A method of predicting a type of origin of fatigue failure of an additively manufactured metallic material

Abstract

The application provides a method for predicting fatigue origin types of an additive manufacturing metal material, which comprises the steps of acquiring parameter data, a defect threshold value and a difference comparison of driving forces, distinguishing additive manufacturing microstructures and additive defect origin types, and laying a foundation for additive manufacturing fatigue performance prediction and damage tolerance design.

Description

Technical Field

[0001] This invention relates to the field of fatigue failure and service safety of metallic materials, and more specifically, to a method for predicting the origin type of fatigue failure in additively manufactured metallic materials. Background Technology

[0002] Additive manufacturing inevitably produces defects such as porosity. Although optimizing process parameters can reduce defect levels to some extent, there is still no effective method to completely eliminate them. Additive manufacturing defects have a relatively small impact on the strength and toughness of the additive structure, but they have a significant effect on fatigue performance. Currently, the influence of these defects on the microstructure and fatigue initiation mechanisms of short cracks in additively manufactured metallic materials is not fully understood. Furthermore, existing methods do not consider the fatigue behavior of short cracks in their criteria. Summary of the Invention

[0003] Based on this, in order to accurately predict the fatigue performance of additively manufactured metallic materials and thus ensure the service reliability of additively manufactured components, this invention provides a method for predicting the fatigue failure origin type of additively manufactured metallic materials, the specific technical solution of which is as follows:

[0004] Step 1: Conduct crack propagation rate tests on additively manufactured metallic materials to obtain the long crack threshold parameter ΔK. th，L Among these, the crack propagation rate da / dN and stress intensity factor range ΔK data were obtained, and da / dN = 10 was determined. -7 ΔK corresponding to mm / cycle, i.e., the long crack threshold parameter ΔK th，L ;

[0005] Step two: Conduct fatigue performance tests on additively manufactured metallic materials to obtain the fatigue limit range Δσ of the defect-free additively manufactured metallic materials. w Among them, SN curve tests of level 5 or 6 are conducted and fatigue limits are determined to obtain the fatigue limit range;

[0006] Step 3: Conduct axial constant-amplitude low-cyclic fatigue tests and uniaxial tensile tests on the additively manufactured metallic materials. Specifically, the axial constant-amplitude low-cyclic fatigue test yields the cyclic yield stress σ′ by fitting the cyclic stress-strain curve using equations. Y K′ and n′,

[0007] Where Δσ is the cyclic stress, Δε is the cyclic strain, E is the elastic modulus, K′ is the cyclic strength coefficient, and n′ is the cyclic strain hardening exponent; stress-strain data are obtained by performing uniaxial tensile tests on additively manufactured metallic materials, and the elastic modulus E is obtained by fitting the data.

[0008] Step 4: Calculate and determine the stress intensity factor ΔK for plastic correction.p ,in, E′ is E under plane stress.

[0009] ΔK is the range of stress intensity factor, f(ΔL) r () is a cyclic plasticity correction function based on the cyclic toughness ratio, where the cyclic toughness ratio is...

[0010]

[0011] Where, Δσ ref For the reference stress range, the cyclic plasticity correction function f(ΔL) based on the cyclic toughness ratio. r ), which is represented as

[0012]

[0013] Step 5: Determine the short crack threshold value ΔK th , where ΔK th，eff ΔK is the intrinsic threshold value. th，eff ≈χ·10 -5 E and χ are correction factors. ΔK is calculated using the Chepetii model of short crack propagation behavior. th ;

[0014] Step six: Determine the criteria for predicting the fatigue initiation type of additively manufactured metallic materials. This includes calculating the stress intensity factor and short crack threshold value after plastic correction. The difference between these two values ​​yields the residual driving force for fatigue initiation, ΔK. dm =ΔK p -ΔK th Its critical value is And compare the residual driving force ΔK at the origin of fatigue. dm Its critical value The numerical value.

[0015] Furthermore, for additive manufacturing metal materials, hot isostatic pressing technology is used to process the additive manufacturing test metal materials to produce additive manufacturing materials with minimal porosity, and then samples are taken to carry out fatigue high-cycle mechanical property tests.

[0016] Furthermore, non-destructive testing techniques were used to identify the region with the lowest porosity in the additively manufactured metallic material. Samples were then taken for high-cycle fatigue performance testing, including SN curve tests at levels 5 or 6, and the fatigue limit was determined. Axial loading was selected as the load method, with a constant amplitude sine wave load waveform. The test reached 10 cycles. 7 The experiment was stopped, and fatigue limit determination of additive manufacturing titanium alloys was carried out, along with tests at stress levels below level 4.

[0017] Furthermore, the stress intensity factor ΔK for plastic correction is determined. p When the reference stress range is obtained, it is given by the following formula:

[0018]

[0019] Where ω is the shape correction factor, a is the internal defect radius and the surface defect depth, and σ is the surface defect depth. app The stress range at the far end is expressed by the cyclic stress-strain constitutive relation as follows:

[0020]

[0021] ΔK p Represented as

[0022] in

[0023] Furthermore, when comparing the residual driving force of fatigue origin with its critical value, when At that time, the fatigue initiation mechanism was dominated by additive manufacturing defects; when At that time, the fatigue origin mechanism was dominated by microstructure.

[0024] Furthermore, predict the fatigue origin type of additively manufactured metallic material structures, including obtaining the maximum defect size inside or on the surface of the additively manufactured metallic material structure. Compare ΔK dm and Predicting the fatigue origin type in additive manufacturing of metallic materials.

[0025] Beneficial effects: (1) The fatigue origin types of smooth fatigue specimens of additively manufactured metal materials vary greatly, and there are microstructure origin cracking, defect origin cracking and the two competing origin cracking mechanisms, which makes it impossible for existing design methods to design accurately. This invention aims to predict the fatigue origin type of additively manufactured metal materials, thereby distinguishing additive components with different fatigue origin types, and then selecting the appropriate design method to accurately design the additive fatigue components, and finally ensuring the service reliability of the additive components; (2) The difference in fatigue origin types of additively manufactured metal materials leads to a certain degree of dispersion in fatigue performance. This invention predicts the fatigue origin type of additively manufactured metal materials, thereby considering the factors of different fatigue origin mechanisms in the prediction model, improving the accuracy of fatigue performance prediction of additively manufactured metal material structures, and thus accurately evaluating the safety of additive fatigue metal material structures. Attached Figure Description

[0026] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0027] Figure 1 This is a flowchart of a method for predicting the fatigue failure origin type of additively manufactured metallic materials according to an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the fatigue origin type prediction results of additive manufacturing titanium alloy according to an embodiment of the present invention. Specific implementation methods

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific implementation methods described herein are only for explaining the invention and do not limit the scope of protection of the invention.

[0030] It should be noted that when an element is said to be "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is said to be "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only implementation methods.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of this invention is for the purpose of describing particular implementations only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0032] In this invention, "first" and "second" do not represent a specific quantity or order, but are merely used to distinguish names.

[0033] A method for predicting the fatigue failure origin type of additively manufactured metallic materials includes the following steps: Step 1, obtaining the long crack threshold parameter ΔK. th，L According to GB / T6398, crack propagation rate tests were conducted on additively manufactured metallic materials to obtain crack propagation rate da / dN and stress intensity factor range ΔK data, and da / dN = 10 was determined. -7 ΔK corresponding to mm / cycle is the long crack threshold parameter ΔK. th，L Step 2: Obtain the fatigue limit range Δσ of the defect-free additive manufacturing metal material. wAccording to GB / T3075, fatigue performance tests of additively manufactured metallic materials were conducted, including SN curve tests with at least 5 stress levels. Axial loading was selected as the loading method, and the load waveform was a constant amplitude sine wave. The test was stopped after 107 cycles. Simultaneously, the fatigue limit of the additively manufactured titanium alloy was determined using the lifting-lowering method, with the stress level controlled within 4 levels. Finally, the fatigue limit was obtained. Step three involved obtaining the elastic modulus E and the cyclic stress-strain constitutive parameter σ′. Y According to GB / T228, uniaxial tensile tests were conducted on additively manufactured metallic materials K′ and n′ to obtain stress-strain data. The elastic modulus E was obtained by fitting the elastic stage. According to GB / T15248, axial constant amplitude low-cyclic fatigue tests were conducted on additively manufactured metallic materials to obtain cyclic stress-strain curves. The cyclic yield stress σ′ was obtained directly from the strain that could pass through the 2% offset elastic segment on the curve. Y K′ and n′ were obtained by fitting the Ramberg-Osgood constitutive equation.

[0034]

[0035] Where Δσ is the cyclic stress, Δε is the cyclic strain, E is the elastic modulus, K′ is the cyclic strength coefficient, and n′ is the cyclic strain hardening exponent; Step four, determine the stress intensity factor ΔK for plastic correction. p Since the microstructure and the plastic zone in the short crack stage have a significant impact, a plastic-corrected stress intensity factor is needed to characterize the driving force in the short crack stage. The plastic-corrected stress intensity factor is expressed as follows: Where E′ is E under plane stress and E / (1-ν) under plane strain. 2 ), where ΔJ is the cyclic J-integral and ν is Poisson's ratio, the cyclic J-integral ΔJ can be obtained from the following formula.

[0036]

[0037] Where ΔK is the range of stress intensity factor, f(ΔL) r () is a cyclic plasticity correction function based on the cyclic toughness ratio, where the cyclic toughness ratio is...

[0038]

[0039] Where, Δσ ref For the reference stress range, the cyclic plasticity correction function f(ΔL) based on the cyclic toughness ratio. r ) represents

[0040]

[0041] The reference stress range can be obtained by the following formula:

[0042]

[0043] Where ω is the shape correction factor, which is 1 for circular defects and 0.5 for semi-circular defects; a is the internal defect radius and the surface defect depth; σ app The range of applied stress at the far end; the reference strain range can be expressed by the cyclic stress-strain constitutive relation as follows:

[0044]

[0045] ΔK p Represented as

[0046]

[0047] in When the defect is on the surface, Y = 0.65; when the defect is inside, Y = 0.5; Step 5: Determine the short crack threshold value ΔK. th The Chepetii model of short crack propagation behavior is used, i.e.

[0048]

[0049] in, The original defect size is ΔK. th，eff The intrinsic threshold value can be obtained from the following formula: ΔKth,eff≈χ·10 -5 ·E,

[0050] The intrinsic defect size is determined by the following formula.

[0051]

[0052]

[0053] Where E is the elastic modulus, χ is the correction factor, and for E = 25–250 MPa, χ is 1.64. ΔK is then obtained. th Step six: Determine the criteria for predicting the fatigue origin type of additively manufactured metallic materials. For the defect size of microstructure origin, use the intrinsic defect size. Replacement, fatigue origin, residual driving force ΔK dm =ΔK p -ΔK th The critical value is for The time is a function of Δσ and Y. The difference between the stress intensity factor and the short crack threshold value after plastic correction is calculated and defined as the residual driving force for fatigue initiation, ΔK. dm =ΔK p -ΔK th Compare ΔK dm and Size; Step 7, predict the fatigue origin type of the additively manufactured metallic material structure by obtaining the maximum defect size inside or on the surface of the additively manufactured metallic material structure through non-destructive testing methods, such as X-ray, ultrasonic, or other advanced non-destructive testing methods. The stress range Δσ of additively manufactured metallic material structures needs to be determined in advance, and Y is based on the maximum defect size. Location determined: for surface or near-surface defects, Y = 0.65; for internal defects, Y = 0.5. ΔK of the additive structure... th，L , Δσ w 、E、σ′ Y 、K′、n′、 Δσ and The fatigue residual driving force ΔK has been obtained and calculated through the aforementioned steps. dm By comparing ΔK dm and Predict the types of fatigue origins in additively manufactured metallic materials.

[0054] In one embodiment, for additive manufacturing of TC11 titanium alloy, hot isostatic pressing (HIP) is used to process the additive manufacturing test TC11 titanium alloy to produce an additive manufacturing TC11 titanium alloy with minimal porosity, and then samples are taken to conduct fatigue high-cycle mechanical property tests; if HIP is not used, non-destructive testing technology is used to detect the region with minimal porosity in the additive manufacturing TC11 titanium alloy, and samples are taken to conduct fatigue high-cycle performance tests.

[0055] like Figure 2 As shown, in one embodiment, when At that time, the fatigue initiation mechanism was dominated by additive manufacturing defects; when The fatigue origin mechanism is dominated by microstructure, which is the predicted result of the fatigue origin type criterion for additively manufactured titanium alloy TC11.

[0056] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0057] The embodiments described above merely illustrate several implementation methods of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A method for predicting the origin type of fatigue failure in additively manufactured metallic materials, characterized in that... Includes the following steps: Step 1: Conduct crack propagation rate tests on additively manufactured metallic materials to obtain the long crack threshold parameter ΔK. th，L Among these, the crack propagation rate da / dN and stress intensity factor range ΔK data were obtained, and da / dN = 10 was determined. -7 ΔK corresponding to mm / cycle, i.e., the long crack threshold parameter ΔK th，L ; Step two: Conduct fatigue performance tests on additively manufactured metallic materials to obtain the fatigue limit range Δσ of the defect-free additively manufactured metallic materials. w Among them, SN curve tests of level 5 or 6 are conducted and fatigue limits are determined to obtain fatigue limits; Step 3: Conduct uniaxial tensile tests on the additively manufactured metallic materials, including axial constant-amplitude low-cyclic fatigue tests to obtain the cyclic yield stress σ′. Y Stress-strain data were obtained by performing uniaxial tensile tests on additively manufactured metallic materials using K′ and n′, and the elastic modulus E was obtained by fitting the data. Step 4: Calculate and determine the stress intensity factor ΔK for plastic correction. p ,in, E′ is E under plane stress. ΔK is the range of stress intensity factor, f(ΔL) r () is a cyclic plasticity correction function based on the cyclic toughness ratio, where the cyclic toughness ratio is... Where, Δσ ref For the reference stress range, the cyclic plasticity correction function f(ΔL) based on the cyclic toughness ratio. r ), which is represented as Step 5: Determine the short crack threshold value ΔK th , where ΔK th，eff ΔK is the intrinsic threshold value. th，eff ≈χ·10 -5 E and χ are correction factors. ΔK is calculated using the Chepetii model of short crack propagation behavior. th ; Step six: Determine the criteria for predicting the fatigue initiation type of additively manufactured metallic materials. This includes calculating the stress intensity factor and short crack threshold value after plastic correction. The difference between these two values ​​yields the residual driving force for fatigue initiation, ΔK. dm =ΔK p -ΔK th Its critical value is And compare the residual driving force ΔK at the origin of fatigue. dm Its critical value The numerical value.

2. The method for predicting the origin type of fatigue failure in additively manufactured metallic materials according to claim 1, characterized in that, For additive manufacturing of metallic materials, hot isostatic pressing (HIP) is used to process the additive manufacturing test metallic materials to produce additive manufacturing materials with minimal porosity, and then samples are taken to carry out fatigue high-cycle mechanical property tests.

3. The method for predicting the fatigue failure origin type of additively manufactured metallic materials according to claim 1, characterized in that, Non-destructive testing techniques were used to identify the region with the lowest porosity in additively manufactured metal materials, and samples were taken to conduct fatigue high-cycle performance tests.

4. The method for predicting the fatigue failure origin type of additively manufactured metallic materials according to claim 1, characterized in that, Fatigue performance tests were conducted on additively manufactured metallic materials, including SN curve tests at levels 5 or 6 and fatigue limits were determined. Axial loading was selected as the loading method, with a constant amplitude sine wave waveform. The test reached 10 cycles. 7 The experiment was stopped, and the fatigue limit of the additively manufactured titanium alloy was determined using the lifting method, and tests were conducted at stress levels less than level 4.

5. The method for predicting the fatigue failure origin type of additively manufactured metallic materials according to claim 1, characterized in that, Fitting the equation Where Δσ is the cyclic stress, Δε is the cyclic strain, E is the elastic modulus, K′ is the cyclic strength coefficient, and n′ is the cyclic strain hardening exponent.

6. The method for predicting the fatigue failure origin type of additively manufactured metallic materials according to claim 1, characterized in that, Determine the stress intensity factor ΔK for plasticity correction. p When the reference stress range is obtained, it is given by the following formula: Where ω is the shape correction factor, α is the internal defect radius and the surface defect depth, and σ app The stress range at the far end is expressed by the cyclic stress-strain constitutive relation as follows: ΔK p Represented as in 7. The method for predicting the origin type of fatigue failure in additively manufactured metallic materials according to claim 1, characterized in that, When comparing the residual driving force of fatigue origin with its critical value, when At that time, the fatigue origin mechanism was dominated by additive manufacturing defects; when At that time, the fatigue origin mechanism was dominated by microstructure.

8. The method for predicting the origin type of fatigue failure in additively manufactured metallic materials according to claim 1, characterized in that, Predicting the fatigue origin type of additively manufactured metallic structures, including obtaining the maximum defect size inside or on the surface of the additively manufactured metallic structure. Compare ΔK dm and Predict the types of fatigue origins in additively manufactured metallic materials.

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