Submitted:
18 November 2025
Posted:
20 November 2025
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Abstract

Keywords:
1. Introduction
2. Microstructure of AM Ti64
- (a)
- Stress relieving (480-800 °C): Stress-relieving treatments reduces residual stresses in the AM build while causing minimal coarsening of the α′ martensite. It increases ductility and dimensional stability while largely preserving the as-built microstructural features [38].
- (b)
- Super-transus heat treatment (β-annealing): In this heat treatment procedure, Ti64 is heated 20–200 °C above its β-transus temperature (995 °C [29,35,39]) to fully convert the microstructure to the β phase. Controlled cooling then produces equiaxed, recrystallized prior-β grains, reducing build-direction texture and improving mechanical isotropy[35].
- (c)
- Sub-transus treatment (recrystallization annealing): Heating Ti64 to ~800–950 °C (within the α+β two-phase field) [40] triggers recrystallization of both hcp α and bcc β grains. Controlled soak times and cooling rates refine grain size, adjust α/β phase fractions, and enable a tailored balance of strength and ductility.
- (d)
- Solution treatment and aging (STA): Solution treatment is conducted just below or above the β-transus (995 °C) to dissolve metastable α′ and homogenize the β matrix. After quenching or air cooling, aging at 400–750 °C precipitates fine α phases, which strengthen the alloy while retaining ductility [38].
- (e)
- Hot isostatic pressing (HIP) (800–1200 °C, 100–200 MPa): HIP closes internal pores and homogenizes the microstructure in AM Ti64 [41]. It is classified into super-transus HIP (1000–1200 °C) and sub-transus HIP (800–950 °C), with further distinctions based on pressure, hold time, and cooling rate, each influencing the microstructure and mechanical behavior.
3. FCG Behavior of AM Ti64
3.1. Build Orientation
3.2. Mean Stress Effect
3.3. Post-Processing Heat Treatment
3.4. Combined Factors
3.5. Effect of Processing Parameters
3.6. Repairs
3.7. Variable Amplitude Loading
3.8. Environmental Assisted FCG
3.9. Temperature Effects
3.10. Small Cracks
4. Perspectives for Future Research
- Build Orientation Effects: The influence of build orientation on FCG behavior in AM Ti64 remains inconclusive in the current literature. Some studies report a strong dependence of FCG resistance on build orientation, whereas others find only minimal effects. These divergent results are primarily attributed to variations in residual stress states, microstructural characteristics, and defect distributions associated with specific printing directions. Most research has focused on horizontal and vertical specimen orientations; however, real-world components often experience multiaxial loading and complex geometries, which promote crack propagation along off-axis directions [117]. Evaluating FCG in off-axis orientations is therefore essential to fully capture the effects of anisotropy and layer-related defects.
- 2.
- Mean Stress Effects and Microstructural Sensitivity: The influence of mean stress, typically characterized by the stress ratio, on FCG in AM Ti64 is well documented. Higher stress ratios generally lead to faster FCG and lower ΔKth [13,118]. However, the combined effects of mean stress and microstructural features such as grain orientation, α/β morphology, and porosity on crack closure are not well understood, particularly during the transition from microstructure-sensitive near-threshold behavior (Region I) to steady-state crack growth (Region II). Addressing this knowledge gap requires targeted research that integrates comprehensive microstructural characterization with in-situ FCG testing under varying mean stress conditions. By combining advanced imaging and analysis techniques with real-time crack growth measurements, researchers can directly observe how specific microstructural features and applied mean stresses interact to influence crack closure and subsequently FCG. These insights are essential for developing more robust design standards for AM Ti64 components, ultimately ensuring greater damage tolerance and structural reliability.
- 3.
- Process Parameters and Defect Populations: FCG behavior in AM Ti64 is sensitive to process parameters such as laser power, scan speed, and hatch spacing, since these factors determine the resulting microstructure and the distribution of defects including pores and lack-of-fusion defects. Few studies [79,95,109] have systematically isolated the effects of individual process parameters, especially for small cracks where conventional fracture mechanics models may not be fully applicable. Achieving a deeper understanding of how these processing conditions impact microstructure and fatigue performance across different build orientations and loading scenarios is essential for optimizing AM processes and improving FCG resistance in AM Ti64.
- 4.
- Repairs, Interfaces, and Service-Relevant Conditions: As AM is increasingly employed for component repair, it has become crucial to understand FCG behavior at repair interfaces. Even when DED techniques closely replicate the substrate microstructure, FCG rates at the bond line are often higher than those observed in wrought Ti64 [88,110] . The specific impacts of interface microstructure on FCG performance are still not well characterized. Furthermore, most existing FCG studies are performed under constant amplitude loading, whereas actual service environments involve variable amplitude loading, multiaxial stresses, and exposure to harsh conditions. This gap in representative test data limits the ability to accurately model and predict damage tolerance for repaired components operating under real-world conditions.
- 5.
- Functionally Graded Ti64: Ti64 alloys offer excellent high-temperature strength, yet their limited wear resistance and hardness restrict use in certain aerospace applications [119]. AM enables the fabrication of functionally graded materials (FGMs) with tailored composition gradients, providing location-specific mechanical properties [119]. Unlike conventional composites with sharp interfaces, FGMs promote smooth transitions between dissimilar materials, enhancing overall performance and expanding aerospace applicability. Studies investigating reinforcements such as TiC, Al₂O₃, stainless steel, and Mo in Ti64 have reported varying improvements in micro-hardness and tensile properties depending on phase fractions [120,121,122,123]. However, while tensile and hardness data are available for functionally graded Ti64, their fatigue behavior remains underexplored. For instance, Li et al. [2] showed that TiC-reinforced Ti64 fabricated by LMD exhibited enhanced tensile and micro-hardness properties when 5% TiC is added to Ti64. This underscores the need to examine FCG, as microstructural modifications can greatly affect durability under cyclic loading and high temperatures. Comprehensive FCG evaluation is essential to establish reliable design criteria and fully realize the potential of these FGMs. High-integrity joining of Ti64 and stainless steels is vital for aerospace structures, but direct welding often leads to the formation of brittle intermetallics such as FeTi and Fe₂Ti, causing premature failure [119,120]. FGMs address this challenge by introducing graded interlayer zones, often employing Cu, Ni, or Al alloys, to reduce incompatibility. The selection of suitable interlayer materials and assessment of their fatigue properties, especially FCG behavior, are crucial for advancing robust multi-material joints.
- 6.
- Cold Spray AM: Among solid-state AM processes, cold spray has emerged as a promising technique for fabricating and repairing structural metallic components[124]. Unlike fusion-based AM methods, cold spray operates entirely in the solid state, producing dense, oxidation-free deposits with minimal thermal distortion [125,126,127]. As its applications expand from coatings to structural and load-bearing parts, evaluating the fatigue performance of cold spray materials has become increasingly important. The adoption of nondestructive inspection techniques for structural health monitoring is vital to establishing cold spray as a certified method for structural restoration, particularly in aerospace applications where continuous health monitoring is required [126,128]. Studies have shown that cold spray coatings can improve fatigue performance, with the degree of enhancement governed by coating–substrate material compatibility, interface quality, and residual stress state. Coatings composed of higher-strength materials than the substrate generally yield greater fatigue improvements. Fatigue resistance is equally critical in repair applications, where restored components must recover the fatigue strength of undamaged parts. Although variations in damage geometry and size complicate systematic evaluation, optimized cold spray repairs can extend component life while reducing costs and environmental impact.
- 7.
- Standardization and Data Openness: Progress in understanding FCG in AM Ti64 is limited by incomplete documentation and inconsistent reporting across studies. Many publications lack comprehensive details about the AM process, FCG testing methods, and post-processing conditions, making it difficult to compare results or build reliable datasets for accurate FCG modeling. To address these challenges, it is essential to establish standardized testing protocols, adopt consistent terminology, and encourage open data-sharing practices. These steps will improve reproducibility, enable robust meta-analyses, and ultimately support the development of dependable fatigue design guidelines for AM Ti64.
- 8.
- In-situ FCG testing: Of the reviewed FCG studies, only a few [61,68,73,77,89] employed in-situ FCG testing. In-situ FCG testing offers a powerful approach to directly observe crack initiation and propagation in AM Ti64, capturing the dynamic interactions between cracks, microstructure, inherent defects, and residual stresses. Unlike conventional ex-situ tests, in-situ methods provide high-resolution, real-time data that enable a mechanistic understanding of defect criticality, microstructural influences, and residual stress effects, thereby supporting improved predictive modeling, process optimization, and damage-tolerant design for aerospace applications.
- Multiscale and In-Situ Characterization: Perform more in-situ studies are needed to systematically investigate these interactions across different AM process parameters, build orientations, and heat treatment conditions to fully leverage the benefits of in-situ testing for fatigue performance assessment.
- Service-Relevant Spectrum Testing: Develop fatigue testing protocols that incorporate variable amplitude loading, multiaxial stresses, and realistic environmental conditions, such as high temperatures and corrosive media. Implementing these protocols will ensure that laboratory data more accurately represent the performance and reliability of AM Ti64 under actual service conditions.
- Data-Driven Process Optimization: Employ machine learning and big data analytics to model the complex relationships among AM process parameters, resulting microstructure, defect populations, and FCG performance. Establishing open-access databases will further accelerate the optimization of processing strategies, enabling enhanced fatigue resistance and damage tolerance in AM Ti64 components.
- Standardized Test Results Reporting: Establish unified testing protocols, clear conventions for specimen orientation, and thorough documentation of processing conditions. Promoting open data sharing and adherence to best practices will enhance the reproducibility of results, facilitate meaningful benchmarking across studies, and provide a robust foundation for certifying and qualifying AM Ti64 components in critical applications.
- Data-driven advancements in AM fatigue: Recent progress in data-driven approaches has demonstrated that these methods can significantly enhance our understanding of fatigue behavior in AM materials [137,138]. Machine learning algorithms and advanced statistical analyses are increasingly employed to uncover key process-structure-property relationships that govern fatigue performance, providing predictive capabilities that match and potentially surpass those of conventional mechanistic models. By harnessing large, high-fidelity datasets that capture the intricacies of the AM process, including build parameters, microstructural features, defect distributions, and post-processing conditions, researchers are able to develop robust models for predicting FCG behavior in Ti64. Data-driven modeling not only improves the accuracy of fatigue property predictions [138], but also facilitates the early identification of process-induced anomalies.
4.1. Observations on Experimental Trends in AM Ti64 FCG
4.2. A Reporting Benchmark for Quantitative Assessment of FCG Data in AM Studies
- The average score, ,for the reporting benchmark across all the reviewed AM Ti64 FCG studies is 0.75.
- Of the 20 elements of the reporting benchmark evaluated, only alloy specification, AM process type, FCG test method, graphical representation of FCG data, and R were reported in 100% of the studies.
- Additionally, the following indices were frequently reported : microstructural features, alloy condition and details of post-processing heat treatment protocols, temperature and/or relative humidity conditions during testing, fatigue test frequency and cyclic waveform characteristics, orientation of test specimens within the AM build chamber, Specimen geometry including dimensional tolerances, and crack propagation direction relative to the build orientation
- Conversely, some important indices were underreported. For example, only 12% of studies reported preheat temperature of the powder or build plate , even though preheating is critical in processes such as LPBF to reduce residual stresses, distortion, and warping, reducing the need for post-process stress-relief treatments[143,144,145]. Information on build plate preheating, another significant means of stress reduction, is also rarely included, despite evidence that elevated base plate temperatures further mitigate thermal gradients [146].
- Other commonly omitted indices include feedstock’s chemical composition, surface treatment or roughness measurements, AM process parameters , details of the controlled AM environment and shielding gas composition, powder size distribution for powder feedstock or wire diameter specification , and tensile properties
- As illustrated in Figure 17, none of the reviewed AM FCG Ti64 studies achieved full documentation
- Test conditions and data representation (Category C) are the most consistently reported, with an average of ~99.1%, demonstrating strong compliance.
- Material properties (Category A) are moderately reported (~68.1%), with gaps in powder/wire specifications and tensile properties.
- AM process and specimen preparation (Category B) are the least documented (~66.3%), with frequent omissions in preheating, scan strategy, and shielding gas details.
- Enhance documentation of AM process parameters, including preheating temperature, scan strategy, laser or electron beam power, layer thickness, build orientation, hatch spacing, powder flow rate, wire feed rate, shielding gas type, and power settings. Comprehensive reporting of these parameters is essential, as they strongly influence microstructure, porosity, defect formation, and residual stress, all of which have a critical impact on FCG behavior in AM Ti64.
- Improve reporting of material properties by thoroughly documenting powder characteristics such as particle size distribution, morphology, and chemical composition, as well as tensile behavior. These properties directly influence crack initiation and growth in AM Ti64.
- Maintain comprehensive reporting of testing conditions by consistently documenting load type, stress intensity range, R-ratio, frequency, and environmental factors. Future efforts should continue this level of thoroughness while also prioritizing the inclusion of upstream AM process parameters to further improve the reproducibility of FCG results in AM Ti64.
5. Conclusion
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| Ref. | AM type | Orientation | Fatigue Temperature (°C) | Fatigue Environment | Load Ratio | Frequency (Hz) | Specimen Type | Type of fatigue test |
| [44] | L-PBF | H | RT | Air | 0.05,0.4 | 10 | C(T) | Uniaxial |
| [45] | P-DED | H, V | RT | Air, 3.5% NaCl | 0.1 | 10 | C(T) | Uniaxial |
| [46] | P-DED | H, V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [47] | L-PBF | H, V, T | RT | Air | 0.1-0.92 | 60,80 | C(T) | Uniaxial |
| [48] | L-PBF | - | RT | Air, artificial saliva, Ringer’s solution | 0.05 | 1,10 | C(T) | Uniaxial |
| [49] | E-PBF | H, V | RT | Air | 0.1,0.5,0.8 | 20 | C(T) | Uniaxial |
| [50] | L-PBF | H, V | RT | Air | 0.1 | 50,80 | C(T) | Uniaxial |
| [51] | W-DED+ roll | H, V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [52] | W-DED | V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [53] | L-PBF | - | RT | Air | 0.1 | 10 | Rectangular c/s | Uniaxial |
| [54] | P-DED | - | RT | Air, vacuum, 3.5% NaCl | 0.1,0.9 | 10 | C(T) | Uniaxial |
| [55] | L-PBF | H, V | RT | Air | 0.1 | 10,40 | C(T) | Uniaxial |
| [56] | L-PBF (E-PBF) | H | RT | Air | 0.1,0.7 | - | C(T), SEN(B) | Uniaxial |
| [57] | E-PBF | H, V | RT | Air | 0.1,0.3,0.7 | 20 | C(T) | Uniaxial |
| [58] | P-DED | H, V | RT | Air | 0.1,0.8 | 20 | C(T) | Uniaxial |
| [43] | L-PBF | H, V, D, 30° | RT | Air | 0.1 | 10 | SEN(T) | Uniaxial |
| [59] | L-PBF | H | RT | Air | 0.1,1 | 150 | M(T) | Uniaxial |
| [60] | L-PBF | H, V, D | RT | Air | 0.1,0.3,0.6 | 20 | C(T) | Uniaxial |
| [61] | L-PBF | H, V | 400 | Air | 0.2 | 10 | SEN(T) | In-situ SEM |
| [62] | L-PBF | H | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [63] | L-PBF | H, V | RT | Air | 0.1 | 60 | C(T) | Uniaxial |
| [64] | L-PBF | H | RT | Air | 0.1,0.5 | 10 | C(T) | Uniaxial |
| [65] | L-PBF | 15°,30°,60°,75°, V | RT | Air | 0.1 | 20 | C(T) | Uniaxial |
| [66] | L-PBF | H, V | RT | Air | -1 | 20 | SEN(T) | Uniaxial |
| [67] | P-DED | H, V | RT | Air | 0.1 | 20 | C(T) | Uniaxial |
| [68] | L-PBF | H, V, D | RT | Air | 0.1 | 8 | SEN(T) | In-situ SEM |
| [69] | W-DED+wrought | V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [70] | L-PBF | H | RT | Air | 0.1 | 10 | - | Uniaxial |
| [71] | W-DED | H, V | RT | Air | 0.1 | 8 | C(T) | Uniaxial |
| [72] | L-PBF | H, V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [73] | L-PBF | H, V | RT | Air | 0.1 | 8 | SEN(T) | In-situ SEM |
| [74] | W-DED | H, V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [75] | P-DED | H | RT | Air | 0.1,0.3,0.5,0.8 | 15 | C(T) | Uniaxial |
| [76] | W-DED | H, V | RT | Air | 0.1 | 30 | C(T) | Uniaxial |
| [77] | P-DED | V | RT | Air | 0.2 | 10 | SEN(T) | In-situ SEM |
| [78] | P-DED | V, T | RT | Air | 0.1 | 0.5 | C(T) | Uniaxial |
| [79] | E-PBF | H, V | RT | Air | 0.1 | 20 | C(T) | Uniaxial |
| [80] | L-PBF | H, V | RT | Air | 0.1,0.5 | 10 | C(T) | Uniaxial |
| [81] | L-PBF | H, V, D | RT | Air | 0.1 | 20 | C(T) | Uniaxial |
| [82] | L-PBF | V | RT | Air, artificial saliva | 0.05 | 1,10 | C(T) | Uniaxial |
| [83] | L-PBF | V | RT | Air | 0 | - | C(T) | Uniaxial |
| [84] | P-DED | H | RT | Air | 0.1 | 15 | C(T) | Uniaxial |
| [85] | L-PBF | H | RT | Air | 0 | 10 | C(T) | Uniaxial |
| [86] | L-PBF | H, V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [87] | W-DED+Wrought | H, V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [88] | W-DED+weld | T | RT | Air | 0.1 | - | C(T) | Uniaxial |
| [89] | L-PBF | H, V | RT, 400 | Air | 0.1,0.5 | - | SEN(T) | In-situ SEM |
| [90] | L-PBF | H | RT | Air | 0.1,0.5 | 10 | SEN(T) | Uniaxial |
| [39] | L-PBF | V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [91] | L-PBF | V | RT | Air | 0.1 | - | C(T) | Uniaxial |
| [92] | L-PBF | H | RT | Air | 0.05 | 10 | C(T) | Uniaxial |
| [93] | P-DED | H | RT | Air | 0.1 | 20 | C(T) | Uniaxial |
| [94] | L-PBF | H, V | RT | Air, vacuum | 0 | 15 | Circular c/s | Uniaxial |
| [95] | L-PBF | - | RT | Air | 0.1,0.4,0.7 | 15 | C(T) | Uniaxial |
| [96] | SLM | H, V, D | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| [97] | SLM | H, V | RT | Air | -1 | 5 | C(T) | Uniaxial |
| [98] | SLM | H, V, D | RT | Air | 0.1 | - | C(T) | Uniaxial |
| [99] | L-PBF | - | RT | Air | 0.1 | 13 | C(T) | Uniaxial |
| [85] | L-PBF | H | RT | Air | 0.1 | - | C(T) | Uniaxial |
| [100] | DMLS | H, V | RT | Air | 0.1 | 50,80 | C(T) | Uniaxial |
| [101] | L-PBF | H, V, T | RT | Air | 0.1 | - | C(T) | Uniaxial |
| [102] | SLM | H, V | RT | Air | 0.05 | 0.5,3 | C(T) | Uniaxial |
| [103] | SLM | H, V | RT | Air | 0.1 | 10 | C(T) | Uniaxial |
| Element | ASTM Reference | FCG relevant documentation |
| * | Alloy specification (e.g. Ti64) | |
| * | Grade (e.g., general purpose, aerospace, biomedical, extra-low interstitial, etc.) | |
| E647-10.1.3 | The chemical composition and the weight percentage of each element | |
| E647-10.1.1 | Specimen type (C(T), M(T), SENT etc.) | |
| E647-10.1.1 | Drawings showing the specimen geometry and important dimensions | |
| * | Plain stress or plane strain conditions | |
| E647-10.1.13 | Processing route used to produce the specimen | |
| E647-10.1.13 | Heat treatment procedure (duration, temperature, atmosphere, and method of cooling) | |
| E647-10.1.2 | Experimental set up (Test machine, grips used etc.) | |
| E647-10.1.1 | Machine type (pneumatic vs servo-hydraulic) | |
| E647-10.1.4 | Orientation & position: crack/build direction and location in AM build | |
| * | Surface treatment and roughness measurement | |
| * | Machining method (e.g., milling, turning, grinding) | |
| * | Polishing steps and travel direction | |
| E647-10.1.12 | Test method (Constant-force-amplitude test procedure, K-Decreasing procedure) | |
| E647-10.1.8 | Data reduction technique used to convert a-N to da/dN -ΔK and calculate the FCG properties (secant, incremental polynomial method etc.) | |
| * | FCG measurement technique (visual tracking, post-mortem fractographic analysis of striation spacing, and measurement of crack opening displacement) | |
| * | Pre-cracking method (mechanical pre-cracking, electrolytic pre-cracking etc.) | |
| E647-10.1.5 | Terminal values of ΔK, R, and a from fatigue pre-cracking | |
| E647-10.1.6 | Cyclic waveform (e.g., sinusoidal, triangular etc.) | |
| E647-10.1.6 | Test frequency | |
| E647-10.1.6 | Load or stress ratio | |
| E647-10.1.6 | Applied force range, ΔP (e.g., ) | |
| E647-10.1.7 | Environmental conditions (e.g., temperature, relative humidity, test medium) | |
| * | Failure criterion (e.g., critical crack length, sudden fracture, unstable crack growth) | |
| * | Target FCG parameters (e.g., Paris law constants, threshold ΔKₜₕ) | |
| E647-10.1.13 | Tabulation of FCG results (e.g., a, N, da/dN, ΔK etc.) | |
| E647-10.1.10 | Graphical FCG results, including a–N, da/dN -ΔK | |
| * | Fracture surface analysis (crack path, roughness, and features) | |
| E647-10.1.11 | Record of test anomalies influencing data validity (e.g., transients from load interruptions, shifts in R, or unexpected system responses | |
| E647-10.1.3 |
Report tensile properties following ASTM E8/E8M test methods |
| Element | ASTM Reference | AM relevant documentation |
| F2971-5.1.1.1 | AM feedstock: description and preparation | |
| F2971-5.1.1.2 | Feedstock reuse procedure | |
| F2971-5.1.1.4 | Special production procedures | |
| F2971-5.1.1.3 | Standard production processes (from feedstock to specimen) | |
| F2971-5.1.1.3 | Specimen placement and orientation in build chamber | |
| F2971-5.1.2.1 | Nominal dimensions and allowable tolerances | |
| F2971-5.1.2.1 | Experimental plan | |
| F2971-5.1.2.1 | Experimental procedures | |
| F2971-5.1.2.1 | Non-destructive testing method | |
| F2971-5.1.2.2 | Description of non-conventional test methods | |
| F2971-5.1.2.3 | Additional post-processing steps |
| ASTM Reference | Description | |
| - | Designated alloy specification or material grade | |
| E647-10.1.3 | Feedstock’s chemical composition | |
| - | Surface preparation/condition/ roughness measurements | |
| - | Microstructural features | |
| E647-10.1.3 | Alloy condition and details of post-processing heat treatment protocols | |
| F2971 -5.1.1.3 | AM processing technique used | |
| F2971 -5.1.1.3 | AM process parameters | |
| F2971 -5.1.1.3 | Scan strategy utilized during the AM fabrication process | |
| F2971 -5.1.1.3 | Build plate or substrate preheating temperature | |
| F2971 -5.1.1.3 | Details of the controlled AM environment and shielding gas composition | |
| E647-10.1.12 | Employed FCG testing methodology | |
| E647-10.1.7 | Temperature and/or relative humidity conditions during testing | |
| E647-10.1.6 | Fatigue test frequency and cyclic waveform characteristics | |
| E647-10.1.13 | Graphical plots illustrating FCG experimental results | |
| E647-10.1.6 | Load ratio or R applied during fatigue testing | |
| F2971 – 5.1.1.1 | Powder size distribution for powder feedstock or wire diameter specification | |
| F2971 – 5.1.1.3 | Orientation of test specimens within the AM build chamber | |
| F2971 – 5.1.2.1 | Precise specimen geometry including dimensional tolerances | |
| E647-10.1.4 | Crack propagation direction relative to the build orientation | |
| E647-10.1.3 | Tensile properties |
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