Jaber Ali Zghair
| Mustafa Abdulhussein Lafta | Ameer Abid Muslim | Laith Ali Zgair | Haider Fawzi Mahmood*
© 2026 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
The present study proposes a method to detect fatigue crack initiation and propagation in super duplex stainless steel 2507, particularly based on microstructural and crystallographic characteristics. Microstructure-fatigue property correlation has also been assessed using Scanning Electron Microscopy (SEM), Electron Backscatter Diffraction (EBSD), Digital Image Correlation (DIC), and in-situ fatigue tests. Over 250 fatigue crack initiation sites have been evaluated, and the results show that 78% of the fatigue crack initiations occur at austenite-ferrite phase boundaries, where the stress/strain concentration is higher compared to grain boundaries. Phase-dependent fatigue crack propagation indicates that the austenite phase crack propagation rate is 34% lower than ferrite phase crack propagation rates for cracks less than 25 μm. Fatigue crack propagation across the grain boundaries depends significantly on the misorientation between the grains. The fatigue crack propagation across the grain boundaries decreases from 85% for low-angle grain boundaries to less than 20% for high-angle grain boundaries. The DIC mapping also shows strain localization at the phase boundaries and triple points, which are the fatigue crack initiation locations. The Weibull analysis has shown that the shape parameter is approximately 3.2, which indicates a consistent fatigue response for cyclic loading conditions. It has also been observed that the microstructural features play a major role in fatigue crack initiation for duplex stainless steel 2507.
duplex stainless steel 2507, fatigue crack initiation, microstructure-property relationship, phase boundaries, Electron Backscatter Diffraction, Digital Image Correlation
Super duplex stainless steels (SDSSs) have found increased preference as fatigue-critical component materials in the offshore industry, marine industry, and chemical processing industry owing to superior mechanical and corrosion properties in hostile environments and fatigue loading conditions [1]. Among the family of SDSSs, UNS S32750 (SDSS 2507) finds extensive application in structural components of mechanical systems in which fatigue crack initiation and propagation play major roles in determining the service life of the components [2].
The unique two-phase microstructure of duplex stainless steels with nearly equivalent volume fractions of austenite and ferrite exhibits inherent mechanical heterogeneity at the microscale [3]. During fatigue loading conditions, the incompatibility in elasticity and plasticity of the two phases of the material will cause stress and strain concentration in the material, greatly influencing fatigue crack initiation and propagation of short cracks.
Previous studies have revealed that fatigue crack initiation in metallic alloys is greatly influenced by the inherent heterogeneity of the material at the microscopic scale, including grain boundaries, phase interfaces, and orientation relationships [4, 5]. In the case of duplex stainless steels, the austenite-ferrite phase boundary has been identified as a major site of fatigue crack nucleation in the material owing to the incompatibility of the elastic modulus of the two phases of the material [6, 7].
In spite of extensive research, quantitative understanding of fatigue crack initiation, as well as early crack growth, in super duplex grades is still in its infancy. Most of the research has been focused on macroscopic fatigue life, with less emphasis on short crack growth, which is more sensitive to microstructural effects [8]. In fact, recent research has shown that environmental effects such as seawater exposure, cathodic protection, as well as hydrogen uptake, can further accentuate microstructure-controlled fatigue in SDSSs, highlighting the need for a more detailed understanding of fatigue crack initiation/early growth mechanisms in duplex stainless steels [9, 10].
In recent years, advances in experimental characterization techniques, such as Electron Backscatter Diffraction (EBSD), Digital Image Correlation (DIC), and in-situ fatigue testing, now open up new avenues for investigating fatigue crack initiation/early growth in duplex stainless steels [11]. Electron backscattered diffraction can be used for a detailed characterization of crystallographic texture, grain misorientations, as well as deformation accumulation in duplex stainless steels [12]. DIC can be used for a direct measurement of strain localization, as well as plastic zone formation in duplex stainless steels, during cyclic fatigue loading. In fact, a combination of in-situ fatigue testing, electron backscattered diffraction, DIC, as well as high-resolution SEM fractography can now be used for a comprehensive investigation of fatigue crack initiation/early growth in duplex stainless steels [13, 14].
In this context, the present research aims at presenting a comprehensive experimental investigation of fatigue crack initiation/early growth in super duplex stainless steel 2507 using SEM, EBSD, DIC, as well as in-situ fatigue testing, complemented by statistical analysis. The specific research aims include: (i) identifying major microstructural crack initiation sites in duplex stainless steels, (ii) quantifying early crack growth in duplex stainless steels, (iii) investigating crystallographic misorientations in duplex stainless steels, as well as (iv) establishing quantitative microstructure-fatigue relationships in duplex stainless steels, which can be used for design/development of advanced duplex stainless steels.
Unlike previous studies that focus mainly on macroscopic fatigue life of duplex stainless steels, this work provides a quantitative microstructure-controlled analysis of fatigue crack initiation and early crack propagation in SDSS 2507 using an integrated SEM–EBSD–DIC–in-situ fatigue framework. The study establishes statistical relationships between phase boundaries, crystallographic misorientation, and crack propagation kinetics, which provide new insights for microstructure-based fatigue design of duplex stainless steels.
2.1 Material selection and processing
The material that is being examined in the present study is a commercially available super duplex stainless steel, UNS S32750, also known as 2507. The reason why this specific material has been selected for the present study is that it is being extensively used in industries that are known for being highly fatigue-prone. The material was machined into specimens of 50 mm length to facilitate fatigue testing and microstructural characterization. The chemical composition and microstructure were verified by a manufacturer who had subjected the material to solution annealing at 1080 ℃ for 30 minutes, followed by water quenching, to produce the optimum two-phase microstructure.
The heat treatment ensured that all undesirable intermetallic were dissolved, and at the same time, it ensured that a stable microstructure was achieved with nearly balanced amounts of austenite and ferrite. The chemical composition was also verified through optical emission spectroscopy (OES), which was carried out according to standard procedures, and it was confirmed that it complies with the chemical as per the applicable material specification standards. The results also confirmed that chromium, nickel, molybdenum, and nitrogen were at desired levels, which is important for super duplex stainless steels of high performance.
The chemical composition of the investigated UNS S32750, carried out through OES, which was carried out according to standard procedures. The chemical composition is shown in Table 1 and is consistent with the nominal composition of UNS S32750, and as a result, it is ensured that a stable microstructure is achieved.
Table 1. Chemical composition of super duplex stainless steel 2507 (wt.%)
|
Element |
Cr |
Ni |
Mo |
Mn |
Si |
N |
C |
Fe |
|
wt.% |
25.1 |
7.0 |
4.0 |
1.2 |
0.6 |
0.27 |
0.02 |
Bal. |
2.2.1 Sample preparation for multi-scale analysis
The specimens for microstructural characterization were prepared with special attention paid to avoiding surface damage and deformation, especially for materials that were to be prepared for high-resolution analysis. The procedures adopted were:
This microstructural preparation method for EBSD analysis is an optimized method, and strain-free surfaces with minimal topological relief between the austenite and ferrite microconstituents have been achieved.
2.2.2 Phase identification and quantitative analysis
Microstructural analysis of the alloy has been conducted using a variety of microstructural analysis techniques to ensure the accuracy of phase identification and quantitative analysis.
Initial microstructural analysis of the alloy has been conducted using a Zeiss Axioplan 2 optical microscope after etching the microstructure using Beraha’s etchant (100 ml H2O + 20 ml HCl + 0.3 g K2S2O5).
Phase volume fractions, grain size distribution, and morphological characteristics have been conducted according to ASTM E562 using a systematic point counting technique with a minimum of 1000 points per sample [15].
High-resolution microstructural analysis has been conducted using a JEOL JSM-7001F field emission SEM operating at accelerating voltages of 15-20 kV.
2.2.3 Electron Backscatter Diffraction analysis
EBSD analysis has been conducted to obtain microstructural data related to the fatigue crack initiation and propagation mechanisms. EBSD analysis has been conducted using an Oxford Instruments AZtec EBSD system coupled with a JEOL JSM-7001F FESEM [16].
2.3 Fatigue testing program
2.3.1 Standard fatigue testing
Fatigue tests were conducted with the aid of an MTS 810 servo-hydraulic testing machine under load control conditions. Dog-bone-shaped samples were machined according to ASTM E466 standards with a gauge length of 25 mm and gauge diameter of 6 mm. Meanwhile, surface roughness maintained Ra < 0.4 µm and stress concentration factor Kt < 1.05.
Testing conditions used sinusoidal loading with stress ratio R = 0.1 at 20 Hz frequency. All tests were performed in air at 23 ± 2 ℃ with stress range from 280 MPa to 500 MPa.
2.3.2 Interrupted fatigue testing
Interrupted fatigue tests were conducted in order to evaluate the crack initiation and early stages of crack propagation in the material under investigation. Interrupted tests were conducted at specified fractions of fatigue life (N/Nf = 0.1, 0.3, 0.5, 0.7, and 0.9). Interrupted tests were followed by surface analysis of the samples with the aid of SEM to identify locations of crack initiation and growth.
2.3.3 In-situ fatigue testing
Fatigue tests were conducted with the aim of understanding the process of crack nucleation and growth in the material under investigation with the aid of a Kammrath & Weiss micro-fatigue stage in the SEM chamber.
Miniature samples of size 15 mm × 3 mm × 1 mm with single-edge notch were used in the tests.
Tests were conducted under load control with stress ratio R = 0.1 and frequency of 0.1 Hz.
High-resolution images and videos were taken periodically throughout the tests.
2.4 Fatigue crack growth modeling
To interpret the experimentally observed fatigue crack growth, the fatigue crack growth rate was calculated using the classical Paris–Erdogan equation. The equation correlates the fatigue crack growth rate with the stress intensity factor range under cyclic loading conditions.
Crack growth rate:
$\frac{d a}{d N}=C(\Delta K)^m$ (1)
where, da/dN represents the fatigue crack growth rate, whereas C and m are the constants for the specific material under consideration, and ΔK represents the stress intensity factor range.
For a surface crack, the stress intensity factor range can be related as:
$\Delta K=Y \sigma \sqrt{ } \pi a$ (2)
where, Y represents the correction factor, σ represents the stress, and a represents the length of the crack. The aforementioned equations delineate the theoretical basis for comprehending the empirically observed fatigue fracture propagation rate in duplex stainless steel 2507.
2.5 Digital Image Correlation analysis
2.5.1 Digital Image Correlation system configuration
The local strain field surrounding the microstructural features and cracks was obtained by utilizing a high-resolution stereo DIC system with dual 5-megapixel CCD cameras and telecentric lenses for accurate sub-pixel measurement. The Vic-3D commercial software was utilized for image correlation and post-processing.
2.5.2 Digital Image Correlation measurement protocol
The optimized speckle pattern was used by employing a white titanium dioxide base coat with a black activated carbon speckle pattern, which gave a speckle size of 3 to 5 pixels and a surface coverage of 50 to 60%.
The parameters used for the measurement were a subset size of 25 × 25 pixels, a step size of 5 pixels, a strain resolution of 50 µstrain, and a displacement resolution of 0.01 pixels. Regular calibration was performed to ensure precise measurement.
2.6 Statistical analysis and data processing
2.6.1 Crack initiation statistics
The crack initiation behavior was statistically analyzed by making use of a database with a minimum of 50 crack initiation points per test condition. Crack initiation points were grouped based on the crack initiation point location with respect to the microstructure, crystallographic orientation, stress concentration, and proximity to the microstructure.
2.6.2 Electron Backscatter Diffraction data processing
The EBSD data processing was performed by making use of the Oxford AZtec software as well as the MTEX MATLAB toolbox to perform noise reduction, grain reconstruction with a threshold of 5°, grain boundary energy estimation by making use of the Read-Shockley model, Taylor factor estimation, and geometrically necessary dislocation density estimation.
2.7 Fractographic analysis
2.7.1 Fracture surface preparation
The fracture surfaces were cleaned thoroughly using ultrasonic baths containing acetone and ethanol, each for a period of 10 minutes. Subsequently, the fracture surfaces were dried using warm air, after which they were stored in a desiccated environment.
2.7.2 Multi-scale fractographic examination
The fracture surfaces were examined at low magnification using stereomicroscopy, which helped to analyze the crack initiation sites, crack growth, as well as the fracture sites. High-resolution SEM examination was carried out to investigate crack initiation, fatigue striations, spacing between striations, secondary crack networks, and phase-dependent fracture mechanisms.
The research methodology adopted in the current research is suitable for the systematic investigation of the effects of microstructures on fatigue crack nucleation and early stages of crack growth. The combination of techniques, i.e., EBSD, DIC, in-situ fatigue testing, and statistical analysis, provides a solid foundation for the development of a microstructure-based fatigue life prediction model, especially for super duplex stainless steels.
The overall experimental workflow adopted in this study, including microstructural characterization, fatigue testing, DIC strain analysis, and statistical crack evaluation, is summarized in Figure 1.
Figure 1. Experimental workflow for microstructure-controlled fatigue crack initiation and propagation in super duplex stainless steel 2507
Measurement uncertainty for a DIC system was estimated to be within ± 50 microstrain. Although optimization of speckle coating was performed for speckle pattern quality, a small change in material properties may arise due to speckle coating, which may influence crack initiation. However, it was observed that speckle coating does not significantly influence crack initiation locations when compared to SEM observations.
3.1 Fatigue crack initiation site analysis
A comprehensive statistical investigation of fatigue crack initiation locations indicates a significant influence of their location in the material’s microstructure, as demonstrated in Table 2. The most striking observation is that 78.2% of all fatigue cracks initiated at austenite-ferrite phase boundaries, thus reinforcing the significance of phase boundaries in controlling fatigue crack initiation in super duplex stainless steel 2507.
This trend significantly exceeds crack initiation at grain boundaries within individual phases, in contrast to single-phase alloys where grain boundaries usually dominate crack nucleation. The results are consistent with earlier observations in duplex stainless steels [3, 17], while the higher fraction observed here reflects the increased interface sensitivity of super duplex grades.
The high level of stress concentration factor at phase boundaries (2.8 ± 0.4) is attributed to the difference in the elastic modulus and strain incompatibility between the austenite and ferrite phases of the duplex stainless steel material, which are of different crystal structures: FCC for austenite and BCC for ferrite. The level of stress concentration at phase boundaries has been reported to be similar for duplex stainless steel by experimental and numerical studies [18, 19]. The highest stress concentration factor is at triple points with a value of 3.4 ± 0.6; however, their probability of occurrence is low.
Table 2. Statistical distribution of fatigue crack initiation sites and associated stress concentration factors
|
Initiation Site |
Percentage (%) |
Stress Concentration Factor |
Cycles to Initiation (×10³) |
|
Phase boundary (γ/α) |
78.2 |
2.8 ± 0.4 |
12.5 ± 3.2 |
|
Ferrite grain boundary |
12.4 |
2.1 ± 0.3 |
18.6 ± 4.1 |
|
Austenite grain boundary |
6.8 |
1.9 ± 0.2 |
21.4 ± 5.0 |
|
Triple junctions |
2.1 |
3.4 ± 0.6 |
8.8 ± 2.1 |
|
Others |
0.5 |
1.6 ± 0.2 |
24.0 ± 5.5 |
Figure 2 shows representative SEM images of fatigue crack initiation at austenite-ferrite phase boundaries and at grain boundaries of individual phases.
Figure 2. Scanning Electron Microscopy (SEM) images of fatigue crack initiation
3.2 Early crack propagation kinetics and phase-dependent behavior
Significant phase dependence behavior indicates a notable phase dependence, as presented in Table 3. For short crack lengths ranging from 10 to 25 μm, the crack growth rates in the austenitic phase are about 34% lower compared to those in the ferritic phase. This suggests that the austenitic phase has better resistance to early crack propagation.
The rates of crack growth measured experimentally can be related to the Paris model for crack growth due to fatigue. In accordance with the Paris relationship, increased stress intensity factors are related to increased rates of crack growth.
The lower rates of crack growth measured for the austenitic phase (Table 3) are related to a reduced stress intensity factor due to increased plastic deformation and crack blunting in the FCC structure of the austenitic phase.
Table 3. Phase-dependent early fatigue crack growth rates
|
Crack Length (µm) |
Austenite da/dN (mm/cycle) |
Ferrite da/dN (mm/cycle) |
Difference (%) |
|
10–25 |
(2.1 ± 0.4) × 10⁻⁶ |
(3.2 ± 0.6) × 10⁻⁶ |
34 |
|
50–100 |
(6.5 ± 1.1) × 10⁻⁶ |
(9.1 ± 1.4) × 10⁻⁶ |
29 |
|
100–200 |
(1.1 ± 0.2) × 10⁻⁵ |
(1.6 ± 0.3) × 10⁻⁵ |
31 |
These results are found to be consistent with the existing studies on duplex steels/super duplex steels [3, 20], where the improved fracture toughness and work hardening of austenite have been found to result in reduced crack growth rates. Recent high-resolution EBSD and TEM investigations have shown the improved capacity of austenite to absorb cyclic plasticity through improved dislocation activity [20, 21]. The crack growth rate along the interface is found to be intermediate due to the benefits of crack deflection and blunting [22].
3.3 Crack path characteristics and microstructural interactions
The crack path morphology varies substantially with crack propagation regions, as indicated in Table 4.
Table 4. Crack deflection, branching, and surface roughness characteristics
|
Crack Location |
Deflection Angle (°) |
Branching Frequency (/100 µm) |
Surface Roughness (µm) |
|
Austenite |
15.6 ± 8.2 |
1.8 ± 0.9 |
0.85 ± 0.25 |
|
Ferrite |
8.9 ± 4.1 |
0.9 ± 0.4 |
0.52 ± 0.18 |
|
Phase boundary |
22.4 ± 12.5 |
3.4 ± 1.8 |
1.12 ± 0.35 |
Phase boundary cracks show the most complex paths, with high deflection angles and branching frequency. This behavior is attributed to crystallographic mismatch and slip incompatibility across the interface, consistent with EBSD-based fatigue studies in duplex alloys [23].
Figure 3. Electron Backscatter Diffraction (EBSD) orientation map showing crack transmission across low- and high-angle boundaries
Figure 3 presents EBSD orientation maps illustrating crack transmission and deflection across low- and high-misorientation boundaries.
3.4 Strain distribution analysis using Digital Image Correlation
Quantitative strain measurements obtained by DIC are summarized in Table 5.
Table 5. Maximum principal strain and plastic zone size measured by Digital Image Correlation (DIC)
|
Microstructural Feature |
Max Strain (×10⁻³) |
Strain Concentration Factor |
Plastic Zone Size (µm) |
|
Triple junction |
4.9 ± 1.2 |
2.3 ± 0.5 |
22.8 ± 5.2 |
|
Phase boundary |
3.8 ± 0.8 |
1.8 ± 0.3 |
15.2 ± 3.5 |
|
Crack tip (10 µm ahead) |
8.2 ± 1.8 |
3.1 ± 0.6 |
45.6 ± 8.9 |
Strain localization is observed maximally in triple junctions and phase boundaries, in direct correlation with crack initiation statistics. Recent DIC-based investigations in duplex steels have reaffirmed the importance of strain localization in fatigue damage accumulation processes [24, 25]. Figure 4 shows some representative DIC strain maps that highlight localization in phase boundaries and triple junctions.
Figure 4. Digital Image Correlation (DIC) strain map showing strain localization at phase boundaries and triple junctions
The strain localization detected using DIC directly influences the stress intensity factor at the crack tip. Regions exhibiting high strain concentration correspond to higher local stress intensity factors, which promotes crack initiation and early crack growth according to the Paris law framework.
3.5 Electron Backscatter Diffraction–based crack transmission analysis
To further quantify the crystallographic influence on fatigue crack behavior, analyses using MTEX software were carried out. The Taylor factor maps obtained using MTEX software indicated that areas where the Taylor factor was high (> 3.2) experienced more localized strain and are preferred sites for fatigue crack nucleation, especially in areas around phase boundaries. Grain boundary energy calculations indicated that grain boundaries where the energy was high (> 0.8 J/m²) experienced a lower probability in crack transmission, which was in conformity with observations from EBSD maps where crack deflection was noted. The influence of grain boundary misorientation on crack transmission probability is depicted in Table 6.
Table 6. Effect of misorientation angle on crack transmission behavior
|
Misorientation Range (°) |
Transmission Probability (%) |
Deflection Angle (°) |
|
5–15 |
85.2 ± 8.5 |
12.3 ± 6.2 |
|
15–30 |
62.8 ± 12.1 |
28.5 ± 15.8 |
|
> 45 |
18.9 ± 9.8 |
62.8 ± 28.5 |
The grain boundary misorientation has a significant impact on the stress intensity factor at the crack tip. Grain boundaries that are high-angle act as barriers for crack transmission; this leads to a decrease in the value of ΔK experienced by the crack.
This explains the reduced likelihood of crack transmission for grain boundary misorientation above 45°. The study also proves that high-angle grain boundaries hinder crack transmission, which is in agreement with classical grain boundary engineering theory [26] and fatigue EBSD theory [21].
3.6 Statistical analysis of fatigue life distribution
Weibull analysis is shown in Table 7, confirming consistent fatigue response with a shape parameter of approximately 3.2.
Table 7. Weibull fatigue life parameters
|
Stress Level (MPa) |
β |
η (cycles) |
N10% |
N90% |
|
300 |
3.3 |
7.2 × 10⁶ |
3.9 × 10⁶ |
1.1 × 10⁷ |
|
400 |
3.1 |
4.3 × 10⁵ |
2.2 × 10⁵ |
6.8 × 10⁵ |
The high Weibull modulus indicates reduced scatter and reliable fatigue performance, consistent with recent probabilistic fatigue studies on duplex steels [27].
3.7 Fractographic analysis and failure mechanisms
Quantitative fractographic analysis results are presented in Table 8, which shows that fatigue striations were found to be the predominant feature, occupying 68.5 ± 8.2% of the fracture surface. This confirms that the failure process is predominantly controlled by fatigue crack growth. The presence of quasi-cleavage features (18.2 ± 5.1%) indicates that there were localized brittle-like features, which can be ascribed to microstructural effects and stress concentration phenomena.
Table 8. Distribution of fracture surface features
|
Feature |
Area Fraction (%) |
|
Fatigue striations |
68.5 ± 8.2 |
|
Quasi-cleavage |
18.2 ± 5.1 |
|
Secondary cracks |
3.1 ± 1.5 |
|
Ductile dimples |
8.9 ± 3.2 |
The presence of secondary cracks (3.1 ± 1.5%) indicates that there were crack branching phenomena, which had a localized effect on the crack growth process. The presence of ductile dimples (8.9 ± 3.2%) was found to be localized to the final fracture region, which indicates that ductile overload was present after extensive fatigue damage accumulation [28], Similar fractographic features and failure mode transitions have been reported in recent SEM-based studies, highlighting the role of local stress state and material heterogeneity in governing fracture morphology [29].
The fractography presented in Figure 5 show the presence of fatigue striations and quasi-cleavage features, which confirms the fractographic analysis results. It can therefore be confirmed that the material had failed due to fatigue, as indicated by the mechanical testing results.
Figure 5. Scanning Electron Microscopy (SEM) fractography showing fatigue striations and quasi-cleavage features in ferrite
3.8 Microstructure-property relationships and design implications
From the results, it is evident that significant microstructure-property relationships relevant to fatigue optimization of duplex stainless steels, along with their design implications, are as follows:
Overall, the integration of EBSD, DIC, fractographic analysis, and statistical modeling provides a robust framework for microstructure-based fatigue design of duplex stainless steels. These findings establish actionable processing–structure–property relationships that can be directly implemented in industrial material design and optimization.
The current research offers a detailed experimental investigation of fatigue crack initiation and early-stage propagation in super duplex stainless steel 2507. Emphasis is given to microstructural and crystallographic effects. Advanced characterization methods are used to establish quantitative correlations between microstructure and fatigue properties.
In the case of fatigue crack initiation, the results show that ~78% of fatigue crack initiation takes place at the austenite-ferrite interface. Triple junctions also show high stress/strain concentration, hence high fatigue crack nucleation rates.
In terms of early-stage propagation, the results indicate that austenite consistently has lower rates of fatigue crack propagation compared to ferrite. This is because ferrite exhibits higher crack growth rates due to lower work-hardening capability compared with austenite. The propagation rates at the interface are intermediate. EBSD results on crystallographic aspects indicate that the transmission of fatigue cracks through phase boundaries depends on boundary misorientation. Low-angle boundaries allow for transmission, while high-angle boundaries impede transmission, resulting in deflection. DIC results indicate that strain localization is highest at triple junctions and phase interfaces. Fatigue life results indicate that the fatigue life follows a Weibull distribution with high shape parameters. This implies low scatter in results and high reproducibility. Fractographic analysis also provides evidence of fatigue characterization in 2507.
Quantitative correlations between microstructure and fatigue properties are established. Texture control is also shown to be effective in enhancing fatigue resistance. The paper also demonstrates the applicability of probabilistic design. The integrated experimental approach is also shown to be useful in the analysis of complex multi-phase materials.
|
a |
crack length |
|
da/dN |
fatigue crack growth rate |
|
C |
paris law material constant |
|
m |
paris law exponent |
|
ΔK |
stress intensity factor range |
|
Kt |
stress concentration factor |
|
σ |
applied stress amplitude |
|
R |
stress ratio (σ_min/σ_max) |
|
N |
number of loading cycles |
|
Nf |
number of cycles to failure |
|
β |
weibull shape parameter |
|
η |
weibull scale parameter |
|
Greek symbols |
|
|
ε |
local strain |
|
α |
phase fraction parameter |
|
β |
weibull distribution shape parameter |
|
θ |
grain boundary misorientation angle |
|
µ |
friction or slip coefficient |
|
Subscripts |
|
|
γ |
austenite phase |
|
α |
ferrite phase |
|
tip |
crack tip |
|
max |
maximum value |
|
min |
minimum value |
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