Model for predicting fatigue life of nanomaterials

Many complicated crack growth phenomena such as the overload retardation effect and the loading sequence effect, etc. The crack closure phenomenon caused by plasticity was first observed by Elber [ 9 ]. This behavior is known as the small crack effect and it indicates that the crack closure phenomenon may not exist in small crack growth regions or it can be negligible.

In this paper, a general methodology is proposed to predict fatigue life of smooth and circular-hole specimens, in which the crack closure model and equivalent initial flaw size EIFS concept are employed.

One of the main problems of this method is how to evaluate the initial flaw size IFS appropriately. Introduction Life prediction and failure analysis are indispensable and critical for engineering structural materials, but continue to be challenging issues.

But most of the existing methods are lack of theoretical Model for predicting fatigue life of nanomaterials and are sometimes unreliable [ 4 ].

In other words, crack closure may just exist in the long crack growth regime but not in the small crack growth region.

In addition, Newman et al. The paper is organized as follows. Experimental data for smooth and circular-hole specimens in three different alloys AlT3, AlT6 and Ti-6Al-4V under multiple stress ratios are used to validate the method.

However, the difference of growth behavior between small crack and long crack is not considered in this method. Some conclusions and future work are given. Failure analysis and fatigue life prediction are necessary and critical for engineering structural materials.

The cumulative fatigue damage theories and the traditional S-N curve method, such as the stress-based approach [ 1 ], are often used for fatigue life prediction in engineering practice.

Therefore, the EIFS concept is considered to be a good way to solve these problems. In the current study, several methods are employed to estimate the value of initial flaw size, such as nondestructive evaluation NDE [ 2 ] and empirical approaches [ 3 ].

In this paper, a general method is proposed to predict fatigue life based on the crack closure model and the EIFS, in which the small crack effect is also considered. A good agreement is observed between model predictions and experimental data.

Liu and Mahadevan [ 5 ] recently proposed a method to predict the fatigue life of smooth specimens based on the equivalent initial flaw size EIFS.

This problem involves the complex mechanism of small-crack growth which is different from long crack growth behavior.

Crack closure considering the small crack effect may reflect real crack propagation characteristics. Several crack growth models are available to describe crack growth behavior, such as the Forman model and the Walker model. In the validation section, Semi-circular surface crack and quarter-circular corner crack are assumed to be the initial crack shapes for the smooth and circular-hole specimens, respectively.

First, a brief review of the concept of EIFS and the framework of fatigue life prediction based on crack growth analysis method, is addressed. Small-crack growth is a very complicated process, and it is difficult to establish an accurate quantitative expression to describe the growth behavior of a real small crack.

Different effects of crack closure on small crack growth region and long crack growth region are considered in the proposed method.

These issues make fatigue life prediction based on crack growth analysis difficult. Though some researchers doubted the contribution of crack closure to crack growth and the existence of the crack closure phenomenon [ 121314 ], plenty of experimental research, numerical, and theoretical analysis on long cracks have shown that the crack closure phenomenon does exist and has a significant effect on fatigue crack growth [ 9101115161718192021222324 ].

Additionally, estimation of the actual IFS is another challenge. Newman developed a strip yield model to quantify the crack closure level [ 1011 ]. The detailed analysis and discussion are performed on the proposed model. Because of this, the fatigue crack growth method based on linear elastic fracture mechanics LEFM is becoming a more important and promising alternative for total fatigue life analysis.

The general material crack propagation model can be expressed as d. Next, a total fatigue life prediction model considering the crack closure, is established; then, a large number of experimental data, for smooth and circular-hole specimens on three different alloys AlT3, AlT6 and Ti-6Al-4Vunder multiple stress ratios collected from the open literature, are employed to validate the proposed model.

Finally, some discussion and conclusions are drawn based on the current study.Failure analysis and fatigue life prediction are necessary and critical for engineering structural materials.

In this paper, a general methodology is proposed to predict fatigue life of smooth and circular-hole specimens, in which the crack closure model and equivalent initial flaw size (EIFS) concept are employed.

Different effects of crack closure on small crack growth region and long crack. Predicting fatigue resistance of nano-twinned materials: Part I – Role of cyclic slip irreversibility and Peierls stress. A Second-Level SAC Solder-Joint Fatigue-Life Prediction Methodology solder joint model for life prediction A finite-element-based modeling methodology for predicting the part-on-board.

Predicting the Fatigue Life of Different Composite Materials Using Artificial Neural Networks M. Al-Assadi & H. El Kadi & I. M. Deiab concluded that ANN can be trained to model constant-stress fatigue behavior at least as well as other current life-prediction methods.

For predicting the fatigue life of composites, the input parameters may include static and cyclic properties of the composite material under consideration, its lay. Cooper et al. investigated the use of an ANN model in predicting fatigue cracking and J-integral of Semicircular Bend (SCB) specimens containing reclaimed asphalt pavement (RAP) and recycled asphalt shingles (RAS).

The authors concluded that the ANN technique had an acceptable level of accuracy to predict the critical strain energy release rate.

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Model for predicting fatigue life of nanomaterials
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