Multiscale structural relaxation and adiabatic shear failure mechanisms

Froustey, Catherine; Naimark, Oleg; Panteleev, Ivan; Bilalov, Dmitry; Петрова, А. Н.; Lyapunova, E. A.

doi:10.1134/s1029959917010039

Cited by 19 publications

(6 citation statements)

References 32 publications

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“…The mechanism of ASB formation lies in decreasing the yield stress in local surface layers as a result of a considerable heat emission under high‐rate dynamic loading and a consequent intensification of plastic flow in these zones. [ 91,92 ] It has been proposed that the emergence of such structures of localized and/or adiabatic shear may promote efficient structure dispersion in local surface regions. [ 93,94 ] Due to such a structure, most materials acquire a high set of mechanical characteristics, including strength and crack resistance, and in some cases cold resistance, primarily due to an increased resistance to the propagation of the initial cracks, especially under impact loading.…”

Section: Promising Trends In the Development Of New Technologies For The Surface Modification Of Parts Operating Under Extreme Conditionsmentioning

confidence: 99%

Advanced Materials for Mechanical Engineering: Ultrafine‐Grained Alloys with Multilayer Coatings

et al. 2021

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Research has demonstrated that the formation of a bulk ultrafine‐grained (UFG) structure in metals and alloys through severe plastic deformation (SPD) enables increasing of their strength properties and decreasing of the temperature range of superplasticity. Designers and process engineers generally show a great interest in such materials because the development of mechanical engineering industries places ever‐increasing demands on the performance properties of commercial alloys, especially for parts operating under extreme conditions. One of the approaches for a comprehensive enhancement of the performance characteristics of structural materials is a combination of a UFG structure in the bulk of a material, providing an increase in strength, and an additional surface modification providing resistance to erosion and corrosion damage. As a result, a set of material service properties can be enhanced, which is difficult to achieve through only metal nanostructuring or only surface modification. This approach has been demonstrated through an example of UFG titanium alloys produced by SPD, including those with nanostructured multilayer TiVN coatings of different “architectures.” Accordingly, herein, the trends, problems, and prospects of surface modification for the innovative application of structural UFG titanium alloys in advanced mechanical engineering are examined.

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Section: Promising Trends In the Development Of New Technologies For The Surface Modification Of Parts Operating Under Extreme Conditionsmentioning

confidence: 99%

Advanced Materials for Mechanical Engineering: Ultrafine‐Grained Alloys with Multilayer Coatings

et al. 2021

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“…he wide-range constitutive equations [22][23][24], describing the relationship between the kinetics of damage caused by defects and the relaxation properties of materials, were used to construct a mathematical model that is capable of describing the deformation behavior of metals and alloys under fatigue loading. To describe the evolution of the structure of the material, two parameters are introduced: tensor: where: s -tensor of microshears [23]; s -shear intensity; l -unit normal vector to the shear plane; b -unit vector in the direction of shear; δ -scale-invariant, structural parameter; R -the distance between defects, 0 r -the characteristic size of the nuclei of defects.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…The frequency of loading in this case was equal to 20 000 Hz, as in the experiment. Thus, the complete set of constants for the AlMg6 alloy is as follows: Constants known from literature [24]…”

Section: Model Parameter Identificationmentioning

confidence: 99%

Damage evolution in the AMg6 alloy during high and very high cycle fatigue

Bannikov

Bilalov

Oborin³

et al. 2019

Frattura Ed Integrità Strutturale

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Paper presents the "in situ" method for determining of irreversible fatigue damage accumulation, based on the analysis of nonlinear manifestations of the feedback signal in a closed system of an ultrasonic fatigue system. During very high cycle (gigacycle) fatigue, the anomalies of the elastic properties of the material are appear, which leads to a nonlinearity effect in the amplitude of oscillations. This effect increases with the initiation and growth of fatigue cracks. The technology was applied to samples of AlMG-6 alloy with preliminary dynamic deformation to determine the moment of initiation and growth of the fatigue crack in very high cycle fatigue regime. This method is applicable for the early detection of fatigue cracks both on the surface and inside the material under cyclic loading in the ultrasonic mode. On the basis of wide-range defining relations for a deformable solid body with mesoscopic defects, a mathematical model has been proposed that can adequately describe behavior of the material during fatigue failure. The results of mathematical modeling are in good agreement with the experimental data

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“…Due to the fact that artificial neural networks have various applications such as accurate prediction of complex material behavior, it could be applied for damage detection and structural integrities in corresponding multiple-variable problems. (Alves et al, 2015;Andrejiova, Grincova, & Marasova, 2019;Bhowmik, Krishnan, Hazra, & Pakrashi, 2019;Dia, Dieng, Gaillet, & Gning, 2019;Dorval, Meredieu, & Danjon, 2016;Egnew, Roueche, & Prevatt, 2018;Favillier et al, 2015;Kabir, Sadiq, & Tesfamariam, 2016;Kim, Hwang, & Jung, 2017;Noori Hoshyar, Samali, Liyanapathirana, & Taghavipour, 2019;Pérez-Ruiz et al, 2018;Wang et al, 2018; (Fakih, Mustapha, Tarraf, Ayoub, & Hamade, 2018;Froustey et al, 2017;J. Li & Zhang, 2016;Mayer & Mayer, 2019;Ovid'Ko, Sheinerman, Skiba, Krasnitiskiy, & Smirnov, 2015;Panettieri, Leclerc, Jumel, & Guitard, 2018;Y.…”

Section: Annmentioning

confidence: 99%

Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances<strong> </strong>

Mosavi¹

2019

Preprint

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The loss of integrity and adverse effect on mechanical properties can be concluded as attributing miro/macro-mechanics damage in structures, especially in composite structures. Damage as a progressive degradation of material continuity in engineering predictions for any aspects of initiation and propagation requires to be identified by a trustworthy mechanism to guarantee the safety of structures. Besides the materials design, structural integrity and health are usually prone to be monitored clearly. One of the most powerful methods for the detection of damage is machine learning (ML). This paper presents the state of the art of ML methods and their applications in structural damage and prediction. Popular ML methods are identified and the performance and future trends are discussed.

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Multiscale structural relaxation and adiabatic shear failure mechanisms

Cited by 19 publications

References 32 publications

Advanced Materials for Mechanical Engineering: Ultrafine‐Grained Alloys with Multilayer Coatings

Advanced Materials for Mechanical Engineering: Ultrafine‐Grained Alloys with Multilayer Coatings

Damage evolution in the AMg6 alloy during high and very high cycle fatigue

Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances<strong> </strong>

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