Propagating bands of plastic deformation in a metal alloy as critical avalanches

Mäkinen, Tero; Karppinen, Pasi; Ovaska, Markus; Laurson, Lasse; Alava, Mikko J.

doi:10.1126/sciadv.abc7350

Cited by 38 publications

(7 citation statements)

References 44 publications

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“…Nevertheless, DIC only tracks total displacements, and thus, its usefulness has mainly been the assessment of strain heterogeneity [30], or to attempt an inverse solution by validating microstructurally accurate finite element modeling [31]. Indeed, DIC data has been useful for finding similarities to finite-element models of various types [1,31], with advanced coarse-grained and multiscale models of microstructural deformation behavior [32][33][34], and machine learning models [35][36][37]. Nevertheless, the evolution of DIC total strain profiles contains enormous information that may be adequate for material properties related to yielding, hardening and eigenstrains.…”

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confidence: 99%

Direct detection of plasticity onset through total-strain profile evolution

Papanikolaou

Alava

2021

Phys. Rev. Materials

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Plasticity in solids is dependent on microstructural history, temperature, and loading rate, and sampledependent knowledge of yield points in structural materials adds reliability to mechanical behavior. Yielding is commonly measured through controlled mechanical testing, in ways that either distinguish elastic (stress) from total deformation measurements or identify plastic slip contributions. In this paper, we show that yielding can be unraveled through statistical analysis of total-strain fluctuations during the evolution sequence of profiles, measured in situ, through digital image correlation. We demonstrate two distinct ways of quantifying yield locations in widely applicable crystal plasticity models for polycrystalline solids, using either principal component analysis or discrete wavelet transforms. We test and compare these approaches for synthetic data of polycrystals and a variety of yielding responses through changes in applied loading rates and strain-rate sensitivity exponents.

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confidence: 99%

Direct detection of plasticity onset through total-strain profile evolution

Papanikolaou

Alava

2021

Phys. Rev. Materials

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“…Richeton et al [43] statistically characterized the intermittent plastic strain bursts for a single metallic crystal by acoustic emission experiments. In metal alloys, the interacting dynamic dislocations are the sources of deformation avalanches [29]. With the uniaxial tension, the material yields and plastic deformations occur [15].…”

Section: Resultsmentioning

confidence: 99%

Molecular dynamics simulation of interface atomic diffusion in ultrasonic metal welding

Mostafavi

Bamer

Markert

2021

Int J Adv Manuf Technol

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The formation of a reliable joint between a large number of aluminum strands for battery applications is crucial in automotive industry, especially in the technology of autonomous vehicles. Therefore, in this study, mechanical deformations and diffusion patterns of the mating interface in ultrasonic welding of aluminum were investigated using molecular dynamics simulations. Furthermore, microscopic observations of the joints between aluminum strands from ultrasonic welding illustrating the influence of two process parameters were done. To study the nanomechanics of the joint formation, two aluminum crystallites of different orientations were built. The impact of the sliding velocity and the compression rate of the upper crystal block on the diffusion pattern at the interface of the two crystallites were quantified via the diffusion coefficient. Tensile deformations of several joint configurations were performed to investigate the load-bearing capacity of the solid state bond, taking into account the compression rate, the sliding velocity and the crystallite orientation. The atomic scale simulations revealed that the orientations of the crystallites govern the interface diffusion and the tensile strength of the joint significantly. Furthermore, interface atom diffusion increased with increasing the sliding velocity. Additionally, it was observed that a higher sliding velocity enhances the friction heat generation between the crystallites and significantly increases the interface temperature.

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“…(see also the next chapter for experimental determination of the value of ϕ). We can also derive an expression for the exponent of the scaling relation between U m and T, using (22a) and (24) in the form…”

Section: Expressions For the Exponents Of Scaling Relationsmentioning

confidence: 99%

“…Until now, Barkhausen noise measurements provided excellent agreement between the predicted [7] and experimentally determined, normalized temporal-avalanche shapes at fixed duration or shape [15]. Besides Barkhausen noise measurements, other techniques such as AE [8,[16][17][18][19][20][21][22] or high-resolution detection of the deformation or stress drops during plastic deformation (see e.g., [9,23,24]) are also used, but the agreement with theoretical predictions is far less satisfactory than those obtained from Barkhausen noise investigations. For instance, there are observations that the normalized shapes of avalanches do not collapse on the same reduced curve for different size or duration bins (see e.g., [7][8][9]).…”

Section: Introductionmentioning

confidence: 95%

Denouement of the Energy-Amplitude and Size-Amplitude Enigma for Acoustic-Emission Investigations of Materials

Kamel,

Samy,

Tóth

et al. 2022

Materials

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There are many systems producing crackling noise (avalanches) in materials. Temporal shapes of avalanches, U(t) (U is the detected voltage signal, t is the time), have self-similar behaviour and the normalized U(t) function (e.g., dividing both the values of U and t by S1/2, where S is the avalanche area), averaged for fixed S, should be the same, independently of the type of materials or avalanche mechanisms. However, there are experimental evidences that the temporal shapes of avalanches do not scale completely in a universal way. The self-similarity also leads to universal power-law-scaling relations, e.g., between the energy, E, and the peak amplitude, Am, or between S and Am. There are well-known enigmas, where the above exponents in acoustic emission measurements are rather close to 2 and 1, respectively, instead of E~Am3 and S~Am2, obtained from the mean field theory, MFT. We show, using a theoretically predicted averaged function for the fixed avalanche area, U(t)=atexp(−bt2) (where a and b are non-universal, material-dependent constants), that the scaling exponents can be different from the MFT values. Normalizing U by Am and t by tm (the time belonging to the Am: rise time), we obtain tm~Am1−φ (the MFT values can be obtained only if φ would be zero). Here, φ is expected to be material-independent and to be the same for the same mechanism. Using experimental results on martensitic transformations in two different shape-memory single-crystals, φ = 0.8 ± 0.1 was obtained (φ is the same for both alloys). Thus, dividing U by Am as well as t by Am1−φ (~tm) leads to the same common, normalized temporal shape for different, fixed values of S. This normalization can also be used in general for other experimental results (not only for acoustic emission), which provide information about jerky noises in materials.

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Propagating bands of plastic deformation in a metal alloy as critical avalanches

Cited by 38 publications

References 44 publications

Direct detection of plasticity onset through total-strain profile evolution

Direct detection of plasticity onset through total-strain profile evolution

Molecular dynamics simulation of interface atomic diffusion in ultrasonic metal welding

Denouement of the Energy-Amplitude and Size-Amplitude Enigma for Acoustic-Emission Investigations of Materials

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