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Microstructural Mechanisms of Damage Accumulation in Technical Alloys

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Metals and Alloys".

Deadline for manuscript submissions: closed (10 September 2022) | Viewed by 4972

Special Issue Editor


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Guest Editor
Institute of Metals Engineering, University Duisburg-Essen, Duisburg, Germany
Interests: severe/complex mechanical loading of metals and alloys; failure analysis; sliding wear; cavitation erosion; solid-state joining; dynamic recovery and recrystallization

Special Issue Information

Dear Colleagues,

The mechanisms of damage and failure of metals under mechanical or combined loads have been widely studied, and high strength materials have been developed. Nevertheless, under complex load conditions frequently occurring in technical applications, unexpected material behavior or failures still occur today. Under tribological loads, chemical and microstructural alterations occur in the material, and surface properties under cyclic and multiaxial stress fields are difficult to determine or predict. echniques of severe plastic deformation, on the other hand, allow the introduction of extremely high strains, typically by shear, without inducing defects through the superposition of hydrostatic compressive stress. Understanding microstructural mechanisms of damage and strain accumulation, but also healing effects through recovery or recrystallization, allows us to understand ways in which materials may be loaded well beyond their current range of application—or clarifies in which load situations conventional material properties will overestimate a material’s performance in a given load situation.

This Special Issue focuses on research aiming at the understanding of fundamental mechanisms of materials’ reactions to potentially damaging mechanical load conditions. This encompasses the analysis of microstructural mechanisms of defect accumulation, as well as studies into targeted measures to counteract or mitigate damage accumulation on a microstructural level. Full research articles, shorter communications reporting limited but conclusive studies of a specific topic, as well as reviews are welcome.

Dr. Stefanie Hanke
Guest Editor

Manuscript Submission Information

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Keywords

  • wear mechanisms
  • strain accumulation
  • fatigue
  • mechanical behavior
  • microstructure
  • failure mechanisms
  • crack initiation
  • crack propagation
  • damage criteria

Published Papers (2 papers)

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Research

16 pages, 7172 KiB  
Article
Wear Mechanism Classification Using Artificial Intelligence
by Philipp Maximilian Sieberg, Dzhem Kurtulan and Stefanie Hanke
Materials 2022, 15(7), 2358; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15072358 - 22 Mar 2022
Cited by 8 | Viewed by 2265
Abstract
Understanding the acting wear mechanisms in many cases is key to predicting lifetime, developing models describing component behavior, or for the improvement of the performance of components under tribological loading. Conventionally scanning electron microscopy (SEM) and sometimes additional analytical techniques are performed in [...] Read more.
Understanding the acting wear mechanisms in many cases is key to predicting lifetime, developing models describing component behavior, or for the improvement of the performance of components under tribological loading. Conventionally scanning electron microscopy (SEM) and sometimes additional analytical techniques are performed in order to analyze wear appearances, i.e., grooves, pittings, surface films, and others. In addition, experience is required in order to draw the correct and relevant conclusions on the acting damage and wear mechanisms from the obtained analytical data. Until now, different types of wear mechanisms are classified by experts examining the damage patterns manually. In addition to this approach based on expert knowledge, the use of artificial intelligence (AI) represents a promising alternative. Here, no expert knowledge is required, instead, the classification is done by a purely data-driven model. In this contribution, artificial neural networks are used to classify the wear mechanisms based on SEM images. In order to obtain optimal performance of the artificial neural network, a hyperparameter optimization is performed in addition. The content of this contribution is the investigation of the feasibility of an AI-based model for the automated classification of wear mechanisms. Full article
(This article belongs to the Special Issue Microstructural Mechanisms of Damage Accumulation in Technical Alloys)
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11 pages, 12456 KiB  
Article
Effect of Annealing on Microstructure and Corrosion Behavior of Interstitial Free Steel
by Qiongyao He, Xiaojuan Jiang, Pengzhan Cai, Ling Zhang, Tao Sun, Xiaokui Yang, Kun Zhou and Lunwu Zhang
Materials 2022, 15(1), 24; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15010024 - 21 Dec 2021
Cited by 6 | Viewed by 2357
Abstract
Interstitial free steels with various grain sizes and textures were prepared by cold-rolling followed by an annealing process. The effect of grain size, crystallographic orientations and stored energy on corrosion behavior of interstitial free steel was investigated. It was found that the deformed [...] Read more.
Interstitial free steels with various grain sizes and textures were prepared by cold-rolling followed by an annealing process. The effect of grain size, crystallographic orientations and stored energy on corrosion behavior of interstitial free steel was investigated. It was found that the deformed microstructure and dislocation boundaries were consumed by recrystallizing grains during annealing. The average grain size increase ranging from 0.61 μm to 11 μm and the volume fraction of recrystallized grains was about 96% after annealing for 64 h; meanwhile, the γ fiber was the dominated recrystallized texture component. The stored energy gradually decreased due to the reduction in dislocation density by annealing. The potentiodynamic polarization and Nyquist plots show that the corrosion potential exhibits a more positive shift and depressed capacitive semicircle radius increase with rising annealing time. The 64 h annealed specimens had the biggest depressed semicircle in the Nyquist plots and the highest positive corrosion potential, which indicates the enhancement of corrosion resistance. Such an improvement of corrosion resistance is attributed to the increase in the volume fraction of the γ fiber and decrease in the stored energy. Full article
(This article belongs to the Special Issue Microstructural Mechanisms of Damage Accumulation in Technical Alloys)
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