Electric arc additive remanufacturing heat affected zone fatigue crack growth rate prediction method

Abstract

The invention provides an electric arc additive remanufacturing heat affected zone fatigue crack growth rate prediction method, and relates to the technical field of crack growth prediction, and the method comprises the following steps: S1, making a sample; s2, performing in-situ SEM fatigue test on the sample; s3, calculating the crack growth rate and stress intensity factor range data of the sample; s4, constructing an initial fatigue crack growth rate model, and obtaining fitting parameter values of the sedimentary layer sample and the heat affected zone sample; s5, constructing a heat affected zone fatigue crack growth rate prediction model; and S6, predicting the fatigue crack growth rate of the heat affected zone: predicting the fatigue crack growth rate of the heat affected zone based on the heat affected zone fatigue crack growth rate prediction model in the step S5. According to the method, the fatigue crack growth rate of the heat affected zone can be accurately predicted according to the fatigue crack growth rate of the line arc additive manufacturing material deposition layer area.

Description

Technical Field

[0001] This invention relates to the field of crack propagation prediction technology, specifically to a method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing. Background Technology

[0002] Additive manufacturing is a revolutionary technology for manufacturing metal components, offering advantages over traditional manufacturing processes such as shorter production cycles and increased design freedom. Among various additive manufacturing processes, Wire-Arc Additive Manufacturing (WAAM) stands out due to its relatively low cost and high deposition rate, making it particularly suitable for manufacturing large and complex titanium alloy components. Aerospace titanium alloy components are subjected to long-term cyclic loading, with fatigue failure being the primary failure mode. Accurately predicting crack propagation rates before fatigue failure is crucial for the aerospace industry, providing fundamental data for fatigue life assessment based on damage tolerance methods. Existing research indicates that under high-cycle fatigue loading, the initiation and propagation stages of short cracks, preceding the long crack propagation stage, account for over 90% of the total lifespan of titanium alloy components. Therefore, accurately predicting the propagation rate of short cracks in structural components is of great significance. According to the current standard ASTM E647-24, a short crack is defined as a through-crack with a length relatively small compared to the microstructural scale, the mechanical scale of a continuum, or the physical size scale. Due to the lower degree of closure effect development in short cracks, under the same nominal crack driving force, the propagation rate of short cracks is faster than that of long cracks. Therefore, using long crack propagation data and prediction models to assess the fatigue life of components containing short cracks may lead to non-conservative life prediction results.

[0003] WAAM Ti-6Al-4V components are widely used in the aerospace field due to their excellent specific strength, superior fracture toughness, and outstanding thermal stability. The reheating of the deposited layers during the WAAM process leads to the formation of regularly distributed heat-affected zones (HAZs) between the Ti-6Al-4V deposits. These HAZs have been observed in both wire and powder additive manufacturing processes, and their microstructure differs from the deposited layers, typically characterized by coarsening of the α-lamellae. Existing research indicates that HAZs affect the fatigue crack propagation behavior of additively manufactured titanium alloys. For example, during the fatigue crack propagation process of WAAM TA15, both long crack deflection and microcrack initiation along the α-cluster boundaries were observed within the HAZ, collectively leading to a decrease in the main crack propagation rate. Similar phenomena were observed in WAAM Ti-6Al-4V ELI; when crack propagation reaches the α-cluster boundaries of the HAZ, resistance and deflection occur, resulting in a decrease in the local FCGR (fatigue crack growth rate). Furthermore, Lu et al. reported a periodic fluctuation in the fatigue crack growth rate (FCGR) between the heat-affected zone (HAZ) and adjacent deposited layers in laser melt deposition (LMD) Ti-6.5Al-3.5Mo-1.5Zr-0.3Si. This fluctuation manifests as a decrease in crack growth rate within the HAZ, followed by a rebound as the crack enters the adjacent deposited layer. This fluctuation is attributed to the microstructural differences between the HAZ and adjacent regions. Notably, a localized decrease in FCGR within the HAZ was observed in Ti-6Al-4V prepared by linear arc additive manufacturing (WAAM) and laser-engineered near-net-shape forming (LENS). This is attributed to the tortuous crack growth path within the coarsened microstructure of the HAZ. These studies reveal the mechanism by which the HAZ influences fatigue crack growth behavior in other widely used additive manufacturing processes and materials. However, differences in heat input and temperature gradients among different additive manufacturing processes lead to variations in the size of the heat-affected zone (HAZ). For example, the HAZ width of Ti-6Al-4V prepared by WAAM is approximately 500 μm, while the HAZ width of Ti-6Al-4V prepared using a more focused laser heat source is only about 150 μm. Furthermore, the microstructure of the HAZ of titanium alloys also differs among different additive manufacturing processes. For instance, the HAZ of the Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy prepared by laser cladding exhibits a transition from primary to secondary structures. The heat-affected zone (HAZ) of laser-clad deposited Ti-6Al-4V exhibits a two-phase microstructure, while the HAZ itself possesses a coarsened basketweave microstructure. Due to the differences in HAZ size and microstructure characteristics, research findings from other additive manufacturing processes and materials cannot be directly applied to the linear-arc additive manufacturing of Ti-6Al-4V. Furthermore, short cracks are far more sensitive to local microstructural features such as α-lamella thickness, grain boundaries, and crystal orientation than long cracks. However, existing research primarily examines the influence of the HAZ on the propagation behavior of long cracks in additively manufactured titanium alloys, with limited attention paid to its role in the propagation of short cracks. Given the significant sensitivity of short cracks to microstructural features, it is necessary to further investigate the influence mechanism of the HAZ on the propagation of short cracks in linear-arc additively manufactured Ti-6Al-4V. Summary of the Invention

[0004] To address the shortcomings of the prior art, the present invention aims to provide a method for predicting the fatigue crack propagation rate of the heat-affected zone in arc additive remanufacturing. This method can fit relevant parameters based on the fatigue crack propagation rate of the material deposition layer region in arc additive manufacturing, without damaging the heat-affected zone. The constructed heat-affected zone fatigue crack propagation rate prediction model can accurately predict the fatigue crack propagation rate of the heat-affected zone using non-destructive techniques.

[0005] Specifically, the present invention provides a method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing, which includes the following steps: S1. Sample Preparation: Ti-6Al-4V bulk materials were prepared using linear arc additive manufacturing technology. Samples were taken from the deposition layer and heat-affected zone of the Ti-6Al-4V bulk materials, and pre-formed notches were made as deposition layer and heat-affected zone samples for in-situ SEM fatigue testing. The pre-formed notch depth was [missing information]. ; S2. In-situ SEM fatigue testing of the samples: In-situ SEM fatigue testing was performed on the deposited layer samples and the heat-affected zone samples respectively, and the distance perpendicular to the loading direction between the crack tip and the notch root was recorded. and the corresponding cycle period Crack length used for crack propagation analysis for and sum; S3. Construct an initial fatigue crack propagation rate model and obtain the fitting parameter values ​​for the deposited layer sample and the heat-affected zone sample: An initial crack propagation rate model is constructed based on the correspondence between the stress intensity factor range and the fatigue crack propagation rate: ; in, This represents the fatigue crack propagation rate. For the range of stress intensity factors, These are the first and second parameters related to the material; S4. Calculate the fitting parameter values ​​for the deposited layer sample and the heat-affected zone sample. And the fatigue crack propagation rate model fitting mean line: the initial crack propagation rate model in step S3 is logarithmically calculated based on the fatigue crack propagation rate of the deposited layer sample and the heat-affected zone sample. and stress intensity factor range The linear correspondence in the logarithmic coordinate system yields the fitted values ​​of the first and second parameters of the deposited layer sample and the heat-affected zone sample, as well as the fitted mean line of the fatigue crack propagation rate of the deposited layer sample and the heat-affected zone sample in the logarithmic coordinate system. S5. Construct a prediction model for fatigue crack propagation rate in the heat-affected zone: in, The fatigue crack propagation rate of the heat-affected zone specimen. Samples from the deposition layer and heat-affected zone, respectively. Layer thickness, The first and second parameters are obtained by fitting the sediment layer sample. To correct the parameters, correct the parameters. The difference in intercepts of the fitting mean lines of fatigue crack propagation rates for deposited layer and heat-affected zone specimens in logarithmic coordinate system. Calculated; S6. Predict the fatigue crack propagation rate of the heat-affected zone (HAZ) specimen: For the Ti-6Al-4V specimen under test, obtain the crack propagation rate of the deposited layer specimen and the HAZ specimen. The thickness of the deposited layer is determined, and the first and second parameters of the deposited layer are fitted. Based on the fatigue crack propagation rate prediction model of the heat-affected zone constructed in step S5, the fatigue crack propagation rate of the heat-affected zone is predicted.

[0006] Preferably, in step S2, a computer-controlled electro-hydraulic fatigue testing system is used to perform in-situ SEM fatigue testing on samples taken from the deposition layer and heat-affected zone in a vacuum chamber.

[0007] Preferably, the Ti-6Al-4V block in step S1 is prepared using cold metal transfer arc welding technology.

[0008] Preferably, the specific steps in step S1 are as follows: S11. Forged Ti-6Al-4V alloy is used as the substrate material. The path of the alloy block is planned and set as a direct reciprocating scanning path. S12. The six-axis robotic arm drives the welding torch to move according to the planned path. The welding torch prepares Ti-6Al-4V alloy blocks under the protection of high-purity argon gas based on the principle of layer-by-layer deposition. S13. Samples are taken from the deposited layer and heat-affected zone of the Ti-6Al-4V alloy block to obtain deposited layer samples and heat-affected zone samples; S14. Use electrical discharge cutting to create a pre-made notch on one side of the center position of the sedimentary layer sampling and heat-affected zone sampling. S15. The in-situ SEM observation surfaces of the deposited layer and the heat-affected zone are mechanically polished and electrochemically polished in sequence to obtain the deposited layer sample and the heat-affected zone sample.

[0009] Preferably, the test parameters for the in-situ SEM process in step S2 are as follows: load control test under room temperature conditions, using 10Hz sine wave cyclic loading, stress ratio R=0.1, and maximum loading force of 1000N.

[0010] Preferably, in step S3, the cycle period recorded in step S2 is used. and corresponding crack length The fatigue crack propagation rate was calculated using the adjacent two-point method. Furthermore, the range of stress intensity factors was obtained based on crack length, loading force, stress ratio, and specimen size data. Thus, the fatigue crack propagation rate is obtained. and stress intensity factor range The correspondence between them.

[0011] Preferably, the stress intensity factor range The calculation formula is as follows: ; in, Stress ratio; For far-field tensile stress, The width of the specimen cross section, These are the geometric correction factor coefficients, expressed as: .

[0012] Preferably, in step S5, the difference in intercepts between the fitting mean lines of the fatigue crack propagation rates of the deposited layer sample and the heat-affected zone sample in the logarithmic coordinate system is: .

[0013] Preferably, in step S6, in-situ SEM fatigue testing is performed on the deposition layer to obtain the fitted parameter values ​​of the deposition layer. Deposition layer and heat-affected zone obtained using non-destructive measurement The thickness of the lamellar layers is incorporated into the fatigue crack propagation rate prediction model for the heat-affected zone, and the fatigue crack propagation rate of the heat-affected zone is predicted.

[0014] Preferably, in step S14, the welding wire is a Ti-6Al-4V wire with a diameter of 1-1.2 mm, the welding speed is 0.4-0.5 m / min, the wire feeding speed is 1.5-2 m / min, and the arc current is 150 amperes.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention provides a method for predicting the fatigue crack propagation rate of the heat-affected zone in arc additive manufacturing, which can accurately predict the fatigue crack propagation rate of the heat-affected zone based on the fatigue crack propagation rate of the material deposition layer region in arc additive manufacturing. It can accurately obtain the fatigue crack propagation rate of the heat-affected zone based on the fatigue crack propagation rate data of the material deposition layer region in arc additive manufacturing, solving the technical pain points of high difficulty in direct testing and low prediction accuracy caused by the heterogeneity of microstructure and complex stress state of the heat-affected zone, and providing reliable data support for the fatigue performance evaluation of the heat-affected zone.

[0016] (2) The method for predicting the fatigue crack propagation rate of the heat-affected zone in the electric arc additive remanufacturing of the present invention does not require complex and costly direct testing of the heat-affected zone. It can predict the relevant performance of the heat-affected zone by using test data that is easily obtained from the deposition layer area, which simplifies the evaluation process of fatigue crack propagation rate of additive remanufactured components, reduces testing costs and engineering application threshold, and improves the efficiency of technology implementation.

[0017] (3) The method for predicting the fatigue crack propagation rate of the heat-affected zone in electric arc additive remanufacturing of the present invention provides key technical support for fatigue life prediction, safety assessment and structural optimization design of additive remanufactured components, especially those in high-tech fields such as aviation and machinery where structural fatigue performance requirements are stringent. It helps to improve the reliability, stability and service safety of additive remanufactured products and expand the application scenarios of linear arc additive manufacturing technology in the field of high-end equipment remanufacturing.

[0018] (4) The method for predicting the fatigue crack propagation rate of the heat-affected zone in electric arc additive remanufacturing of the present invention establishes an effective correlation model between the deposition layer region and the fatigue crack propagation rate of the heat-affected zone, fills the technical gap in the accurate prediction of the fatigue performance of the heat-affected zone in the existing additive remanufacturing technology, provides a new technical idea for the optimization of additive remanufacturing process, defect control and performance improvement, and can ensure the accuracy of prediction. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the linear arc additive remanufacturing process and sampling location of the present invention; Figure 2XZ plane optical image obtained at any position of the alloy block of the present invention; Figure 3 This is a diagram showing the dimensions of the fatigue specimen of the present invention. Figure 4 SEM and optical microscopic images of the fatigue test specimens of this invention; Figure 5 This invention relates to an in-situ SEM fatigue testing system. Figure 6 The FCGR test data of this invention are represented by discrete markers, and the model mean fitting moving average is represented by a solid line; Figure 7 This is a flowchart of the fatigue crack propagation rate prediction method for the heat-affected zone in linear arc additive remanufacturing according to the present invention. Detailed Implementation

[0020] Specifically, this invention provides a method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing, such as... Figure 7 As shown, it includes the following steps: S1. Sample Preparation: Ti-6Al-4V bulk materials were prepared using linear arc additive manufacturing technology. Samples were taken from the deposition layer and heat-affected zone of the Ti-6Al-4V bulk materials, and a pre-formed notch was made on one side of the center of the sample as an in-situ SEM fatigue test sample. The depth of the pre-formed notch was [notch depth missing]. In a specific embodiment, the Ti-6Al-4V bulk material was prepared using cold metal transfer (CMT) arc welding technology.

[0021] The specific steps for linear arc additive manufacturing of test specimens are as follows: S11. Forged Ti-6Al-4V alloy was used as the substrate material. The path planning for the preparation of the alloy block was performed using additive manufacturing software, and the direct reciprocating scanning path scheme was set.

[0022] S12. The six-axis robotic arm drives the welding torch according to the planned path. The welding torch is based on the principle of layer-by-layer deposition. The welding wire is Ti-6Al-4V wire with a diameter of 1.2mm. Under the protection of high-purity argon gas with a gas flow rate of 15 liters / minute, a Ti-6Al-4V alloy block with a geometric dimension of 100mm×10mm×120mm is prepared. The main deposition parameters in this process are set as follows: welding speed 0.4m / min, wire feed speed 2m / min, and arc current 150 amperes.

[0023] S13. Samples are taken from the deposited layer and heat-affected zone of the Ti-6Al-4V alloy block to obtain deposited layer samples and heat-affected zone samples. In this embodiment, the geometric shape of the sample is dog bone shaped, with a center width of 2.5 mm and a thickness of 0.7 mm.

[0024] S14. Use electrical discharge machining to cut a prefabricated notch with a depth of 0.3 mm and a width of 0.2 mm on one side of the center position of the sediment layer sampling and heat-affected zone sampling.

[0025] S15. The in-situ SEM observation surfaces of the deposited layer and the heat-affected zone are mechanically polished and electrochemically polished in sequence to obtain the deposited layer sample and the heat-affected zone sample.

[0026] S2. In-situ SEM fatigue testing of the samples: In-situ SEM fatigue testing was performed on the deposited layer samples and the heat-affected zone samples respectively, and the distance perpendicular to the loading direction between the crack tip and the notch root was recorded. and the corresponding cycle period Crack length used for crack propagation analysis for and sum.

[0027] The specific test parameters for the in-situ SEM process are as follows: load control test under room temperature conditions, using 10Hz sine wave cyclic loading, stress ratio R=0.1, and maximum loading force of 1000N.

[0028] S3. Calculate the crack propagation rate and stress intensity factor of the specimen: based on the cycle number recorded in step S2. and crack length The fatigue crack propagation rate was obtained. Simultaneously, based on crack length, loading force, stress ratio, and specimen size data, the range of stress intensity factors is obtained. An initial fatigue crack propagation rate model was constructed, and the fitting parameter values ​​for the deposited layer sample and the heat-affected zone sample were obtained. In this embodiment, the initial fatigue crack propagation rate model was constructed using the Paris model. Specifically, the initial crack propagation rate model was constructed based on the correspondence between the stress intensity factor range and the fatigue crack propagation rate: in, These are the first and second parameters of the model, which are related to the material.

[0029] The crack propagation rate and stress intensity factor range of the specimen, and the corresponding relationship between them, are calculated as follows: For notched fatigue specimens, in the far-field tensile stress Range of stress intensity factors under action Calculation as follows in, Stress ratio; It is the width of the sample cross-section. These are the geometric correction factor coefficients, expressed as: According to the cycle period recorded in step S2 and corresponding crack length The fatigue crack propagation rate was calculated using the adjacent two-point method. And the range of stress intensity factor is obtained according to formula (3). Thus, the fatigue crack propagation rate is obtained. and stress intensity factor range The correspondence between them.

[0030] S4. Take the logarithm of the above expression (1) and calculate the fatigue crack propagation rate of the deposited layer sample and the heat-affected zone sample obtained in step S3. and stress intensity factor range By establishing a linear correspondence in the logarithmic coordinate system, the fitting parameter values ​​for the deposited layer sample and the heat-affected zone sample were obtained, respectively. And the fatigue crack propagation rate model fitting moving average.

[0031] S5. Construct a prediction model for fatigue crack propagation rate in the heat-affected zone: in, The fatigue crack propagation rate of the heat-affected zone specimen. Samples from the deposition layer and heat-affected zone, respectively. Layer thickness, The first and second parameters are obtained by fitting the sediment layer sample. To correct the parameters, The difference in intercepts represents the fitting mean lines of fatigue crack propagation rates for the deposited layer and heat-affected zone samples in logarithmic coordinates.

[0032] The difference in intercepts of the fitting mean lines of fatigue crack propagation rates for the deposited layer specimen and the heat-affected zone specimen in the logarithmic coordinate system in the established fatigue crack propagation rate prediction model is as follows: Solving for the given information yields the following results. It is 3.328.

[0033] Therefore, the predicted model for fatigue crack propagation rate of the heat-affected zone specimen is as follows: in, The fatigue crack propagation rate of the heat-affected zone specimen is predicted based on the fitted parameters of the deposited layer specimen. Samples from the deposition layer and heat-affected zone, respectively. Layer thickness, These are the first and second parameters of the Paris model obtained in step S3 for the deposition layer sample.

[0034] S6. Predicting the fatigue crack propagation rate of the heat-affected zone (HAZ) specimen: In the subsequent prediction, for the Ti-6Al-4V specimen to be tested, the deposition layer specimen and the HAZ specimen were obtained respectively. The thickness of the deposited layer is determined, and the first and second parameters of the deposited layer are obtained through fitting. Based on the fatigue crack propagation rate prediction model of the heat-affected zone constructed in step S5, the fatigue crack propagation rate of the heat-affected zone can be directly predicted without further destructive operations on the heat-affected zone. The parameters required for the fatigue crack propagation rate prediction model of the heat-affected zone can be obtained through non-destructive operations, thereby enabling direct prediction of the fatigue crack propagation rate of the heat-affected zone under non-destructive conditions.

[0035] In a specific embodiment, when the experimental parameters of the in-situ SEM fatigue test in S2 change, it is only necessary to perform an in-situ SEM fatigue test on the deposited layer sample, and obtain the current experimental parameters according to expression (1). And combined with non-destructive testing of the deposited layer samples and heat-affected zone samples By taking the thickness of the lamellar layers into expression (2), the fatigue crack propagation rate in the heat-affected zone can be directly predicted.

[0036] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

[0037] S1. Prepare the sample. For example... Figure 1 As shown, this embodiment uses 1.2mm diameter Ti-6Al-4V raw material wire to form a WAAM block with dimensions of 100mm×10mm×120mm along the Z-axis. Cold metal transfer (CMT) arc welding technology and a direct reciprocating scanning path scheme were employed in the WAAM process. Interlayer deposition was carried out under 99.99% high-purity argon gas protection, with the shielding gas flow rate maintained at a constant 15 liters / minute. The main deposition parameters were set as follows: torch travel speed 0.4 m / min, wire feed speed 2 m / min, and arc current 150 amperes. Three samples, A, B, and C, were taken from the WAAM-formed Ti-6Al-4V block by wire EDM. Samples A and C were taken from the deposition layer, while sample B was taken across the heat-affected zone.

[0038] like Figure 2 As shown, during the WAAM process of Ti-6Al-4V, reheating of the deposited layers creates a regularly spaced heat-affected zone (HAZ) between the deposited layers. The HAZ is approximately 500 micrometers wide. The microstructural difference between the HAZ sample and the deposited layer sample is mainly reflected in the short axis length of the α-lamella, i.e., the α-lamella thickness. The thickness of the α-lamella in the HAZ increases due to the thermal cycling during the additive manufacturing process.

[0039] like Figure 3 As shown, the fatigue test specimen is canine-shaped, with a center gauge length of 2.5 mm × 0.75 mm. A pre-made notch with a depth of 0.3 mm and a width of 0.2 mm is machined on one side of the center position of each specimen.

[0040] S2. In-situ SEM fatigue testing was performed on the samples. Before the in-situ SEM test, the samples were sequentially polished with 500#, 1000#, 1500#, and 2000# silicon carbide sandpaper, followed by mechanical polishing. Finally, surface preparation was completed by electrochemical polishing with a voltage of 25 volts and a current density of 450 mA / cm² for approximately 1 minute. The electrolyte was a mixed solution of 6% (v / v) perchloric acid, 34% (v / v) n-butanol, and 60% (v / v) methanol, and was maintained at a constant temperature using liquid nitrogen cooling. .

[0041] Figure 4 Scanning electron microscope (SEM) and metallographic micrographs of the fatigue test specimens are shown. It is foreseeable that short cracks in these specimens will initiate from the root of the notch. The notch is as follows: Figure 4 As shown in section (b), the main microstructures in the fatigue test specimens are basketweave and α-bundles. The basketweave consists of randomly interwoven α-lamellae, while the α-bundles are composed of parallel, ordered α-lamellae. Figure 4 Part (a) and Figure 4 As shown in section (e), short cracks in samples A and C propagate within the deposited layer. Figure 4 Part (c) and Figure 4 (d) shows that the short cracks in specimen B primarily propagate within the microstructure of the heat-affected zone. Furthermore, Figure 4 Middle (e) part and Figure 4 The C sample shown in section (f) contains acicular α' martensite with an aspect ratio exceeding 10, which is attributed to the high cooling rate in certain regions during the WAAM process.

[0042] like Figure 5 As shown, an in-situ SEM fatigue test was conducted in a vacuum chamber using a computer-controlled fatigue testing system. Load-controlled testing was performed at room temperature using a 10Hz sinusoidal cyclic loading method with a stress ratio R=0.1. A 50-micrometer-long pre-crack was created before the formal test. Loading could be paused at any time during the fatigue test for SEM image acquisition, and the number of cycles was recorded simultaneously. and observe crack length The observed crack length is the distance between the crack tip and the notch root perpendicular to the load direction. The crack length used for crack propagation analysis includes the initial notch depth. ,Right now The geometric dimensions, maximum load, final crack length, and final number of cycles for each specimen are summarized in Table 1.

[0043] Table 1 S3. Calculate the crack propagation rate and stress intensity factor of the specimen. For notched fatigue specimens, in the far-field tensile stress... Range of stress intensity factors under action The calculation is as follows: Where R is the stress ratio; It is the crack length, determined by the depth of the pre-fabricated notch. and observe crack length Add the two together; It is the width of the sample cross-section. These are the geometric correction factor coefficients, expressed as: Using the obtained crack length 'a' and cycle number 'N' data, the fatigue crack propagation rate is calculated using the adjacent two-point method. Figure 6 The crack propagation rate data are shown, where the horizontal axis represents the range of stress intensity factors. The vertical axis represents the crack size increment per cycle. That is, the fatigue crack propagation rate, where, For the crack size increment, This represents the increment of the cycle period. Ultimately, the fatigue crack propagation rate is described using the Paris model based on linear elastic fracture mechanics. and stress intensity factor range Correspondence in logarithmic coordinates: in, These are the first and second parameters of the material-related Paris model.

[0044] S4. Take the logarithm of the above expression (1) and calculate the fatigue crack propagation rate of the deposited layer sample and the heat-affected zone sample obtained in step S3. and stress intensity factor range By establishing a linear correspondence in the logarithmic coordinate system, the fitting parameter values ​​for the deposited layer sample and the heat-affected zone sample were obtained, respectively. And the mean square of the fatigue crack propagation rate model. The two parameters are estimated using linear regression after taking the logarithm of both sides of expression (8). Table 2 shows the Paris model fitting parameters for each fatigue test specimen. α-sheet thickness ( ) and root mean square error (RMSE) value. Figure 6 The solid lines in the figure show the Paris model fitting mean lines for different specimens, and the discrete markers are the original data from the fatigue crack propagation test.

[0045] Table 2 Figure 6 The FCGR data show that the FCGR of specimen B, sampled from the heat-affected zone (HAZ), is the lowest among all fatigue test specimens, indicating that crack propagation in the HAZ is inhibited by certain microstructural features. Secondly, the similar FCGR data of specimens A and C, sampled from the deposited layer, indicate that the FCGR in the deposited layer is similar at different cooling rates. Therefore, the microstructures generated by different cooling rates in the deposited layer exhibit similar crack propagation resistance. Based on these results, the crack propagation data of the deposited layer cannot be directly used to extrapolate the propagation rate of the HAZ. This invention proposes the following method to achieve accurate prediction of the fatigue crack propagation rate in the HAZ.

[0046] S5. Constructing a fatigue crack propagation rate prediction model for the heat-affected zone (HAZ). In WAAM Ti-6Al-4V, the microstructural differences between the HAZ and the deposited layer lead to differences in fatigue crack propagation behavior between different regions. The microstructural differences between the HAZ and the deposited layer are mainly reflected in the α-lamella thickness. Increasing the α-lamella thickness in the HAZ usually reduces the fatigue crack propagation rate in that region. Fatigue crack propagation rate studies based on damage tolerance design methods are often destructive, making it necessary to obtain more crack propagation data with fewer samples. Therefore, this invention introduces a correction coefficient related to the α-lamella thickness into the Paris model to correlate the fatigue crack propagation behavior of the deposited layer and the HAZ. By using fatigue crack propagation data from the deposited layer region to predict the fatigue crack propagation rate of the HAZ, this method helps to accurately predict the FCGR of crack propagation in different regions of WAAM Ti-6Al-4V, enabling more precise component safety assessments.

[0047] Figure 6 The FCGR test data show that the difference between the model fitting mean lines of the deposited layer sample and the heat-affected zone sample is mainly reflected in the slope. That is, the heat-affected zone of the sample. The difference is significantly lower than that of the deposited layer sample. Therefore, a formula (8) can be introduced with respect to this. Correction factor related to sheet thickness The FCGR data of the two regions were correlated by the difference in the intercept of the fitted mean lines between the deposited layer (DL) sample and the heat-affected zone (HAZ) sample. Table 2 shows the relationship between FCGR and α-layer thickness (…). The model, after introducing a correction coefficient based on the inverse correlation experimental facts, is expressed as follows: (9) in, These parameters are obtained by fitting the FCGR data of the sediment layer sample to the Paris mean. The FCGR data of the heat-affected zone are predicted based on the fitting parameters of the deposited layer sample. After taking the logarithm of both sides of equation (9), the model is as follows: Similar to expression (8) which takes the logarithm of both sides, in formula (10) This is the intercept of the Paris mean fitted line. Samples A and C from the deposition layer, deposited at a slower cooling rate, show that sample A does not contain α' martensite and represents a more representative microstructure morphology of the deposition layer. Therefore, by solving... Figure 6 The difference between the intercepts of the Paris mean fitted lines for the intermediate sedimentary layer sample (sample A) and the heat-affected zone sample (sample B) can be obtained. The α-lamellae thicknesses of samples A and B shown in Table 2 are 1.37 μm and 2.51 μm, respectively. Therefore, it can be obtained that... Formula (9) can be expressed as: S6. By applying the modified model, the fatigue crack propagation rate of the heat-affected zone can be accurately predicted using the FCGR test data of the deposited layer in specific applications, thereby achieving accurate prediction of the crack propagation rate in different regions of WAAM Ti-6Al-4V.

[0048] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for predicting fatigue crack growth rate of heat-affected zone in arc additive remanufacturing, characterized in that: It includes the following steps: S1. Sample Preparation: Ti-6Al-4V bulk materials were prepared using linear arc additive manufacturing technology. Samples were taken from the deposition layer and heat-affected zone of the Ti-6Al-4V bulk materials, and pre-formed notches were made as deposition layer and heat-affected zone samples for in-situ SEM fatigue testing. The pre-formed notch depth was [missing information]. ; S2. In-situ SEM fatigue testing of the samples: In-situ SEM fatigue testing was performed on the deposited layer samples and the heat-affected zone samples respectively, and the distance perpendicular to the loading direction between the crack tip and the notch root was recorded. and the corresponding cycle period Crack length used for crack propagation analysis for and sum; S3. Construct an initial fatigue crack propagation rate model and obtain the fitting parameter values ​​for the deposited layer sample and the heat-affected zone sample: An initial crack propagation rate model is constructed based on the correspondence between the stress intensity factor range and the fatigue crack propagation rate: ； in, This represents the fatigue crack propagation rate. For the range of stress intensity factors, These are the first and second parameters related to the material; S4. Calculate the fitting parameter values ​​for the deposited layer sample and the heat-affected zone sample. And the fatigue crack propagation rate model fitting mean line: the initial crack propagation rate model in step S3 is logarithmically calculated based on the fatigue crack propagation rate of the deposited layer sample and the heat-affected zone sample. and stress intensity factor range The linear correspondence in the logarithmic coordinate system yields the fitted values ​​of the first and second parameters of the deposited layer sample and the heat-affected zone sample, as well as the fitted mean line of the fatigue crack propagation rate of the deposited layer sample and the heat-affected zone sample in the logarithmic coordinate system. S5. Construct a prediction model for fatigue crack propagation rate in the heat-affected zone: ； in, The fatigue crack propagation rate of the heat-affected zone specimen. Samples from the deposition layer and heat-affected zone, respectively. Layer thickness, The first and second parameters are obtained by fitting the sediment layer sample. To correct the parameters, correct the parameters. The difference in intercepts of the fitting mean lines of fatigue crack propagation rates for deposited layer and heat-affected zone specimens in logarithmic coordinate system. Calculated; S6. Predict the fatigue crack propagation rate of the heat-affected zone (HAZ) specimen: For the Ti-6Al-4V specimen under test, obtain the crack propagation rate of the deposited layer specimen and the HAZ specimen. The thickness of the deposited layer is determined, and the first and second parameters of the deposited layer are fitted. Based on the fatigue crack propagation rate prediction model of the heat-affected zone constructed in step S5, the fatigue crack propagation rate of the heat-affected zone is predicted.

2. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 1, characterized in that: In step S2, a computer-controlled electro-hydraulic fatigue testing system is used to perform in-situ SEM fatigue testing on samples taken from the deposition layer and heat-affected zone in a vacuum chamber.

3. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 1, characterized in that: In step S1, the Ti-6Al-4V block is prepared using cold metal transfer arc welding technology.

4. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 3, characterized in that: The specific steps in step S1 are as follows: S11. Forged Ti-6Al-4V alloy is used as the substrate material. The path of the alloy block is planned and set as a direct reciprocating scanning path. S12. The six-axis robotic arm drives the welding torch to move according to the planned path. The welding torch prepares Ti-6Al-4V alloy blocks under the protection of high-purity argon gas based on the principle of layer-by-layer deposition. S13. Samples are taken from the deposited layer and heat-affected zone of the Ti-6Al-4V alloy block to obtain deposited layer samples and heat-affected zone samples; S14. Use electrical discharge cutting to create a pre-made notch on one side of the center position of the sedimentary layer sampling and heat-affected zone sampling. S15. The in-situ SEM observation surfaces of the deposited layer and the heat-affected zone are mechanically polished and electrochemically polished in sequence to obtain the deposited layer sample and the heat-affected zone sample.

5. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 1, characterized in that: The specific test parameters for the in-situ SEM process in step S2 are as follows: load control test under room temperature conditions, using 10Hz sine wave cyclic loading, stress ratio R=0.1, and maximum loading force of 1000N.

6. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 1, characterized in that: In step S3, the cycle period recorded in step S2 is used as a reference. and corresponding crack length The fatigue crack propagation rate was calculated using the adjacent two-point method. Furthermore, the range of stress intensity factors was obtained based on crack length, loading force, stress ratio, and specimen size data. Thus, the fatigue crack propagation rate is obtained. and stress intensity factor range The correspondence between them.

7. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 6, characterized in that: Stress intensity factor range The calculation formula is as follows: ； in, Stress ratio; For far-field tensile stress, The width of the specimen cross section, These are the geometric correction factor coefficients, expressed as: 。 8. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 1, characterized in that: In step S5, the difference in the intercepts of the fitting mean lines of the fatigue crack propagation rates of the deposited layer sample and the heat-affected zone sample in logarithmic coordinates is: 。 9. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 1, characterized in that: In step S6, in-situ SEM fatigue testing is performed on the deposition layer to obtain the fitted parameter values ​​of the deposition layer. Deposition layer and heat-affected zone obtained using non-destructive measurement The thickness of the lamellar layers is incorporated into the fatigue crack propagation rate prediction model for the heat-affected zone, and the fatigue crack propagation rate of the heat-affected zone is predicted.

10. The method for predicting the fatigue crack propagation rate in the heat-affected zone of arc additive remanufacturing according to claim 4, characterized in that: In step S14, the welding wire is Ti-6Al-4V wire with a diameter of 1-1.2mm, the welding speed is 0.4-0.5m / min, the wire feed speed is 1.5-2m / min, and the arc current is 150 amperes.

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