scholarly journals Machine Learning Based Prognostics of Fatigue Crack Growth in Notch Pre-cracked Aluminum 7075-T6 Rivet Hole

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Robert Haynes ◽  
Ghanashyam Joshi ◽  
Natasha Bradley

Constant stress amplitude fatigue tests were conducted on the notch pre-cracked Aluminum 7075-T6 rivet hole dog-bone coupons. Monitoring of visible surface crack length by special surface engraving using digital microscope images and by ultrasonic sensors signals was carried out to yield fatigue crack length measurements in relation to number of fatigue cycles applied. The experimental results provide ultrasonic sensor validation for fatigue crack length measurements. Fracto-graphic examination of failed fatigue surfaces has provided further confirmation of notch pre-crack length, crack initiation process, and crack growth marker bands. These experimental inputs were used in NASGRO and AFGROW software fatigue crack growth simulations. The simulation results did not match the crack initiation fatigue life measured by experiments. However, there was good agreement with crack growth simulations of larger cracks. Hence, we plan to develop a machine learning application that will learn the fatigue crack initiation and crack growth processes from data obtained from our own experiments and other fatigue data available from AFGROW databases. Nonlinear AutoRegressive models with eXogenous input (NARX) artificial neural network were used to predict crack growth longer than 5.0-mm. Particle filtering modeling with Bayesian updating was applied to these experimental data for prognostics of fatigue crack growth. A concept design and preliminary implementation results will be presented.

2004 ◽  
Vol 126 (1) ◽  
pp. 77-86 ◽  
Author(s):  
Yanyao Jiang ◽  
Miaolin Feng

Fatigue crack propagation was modeled by using the cyclic plasticity material properties and fatigue constants for crack initiation. The cyclic elastic-plastic stress-strain field near the crack tip was analyzed using the finite element method with the implementation of a robust cyclic plasticity theory. An incremental multiaxial fatigue criterion was employed to determine the fatigue damage. A straightforward method was developed to determine the fatigue crack growth rate. Crack propagation behavior of a material was obtained without any additional assumptions or fitting. Benchmark Mode I fatigue crack growth experiments were conducted using 1070 steel at room temperature. The approach developed was able to quantitatively capture all the important fatigue crack propagation behaviors including the overload and the R-ratio effects on crack propagation and threshold. The models provide a new perspective for the R-ratio effects. The results support the notion that the fatigue crack initiation and propagation behaviors are governed by the same fatigue damage mechanisms. Crack growth can be treated as a process of continuous crack nucleation.


2005 ◽  
Vol 128 (4) ◽  
pp. 889-895 ◽  
Author(s):  
K. S. Chan ◽  
M. P. Enright

This paper summarizes the development of a probabilistic micromechanical code for treating fatigue life variability resulting from material variations. Dubbed MICROFAVA (micromechanical fatigue variability), the code is based on a set of physics-based fatigue models that predict fatigue crack initiation life, fatigue crack growth life, fatigue limit, fatigue crack growth threshold, crack size at initiation, and fracture toughness. Using microstructure information as material input, the code is capable of predicting the average behavior and the confidence limits of the crack initiation and crack growth lives of structural alloys under LCF or HCF loading. This paper presents a summary of the development of the code and highlights applications of the model to predicting the effects of microstructure on the fatigue crack growth response and life variability of the α+β Ti-alloy Ti-6Al-4V.


Author(s):  
C. M. Davies ◽  
H. Thomlinson ◽  
P. A. Hooper

Selective Laser Melting (SLM) is a relatively new manufacturing technique that offers many benefits. However the utilisation of SLM manufactured components depends on the assurance of their integrity during operation. Tensile and high cycle fatigue tests have been performed on uniaxial samples manufactured using SLM of 316L stainless steel to examine the elastic-plastic deformation and fatigue crack initiation behaviour of the material. In addition, the fatigue crack growth behaviour has been determined from tests on compact tension samples manufactured using SLM. The influence of build orientation has been examined on the compact tension samples. The results are compared to values obtained from conventional manufacturing methods. The tensile samples have a higher strength but significantly lower ductility than wrought material. The fatigue strength of the SLM material was substantially less than wrought material, though a similar fatigue limit maybe seen, this may be attributed to porosity in the material. The fatigue crack growth rate of the SLM material was 5–10 times faster, for a given stress intensity factor, than wrought materials and strongly depended on crack orientation in relation to the build direction.


Author(s):  
K. S. Chan ◽  
M. P. Enright

This paper summarizes the development of a probabilistic micromechanical code for treating fatigue life variability resulting from material variations. Dubbed MicroFaVa (Micromechanical Fatigue Variability), the code is based on a set of physics-based fatigue models that predict fatigue crack initiation life, fatigue crack growth life, fatigue limit, fatigue crack growth threshold, crack size at initiation, and fracture toughness. Using microstructure information as material input, the code is capable of predicting the average behavior and the confidence limits of the crack initiation and crack growth lives of structural alloys under LCF or HCF loading. This paper presents a summary of the development of the code and highlights applications of the model to predicting the effects of microstructure on the fatigue crack growth response and life variability of the α + β Ti-alloy Ti-6Al-4V.


Author(s):  
Somnath Chattopadhyay

The propagation behavior of short cracks cannot be studied by linear elastic methods because of large plastic region near the crack tip, as well as a breakdown in correlation of the stress intensity factor with the fatigue crack growth rates. The proposed fatigue design approach incorporates a distance parameter in conjunction with linear elastic fracture mechanics and effectively integrates long and short crack growth test data. This distance parameter is a material constant that allows for the effects of (a) large-scale plasticity, (b) crack closure and (c) fatigue crack threshold. Furthermore, this parameter can be used to successfully predict fatigue crack growth behavior of short cracks. The practical application of this method to study fatigue crack initiation in pressure vessels rests on the concept that initiation occurs only when the material ahead of the crack tip is damaged enough by cyclic straining.


2020 ◽  
Vol 4 (1) ◽  
pp. 30-39
Author(s):  
Georgi Georgiev Georgiev

The paper explores the shape of a fatigue crack initiation in the interval of 106-107cycles of duplex stainless steel, commercially designated as SAF 2507. Particular emphasis is placed upon the development of the crack’s growth front and its subsequent expansion in three directions x, y, z. Created, accordingly, on the basis of the experimentally obtained results, is a 3D computer model to help provide a further prediction for the physical endurance of similar materials. The growth of a fatigue crack is modeled by using The SolidWorks and AutoCAD software tools for constructing the model of fatigue crack growth.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4221
Author(s):  
Roshan Joseph ◽  
Hanfei Mei ◽  
Asaad Migot ◽  
Victor Giurgiutiu

Acoustic waves are widely used in structural health monitoring (SHM) for detecting fatigue cracking. The strain energy released when a fatigue crack advances has the effect of exciting acoustic waves, which travel through the structures and are picked up by the sensors. Piezoelectric wafer active sensors (PWAS) can effectively sense acoustic waves due to fatigue-crack growth. Conventional acoustic-wave passive SHM, which relies on counting the number of acoustic events, cannot precisely estimate the crack length. In the present research, a novel method for estimating the crack length was proposed based on the high-frequency resonances excited in the crack by the energy released when a crack advances. In this method, a PWAS sensor was used to sense the acoustic wave signal and predict the length of the crack that generated the acoustic event. First, FEM analysis was undertaken of acoustic waves generated due to a fatigue-crack growth event on an aluminum-2024 plate. The FEM analysis was used to predict the wave propagation pattern and the acoustic signal received by the PWAS mounted at a distance of 25 mm from the crack. The analysis was carried out for crack lengths of 4 and 8 mm. The presence of the crack produced scattering of the waves generated at the crack tip; this phenomenon was observable in the wave propagation pattern and in the acoustic signals recorded at the PWAS. A study of the signal frequency spectrum revealed peaks and valleys in the spectrum that changed in frequency and amplitude as the crack length was changed from 4 to 8 mm. The number of peaks and valleys was observed to increase as the crack length increased. We suggest this peak–valley pattern in the signal frequency spectrum can be used to determine the crack length from the acoustic signal alone. An experimental investigation was performed to record the acoustic signals in crack lengths of 4 and 8 mm, and the results were found to match well with the FEM predictions.


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