution rule of the CMC is determined.
2. The CMC fatigue life dispersion prediction method considering the thermosetting coupling effect according to claim 1, wherein the actual CMC preform geometric feature is obtained based on XCT scan images in step 1, and the cross-sectional shape, fiber orientation and pore of the CMC are approximated under the condition that the basic feature required by calculation can be maintained in the process of constructing the geometric model.
3. The method of claim 1, wherein the material parameters of step 2 include at least elastic modulus, shear modulus, poisson's ratio and density.
4. The CMC fatigue life dispersion prediction method considering the thermosetting coupling effect according to claim 1, wherein the step 3 determines the temperature load distribution of the RVE geometric model according to the temperature condition, and applies a periodic boundary condition and an initial mechanical external load to the RVE geometric model;
the initial mechanical external load is in the proportion range of 60% -80% of the static strength of the material.
5. The CMC fatigue life dispersion prediction method considering the thermosetting coupling effect according to claim 1, wherein the step 6 performs unit failure judgment based on the number of cyclic loads that each unit obtained in the step 5 can bear and a Miner cumulative damage failure criterion;
wherein the Miner cumulative damage failure criteria is:
d represents the damage sum of stress amplitude of each level;
X i representing the actual number of cycles reached at the i-th level of stress amplitude;
N i the number of load allowed to reach fatigue failure at the i-th stress amplitude is expressed and can be obtained from the fatigue life distribution function of the small composite material of CMC.
6. The CMC fatigue life dispersion prediction method considering the thermosetting coupling effect according to claim 1, wherein the mode of updating the failure unit material property in step 6 is:
and carrying out rigidity reduction treatment on the material property of the failure unit: the units are progressively stiffness-reduced in percent reduction to a minimum of about zero.
7. The method for predicting the fatigue life dispersion of CMC taking into account the thermosetting coupling effect according to claim 1, wherein in the step 8, the same load can correspond to one fatigue life in the stress-fatigue life curves of the finite element RVE models of the CMC respectively, the corresponding fatigue life is fitted into Weibull distribution by using a least square method, and the fatigue life dispersion distribution rule of CMC is determined.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109657412A (en) * | 2019-01-22 | 2019-04-19 | 北京航空航天大学 | A kind of multi-scale prediction method of the fatigue life of ceramic matric composite |
| CN109711100A (en) * | 2019-01-23 | 2019-05-03 | 南京航空航天大学 | A kind of prediction technique weaving ceramic matric composite fatigue life |
| CN111507038A (en) * | 2020-04-22 | 2020-08-07 | 南京航空航天大学 | Fatigue life prediction method for ceramic matrix composite structure |
| CN113866026A (en) * | 2021-08-29 | 2021-12-31 | 北京工业大学 | Method for acquiring load parameter-service life curve of ceramic matrix composite |
| CN114117839A (en) * | 2021-10-27 | 2022-03-01 | 中国运载火箭技术研究院 | Method for predicting mechanical property of ceramic matrix composite coupling damage |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10576670B2 (en) * | 2014-09-15 | 2020-03-03 | The Regents Of The University Of Michigan | Methods to increase structural performance, strength and durability of fabric-reinforced composite materials by pre-stressing |
| CN109614755B (en) * | 2018-12-29 | 2023-04-07 | 南京航空航天大学 | Method for predicting shear stress of high-temperature fatigue fiber/matrix interface of woven ceramic matrix composite material through hysteresis dissipation energy |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109657412A (en) * | 2019-01-22 | 2019-04-19 | 北京航空航天大学 | A kind of multi-scale prediction method of the fatigue life of ceramic matric composite |
| CN109711100A (en) * | 2019-01-23 | 2019-05-03 | 南京航空航天大学 | A kind of prediction technique weaving ceramic matric composite fatigue life |
| CN111507038A (en) * | 2020-04-22 | 2020-08-07 | 南京航空航天大学 | Fatigue life prediction method for ceramic matrix composite structure |
| CN113866026A (en) * | 2021-08-29 | 2021-12-31 | 北京工业大学 | Method for acquiring load parameter-service life curve of ceramic matrix composite |
| CN114117839A (en) * | 2021-10-27 | 2022-03-01 | 中国运载火箭技术研究院 | Method for predicting mechanical property of ceramic matrix composite coupling damage |
Non-Patent Citations (3)
| Title |
|---|
| 《复杂预制体陶瓷基复合材料疲劳失效机理及多尺度模拟》;方光武;《中国优秀博士学位论文全文库》;20171215;B020-25 * |
| 针刺C/SiC复合材料应力-应变模型及试验验证;方光武;宋迎东;高希光;;复合材料学报;20150907(第04期);第145-150页 * |
| 陶瓷基复合材料疲劳寿命预测方法;胡殿印;张泽帮;张龙;梅文斌;王荣桥;;航空发动机;20170815(第04期);第21-26页 * |
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