Fatigue and Crack Growth under Constant- and Variable-Amplitude Loading in 9310 Steel Using “Rainflow-on-the-Fly” Methodology

Fatigue of materials, like alloys, is basically fatigue-crack growth in small cracks nucleating and growing from micro-structural features, such as inclusions and voids, or at micro-machining marks, and large cracks growing to failure. Thus, the traditional fatigue-crack nucleation stage (Ni) is basically the growth in microcracks (initial flaw sizes of 1 to 30 μm growing to about 250 μm) in metal alloys. Fatigue and crack-growth tests were conducted on a 9310 steel under laboratory air and room temperature conditions. Large-crack-growth-rate data were obtained from compact, C(T), specimens over a wide range in rates from threshold to fracture for load ratios (R) of 0.1 to 0.95. New test procedures based on compression pre-cracking were used in the near-threshold regime because the current ASTM test method (load shedding) has been shown to cause load-history effects with elevated thresholds and slower rates than steady-state behavior under constant-amplitude loading. High load-ratio (R) data were used to approximate small-crack-growth-rate behavior. A crack-closure model, FASTRAN, was used to develop the baseline crack-growth-rate curve. Fatigue tests were conducted on single-edge-notch-bend, SEN(B), specimens under both constant-amplitude and a Cold-Turbistan+ spectrum loading. Under spectrum loading, the model used a “Rainflow-on-the-Fly” subroutine to account for crack-growth damage. Test results were compared to fatigue-life calculations made under constant-amplitude loading to establish the initial microstructural flaw size and predictions made under spectrum loading from the FASTRAN code using the same micro-structural, semi-circular, surface-flaw size (6-μm). Thus, the model is a unified fatigue approach, from crack nucleation (small-crack growth) and large-crack growth to failure using fracture mechanics principles. The model was validated for both fatigue and crack-growth predictions. In general, predictions agreed well with the test data.

Characterization of Surface Fatigue Crack Nucleation and Microstructurally Small Crack Growth in High Strength Aluminum Alloys

It is well established that fatigue crack nucleation and small crack growth in high strength aluminum alloys are highly influenced by the surrounding microstructure including grain boundaries, texture, inclusion barriers, among other factors. As such, specific and targeted experimental and computational methods are necessary to accurately capture and predict the discrete behavior of microstructurally small fatigue cracks. In this study, surface fatigue crack nucleation and microstructurally small crack growth in high strength aluminum alloys, commonly used in aerospace applications, are evaluated through a holistic approach encompassing fatigue testing, crack measurement, and computational prediction of crack growth rates. During fatigue testing, crack shapes and growth are quantified using a novel surface replication technique that is applied to investigate crack nucleation, as well as to collect validation data that includes an accurate description of crack shape during crack propagation, a challenging and essential component in predicting crack growth. Computational simulation of fatigue crack growth in non-straight, complex surface crack arrays typically requires high fidelity analysis using computationally expensive methods to account for the mathematical and geometrical complexities inherent in the solution. A dislocation distribution based technique has been previously demonstrated to rapidly and accurately predict the stress intensity factors for through cracks of complex shape. This method was expanded and investigated as an approach for rapidly predicting the crack growth rate of kinked and tortuous surface crack arrays, using the crack configuration and bulk material properties as inputs. To investigate the accuracy and effectiveness of this characterization approach, surface crack growth in AA7075-T7351 was experimentally analyzed and modeled under high cycle and low cycle fatigue conditions. This comprehensive approach was determined to be an expedient and applicable method for characterizing and evaluating the nucleation and crack growth rate of non-planar microstructurally small and short crack configurations.

Simulation of fatigue small crack growth in additive manufactured Ti–6Al–4V material

Additive manufacturing (AM) offers design freedom and ability to fabricate parts of complex shapes which are not often possible with the conventional methods of manufacturing. In an AM part, even with optimum build parameters, a complete elimination of defects is not possible and this makes it hard to fully deploy the AM technology to build load bearing parts operating under cyclic loading conditions. Many of these defects are < 1 mm in size and are categorised as ‘small cracks’. Local interaction of cracks with microstructural features and closure effects at the wake of the crack tip are some of the factors which make the growth behaviour of small and long cracks different. A crack growth life prediction method, which effectively considers the small crack growth behaviour, has been discussed in this paper. This proposed method includes a detailed finite element-based crack growth simulation using the ANSYS SMART fracture technology. The lifing calculations utilise the modified NASGRO equation and small crack growth data which was obtained from the published long crack growth data, corrected for closure effects. The predicted stress versus number of cycles curves were compared against the fatigue test results for the AM specimens in Ti–6Al–4V material. A good correlation between the predictions and test results suggests that the proposed method can be used to assess the small crack growth life of AM parts where the fatigue effects of cyclic loading can be quite significant.

Confidence Bound Estimation for Mechanism-Based Small Crack Growth Probabilistic Design Life Predictions

Current design lives for US Air Force turbine engine materials are based on a 1 in 1000 rate of nucleation of an engineering sized crack (B0.1). These lives are determined from models fitted to test coupon fatigue data at many different loading conditions. It has been shown that this methodology can sometimes lead to excess conservatism, and it often does not fully incorporate understanding of the mechanisms that drive crack initiation, growth, and fracture. A mechanism based probabilistic life forecasting methodology has been previously proposed with the objective to improve the prediction of minimum fatigue life or design life through understanding of the type and frequency of the material mechanisms that lead to early or immediate fatigue crack initiation. An approach is proposed and demonstrated for the estimation of probabilistic mechanism-based design life prediction confidence bounds. These confidence bounds on the calculated B0.1 or minimum life predictions are dependent on the quality and quantity of the data used in the analysis. The effect of additional data from either small crack growth tests or microstructural characterization or fractography analysis on the extent of the calculated confidence bounds is shown. The analysis presented can ultimately be used to describe a relationship between the required confidence in the design life predictions to the cost of the test program required to collect the necessary data. Comparisons are made between data requirements and the level of confidence in empirical statistical predictions from fatigue test data and the new probabilistic mechanism-based design life predictions for laboratory specimens in a turbine engine material.