Two- and Three-Dimensional Failure Criteria for Laminate Composites

Abstract Several two- and three-dimensional mixed-mode interface failure criteria are proposed for predicting delamination failure in multidirectional, laminate composites. The proposed criteria, based on the stress intensity factors K1, K2, and KIII, as well as the critical interface energy release rate Gic and phase angles ψ and ϕ, are examined using results obtained from Brazilian disk mixed-mode fracture toughness tests. Two material systems are considered. The first contains a delamination along an interface between a unidirectional fabric and a plain woven fabric. The second is composed of a plain woven fabric with fibers oriented in different directions in succeeding plies. The former was manufactured by means of a wet-layup and the latter is a prepreg. Finally, a statistical analysis is carried out to obtain a failure curve or surface with a 10% probability of unexpected failure and a 95% confidence. These curves or surfaces may be used to predict failure of structures containing these laminates and to assist in composite design.</jats:p

Effects of Anisotropic Microstructure and Load Ratio on Fatigue Crack Propagation Rate in Additively Manufactured Ti-6Al-4V Alloy

Additive manufacturing (AM) refers to advanced technologies for building 3D objects by adding material layer upon layer using either electron beam melting (EBM) or selective laser melting. AM allows us to produce lighter and more complex parts. However, various defects are created during the AM process, which severely affect fatigue behavior. In the current research, the effects of the anisotropic microstructure in the in-plane and out-of-plane orientations and defects on the fatigue crack propagation rate (FCPR) and crack path were studied. A resonance machine was used to determine the fatigue crack propagation rate (da/dN vs. ΔK) from the near-threshold up to the final fracture, accompanied by in situ Acoustic Emission (AE) monitoring. Micro-Computerized Tomography (µCT) enabled us to characterize surface and microstructural defects. Metallography was used to determine the microstructure vs. orientations and fractography to classify the fatigue fracture propagation modes. Calculations of the local stress distribution were performed to determine the interactions of the cracks with the defects. In the out-of-plane direction, the material exhibited high fatigue fracture toughness accompanied by a slightly lower fatigue crack propagation rate as compared to in-plane orientations. The near-threshold stress intensity factor was slightly higher in the out-of-plane orientation as compared to that in the in-plane one, accompanied by a lower exponent of the Paris law regime. The threshold decreased with an increasing load ratio as expected for both orientations. The crack propagation direction that crosses the elongated grains plays an important role in increasing fatigue resistance in the out-of-plane direction. In the in-plane directions, the crack propagates parallel to the grain boundary, interacts with more defects and exhibits more brittle striations on the fracture surface, resulting in lower fatigue resistance

Adopting Learning Analytics to Inform Postgraduate Curriculum Design

Part 4: Diffusion and Adoption TechnologyInternational audienceUnderstanding students’ sentiment is valuable to understanding the changes that could or should be made in curriculum design at third level. Learning analytics has shown potential for improving student learning experiences and supporting teacher inquiry. Yet, there is limited research that reports on the adoption and actual use of learning analytics to support teacher inquiry. This study captures sentiment of postgraduate students by integrating learning analytics with the steps of teacher inquiry. This study makes two important contributions to teaching and learning literature. First, it reports on the use of learning analytics to support teacher inquiry over three iterations of a business analytics programme between 2016 and 2019. Second, evidence-based recommendations on how to optimise learning analytics to support teacher inquiry are provided