A Model for Predicting the Stress Concentration of Intergranular Corrosion around a Fastener Hole

This paper presents a model that predicts the stress field around intergranular corrosion. The stress analysis is conducted in ABAQUS via a Python input script, which is written in Igor Pro. The intergranular corrosion path is described using a Monte-Carlo Markov Chain based on the materials grain size distribution and probability that the corrosion will turn at a grain boundary junction. The model allows a complete analysis of the stresses resulting from intergranular corrosion around a fastener hole of any size. As fatigue initiation is most likely to occur at the highest stress concentration, this model gives an understanding of which of the features of intergranular corrosion are most critical and can allow for the development of beta solutions for crack growth. This model has been applied to 7075-T651 extruded aluminum alloy from a legacy era aircraft but can be readily applied to any material where the microstructure is known and can be described using a statistical distribution.

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Numerical Simulation of the Stress Field of Thick 7B04 Aluminum Alloy Board during Continuous Manufacture Procedure

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.127.259 ◽

2007 ◽

Vol 127 ◽

pp. 259-264

Author(s):

Hong Yuan Fang ◽

Cheng Iei Fan

Keyword(s):

Numerical Simulation ◽

Aluminum Alloy ◽

Stress Concentration ◽

Stress Field ◽

Solution Treatment ◽

Simulation Method ◽

The Core ◽

Manufacturing Procedure ◽

Continuous Manufacture ◽

Simulation Results

Numerical simulation method is employed in the article to analyze the stress field of thick 7B04 aluminum alloy board during manufacturing procedure of solution treatment, calendaring and stretching. The simulation results show that the surface of the board endures compressive stress while the core segment endures tensile stress, and the distribution of the stress is very inhomogeneous. The calendaring procedure helps to decrease the stress and redistribute the stress uniformly, but it also leads to stress concentration at the two ends of the board, which engenders bad influence on the subsequent processing. The board deforms plastically when being stretched, thus the stress decreases greatly and is redistributed uniformly.

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The effect of grain structure on the corrosion resistance of 7050 aluminum alloy

International Journal of Modern Physics B ◽

10.1142/s0217979219400113 ◽

2019 ◽

Vol 33 (01n03) ◽

pp. 1940011 ◽

Cited By ~ 1

Author(s):

Lin Sun ◽

Ming-An Chen ◽

Yun-Lai Deng

Keyword(s):

Mechanical Properties ◽

Grain Size ◽

Corrosion Resistance ◽

Aluminum Alloy ◽

Vickers Hardness ◽

Intergranular Corrosion ◽

Volume Fraction ◽

Grain Structure ◽

Isothermal Forging ◽

7050 Aluminum Alloy

Multi-direction isothermal forging of 7050 aluminum alloy at 103s1 strain rate and temperature of 3000C are observed. EBSD is used to characterize the grain structure, and the Vickers hardness and intergranular corrosion (IGC) properties are tested. The results of EBSD indicate that the sub-grains increase and the grain size decreases gradually as the pass of isothermal forging increases. The volume fraction of sub-grain has great effect on the corrosion resistance. The more sub-grains are included in the grain structure, the better the corrosion resistance and the mechanical properties. The grain size also influences the corrosion resistance, and the decreasing of the grain size is adverse to the corrosion resistance but is good for mechanical properties.

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Bayesian Applications in Auditory Research

Journal of Speech Language and Hearing Research ◽

10.1044/2018_jslhr-h-astm-18-0228 ◽

2019 ◽

Vol 62 (3) ◽

pp. 577-586 ◽

Cited By ~ 9

Author(s):

Garnett P. McMillan ◽

John B. Cannon

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Bayesian Methods ◽

Prior Distribution ◽

Interim Analysis ◽

Iterative Process ◽

Bayes Theorem ◽

Sound Therapy ◽

The Many ◽

Auditory Research

Purpose This article presents a basic exploration of Bayesian inference to inform researchers unfamiliar to this type of analysis of the many advantages this readily available approach provides. Method First, we demonstrate the development of Bayes' theorem, the cornerstone of Bayesian statistics, into an iterative process of updating priors. Working with a few assumptions, including normalcy and conjugacy of prior distribution, we express how one would calculate the posterior distribution using the prior distribution and the likelihood of the parameter. Next, we move to an example in auditory research by considering the effect of sound therapy for reducing the perceived loudness of tinnitus. In this case, as well as most real-world settings, we turn to Markov chain simulations because the assumptions allowing for easy calculations no longer hold. Using Markov chain Monte Carlo methods, we can illustrate several analysis solutions given by a straightforward Bayesian approach. Conclusion Bayesian methods are widely applicable and can help scientists overcome analysis problems, including how to include existing information, run interim analysis, achieve consensus through measurement, and, most importantly, interpret results correctly. Supplemental Material https://doi.org/10.23641/asha.7822592

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