Search for: All records

Abstract Damage mechanism identification has scientific and practical ramifications for the structural health monitoring, design, and application of composite systems. Recent advances in machine learning uncover pathways to identify the waveform-damage mechanism relationship in higher-dimensional spaces for a comprehensive understanding of damage evolution. This review evaluates the state of the field, beginning with a physics-based understanding of acoustic emission waveform feature extraction, followed by a detailed overview of waveform clustering, labeling, and error analysis strategies. Fundamental requirements for damage mechanism identification in any machine learning framework, including those currently in use, under development, and yet to be explored, are discussed. 

The relationship between acoustic emission (AE) and damage source areas in SiC/SiC minicomposites was modeled using insights from tensile testing in-scanning electron microscope (SEM). Damage up to matrix crack saturation was bounded by: (1) AE generated by matrix cracking (lower bound) and (2) AE generated by matrix cracking, and fiber debonding and sliding in crack wakes (upper bound). While fiber debonding and sliding exhibit lower strain energy release rates than matrix cracking and fiber breakage, they contribute significant damage area and likely produce AE. Fiber breaks beyond matrix crack saturation were modeled by two conditions: (i) only fiber breaks generated AE; and (ii) fiber breaks occurred simultaneously with fiber sliding to generate AE. While fiber breaks are considered the dominant late-stage mechanism, our modeling indicates that other mechanisms are active, a finding that is supported by experimental in-SEM observations of matrix cracking in conjunction with fiber failure at rupture. 

Abstract In this work, we demonstrate that damage mechanism identification from acoustic emission (AE) signals generated in minicomposites with elastically similar constituents is possible. AE waveforms were generated by SiC/SiC ceramic matrix minicomposites (CMCs) loaded under uniaxial tension and recorded by four sensors (two models with each model placed at two ends). Signals were encoded with a modified partial power scheme and subsequently partitioned through spectral clustering. Matrix cracking and fiber failure were identified based on the frequency information contained in the AE event they produced, despite the similar constituent elastic properties of the matrix and fiber. Importantly, the resultant identification of AE events closely followed CMC damage chronology, wherein early matrix cracking is later followed by fiber breaks, even though the approach is fully domain-knowledge agnostic. Additionally, the partitions were highly precise across both the model and location of the sensors, and the partitioning was repeatable. The presented approach is promising for CMCs and other composite systems with elastically similar constituents. 

The sulfur isotope composition of volcanic rocks in arcs can be difficult to constrain because significant fractionation can occur during degassing. Mafic and ultramafic cumulates represent the least degassed part of the magmatic arc system, thereby offering an opportunity to investigate undegassed sulfur in arcs. Recent work on high pressure metamorphic rocks has suggested that subducted materials can retain their original isotopic composition to sub-arc depths. In particular, extreme negative δ34S values can be retained in subducted sediments. The purpose of this project is to investigate to what extent these deep subduction zone processes are reflected in the sulfur isotope signature of arc magmas. In the Lesser Antilles arc, there is a gradual decrease in terrigenous sediment being subducted from south to north. An estimated ~15% subducted sediment in the south and ~2% in the north is reflected in the chemical and isotopic composition of the Lesser Antilles arc magmas. Sulfides in these magma- derived cumulates record the earliest stages of magma evolution and are a more faithful monitor of the sulfur isotopic composition of the magma source region in the mantle than erupting lavas. We hypothesize that the decrease in terrigenous sediment being subducted from the south to north will be reflected in the S isotopes in cumulate samples. Samples of mafic and ultramafic cumulates have been collected from fourteen islands across the Lesser Antilles arc. Primary rock types are olivine gabbro, amphibole gabbro, plagioclase gabbro, and olivine gabbronorite. Sulfide minerals include pyrite, chalcopyrite, and pyrrhotite, and typically occur as spherical blebs. Sulfides are found primarily as inclusions in clinopyroxene, amphibole, olivine, and plagioclase. Sulfides occur less frequently as inclusions in magnetite and within the matrix. Analyses of sulfur isotopes in cumulate sulfides are currently underway. The decrease in the amount sediment being subducted from south to north in the Lesser Antilles arc should result in δ34S values that increase from south to north (more sediment subducted = more negative δ34S values).