Fine structures of acoustic emission spectra: How to separate dislocation movements and entanglements in 316L stainless steel

Abstract

Intermittent avalanches in a multitude of materials are characterized by acoustic emission, AE, where local events lead to strain relaxations and generate shock waves (so-called “jerks”), which are measured at the sample surface. The bane of this approach is that several avalanche mechanisms may contribute to the same AE spectrum so that a detailed analysis of each individual contribution becomes virtually impossible. It is, hence, essential to develop tools to separate signals from different dynamical processes, such as ferroic domain switching, collapse of porous inclusions, dislocation movements, entanglements, and so on. Particularly, difficult cases are dynamical microstructures in fcc alloys where the AE signal strength is weak. Nevertheless, using profile analysis of AE signals, we can distinguish between two mechanisms, namely, dislocation movements and dynamic entanglements in fcc 316L stainless steel. In this approach, we are able to measure the statistical AE durations of both subsets separately. The fingerprint for superposed avalanches with different durations is seen by the scaling between the energy E and the maximum amplitude A of each avalanche E ∼ Ax with x = 2. While the same exponent x applies for both mechanisms, the scaling relation shows two branches with different absolute energy values. The two mechanisms are then confirmed by separating the energy distributions P(E) ∼ E−ε for the two mechanisms with ε = 1.55 for dislocation movements and ε = 1.36 for entanglements.

Change of Acoustic Emission Characteristics during Temperature Induced Transition from Twinning to Dislocation Slip under Compression in Polycrystalline Sn

“…Since our acoustic activity was very low at high temperatures, more efforts are needed to clear up the reason of the obtained small value of ε (i.e., whether it is caused by the presence of different types of AE signals and/or if this is due to the combination of wild and mild fluctuations) [ 22 ]. Another option can be the application of the recently published method [ 56 ] to separate signals from different dynamical processes.…”

Multiple Avalanche Processes in Acoustic Emission Spectroscopy: Multibranching of the Energy−Amplitude Scaling

“…Reproduced with permission. [ 43 ] Copyright 2021, Elsevier. b) TEM image after tension (tensile strain: ≈70%) shows that martensites and dislocation microstructures coexist.…”

Acoustic Emission Spectroscopy: Applications in Geomaterials and Related Materials

“…Chen and her collaborators have demonstrated how to separate dislocation moves and entanglements in 316 L stainless steel. They showed that the main difference between the two mechanisms is the average duration for each type of avalanche [74].…”