Characterisation of dynamic behaviour of alumina ceramics: evaluation of stress uniformity

Accurate characterisation of dynamic behaviour of ceramics requires the reliable split-Hopkinson pressure bar (SHPB) technique and the condition of uniaxial homogeneous specimen deformation. In this study, an experimentally validated 3D finite element model of the full scale SHPB experiment was developed to quantitatively evaluate the wave propagation in the bars and the stress distribution/evolution in the alumina specimen. Wave signals in both the SHPB experiments and the finite element model were analysed to characterise the dynamic behaviour of alumina. It was found that the equilibrium of both stresses within the specimen and forces at the specimen ends can be established in the intermediate stage of deformation. The validity of stress uniformity in the alumina specimen supports the assumption of uniaxial homogeneous specimen deformation in the SHPB and validates the characterisation of dynamic behaviour of alumina ceramics

Voronoi cell finite element modelling of the intergranular fracture mechanism in polycrystalline alumina

The mechanisms of fracture in polycrystalline alumina were investigated at the grain level using both the micromechanical tests and finite element (FE) model. First, the bending experiments were performed on the alumina microcantilever beams with a controlled displacement rate of 10 nm s–1 at the free end; it was observed that the intergranular fracture dominates the failure process. The full scale 3D Voronoi cell FE model of the microcantilever bending tests was then developed and experimentally validated to provide the insight into the cracking mechanisms in the intergranular fracture. It was found that the crystalline morphology and orientation of grains have a significant impact on the localised stress in polycrystalline alumina. The interaction of adjacent grains as well as their different orientations determines the localised tensile and shear stress state in grain boundaries. In the intergranular fracture process, the crack formation and propagation are predominantly governed by tensile opening (mode I) and shear sliding (mode II) along grain boundaries. Additionally, the parametric FE predictions reveal that the bulk failure load of the alumina microcantilever increases with the cohesive strength and total fracture energy of grain boundaries

Characterisation and constitutive model of tensile properties of selective laser melted Ti-6Al-4V struts for microlattice structures

Predicting the mechanical performance of selective laser melted (SLM) microlattice structures requires the constitutive data of the parent solid material in the struts. This work first characterised the cross-sectional features of individual SLM Ti-6Al-4V struts. The direct examination revealed the non-linear relation between the equivalent diameter and the Feret diameter of a strut, which was quantified by an empirical equation. The equation considering surface roughness effects allowed the non-destructive determination of the equivalent diameter using the directly measured Feret diameter prior to tension testing. Uniaxial tension experiments were then performed to accurately measure the constitutive behaviour of SLM Ti-6Al-4V struts, with the strain history tracked and recorded using high resolution imaging. It was found that the strut diameter ranging 300–1200 µm has a negligible effect on the stress–strain response. The strain hardening and fracture behaviour of the SLM Ti-6Al-4V can be quantitatively described using the Johnson–Cook models with damage. The constitutive models were finally validated by the 3D finite element model and experiments of uniaxial compression on an SLM microlattice structure. The methodology presented here can accurately characterise and formulate the constitutive behaviour of SLM metallic struts for microlattices

Inelastic deformation micromechanism and modified fragmentation model for silicon carbide under dynamic compression

The underlying micromechanism remains to be clarified for the bulk inelastic behaviour of specific ceramics under impact loads. In this study, the silicon carbide materials were subjected to the split-Hopkinson pressure bar compression in which the strain rate was not constant but increased to the dynamic level at high stresses. The inelastic deformation occurs in the high strain rate stage in compression, followed by the final transgranular fracture. The post-test fragments were examined in both the SEM and high resolution TEM. It was found that macroscopic inelastic behaviour is dominated by the dislocation motion and the localised amorphisation that arise at high strain rates. The damage and thus the degraded modulus in the dynamic inelastic deformation were incorporated to modify a dynamic fragmentation model to evaluate the fragment size as a function of strain rates. The modified model more accurately predicts the size of fragments produced at high strain rates

An Investigation into the Connection between Language Proficiency and Text Analysis Abilities in English Learners

This study’s objective is to evaluate whether or not there is a correlation between students’ command of the English language and their analytical prowess with regard to written material. Through quantitative and qualitative study on students with varied degrees of linguistic proficiency, it has been found that an increase in one’s level of linguistic competence is strongly and favorably associated with an increase in one’s ability for textual analysis. This discovery was made on students with varying levels of linguistic proficiency. Learners who have a higher degree of language competency are able to more effectively absorb vocabulary, grammatical structure, and logical links in the discourse when reading and interpreting English texts. This is because they have a better understanding of the English language. As a consequence of this, they are capable of performing text analysis in a manner that is both more effective and more accurate than before. This article’s goal is to give instructional strategies for learners of all language levels in order to optimize the process of strengthening those learners’ ability to evaluate texts. The target audience for this article is learners of all language levels. When these strategies are utilized, educators will be provided with practical recommendations that will assist them in more effectively directing students toward mastery of the basic text analysis skills. The outcomes of this study may, in some way, have an impact on the educational practice of teaching English as a second language

PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales

Neural language models (LMs) have achieved impressive results on various language-based reasoning tasks by utilizing latent knowledge encoded in their own pretrained parameters. To make this reasoning process more explicit, recent works retrieve a rationalizing LM's internal knowledge by training or prompting it to generate free-text rationales, which can be used to guide task predictions made by either the same LM or a separate reasoning LM. However, rationalizing LMs require expensive rationale annotation and/or computation, without any assurance that their generated rationales improve LM task performance or faithfully reflect LM decision-making. In this paper, we propose PINTO, an LM pipeline that rationalizes via prompt-based learning, and learns to faithfully reason over rationales via counterfactual regularization. First, PINTO maps out a suitable reasoning process for the task input by prompting a frozen rationalizing LM to generate a free-text rationale. Second, PINTO's reasoning LM is fine-tuned to solve the task using the generated rationale as context, while regularized to output less confident predictions when the rationale is perturbed. Across four datasets, we show that PINTO significantly improves the generalization ability of the reasoning LM, yielding higher performance on both in-distribution and out-of-distribution test sets. Also, we find that PINTO's rationales are more faithful to its task predictions than those generated by competitive baselines.Comment: 19 pages, 6 figures, preprin