Experimental and numerical investigation of the Refined Zigzag Theory for accurate buckling analysis of highly heterogeneous sandwich beams

The Refined Zigzag Theory (RZT) is a structural theory developed for the analysis of composite multilayer and sandwich beams. However, the accuracy of RZT for buckling analysis of sandwich beams has not been experimentally investigated, and for RZT and Timoshenko Beam Theory (TBT) the effect of the degree of heterogeneity on their accuracy requires further study. The aim of this work was to validate the use of the RZT for predicting the critical buckling loads of sandwich beams, even with highly heterogeneous material properties, and to assess the use of the TBT for the same application. Buckling experiments were conducted on five foam-core sandwich beams, which varied in geometry and included highly heterogeneous configurations. For each beam, two finite element (FE) models were analyzed using RZT- and TBT-beam FEs. The comparison between the numerical and the experimental results highlighted a major capability of RZT to correctly predict the critical buckling load for all the beams considered. The dependence of the TBT results on the beam characteristics was further investigated through a parametric analysis, which showed the dominant effect to be a close to linear relationship between the TBT error and the beam face-to-core thickness ratio. The work demonstrated the outstanding accuracy of the RZT predictions, including the superior capabilities with respect to TBT, and has application for rapid and accurate analysis of industrial structures

A penetration model for semi-infinite ultra-high molecular weight polyethylene composite

Ultra-high molecular weight polyethylene (UHMW-PE) composite has been shown to be an effective material for ballistic protection against blunt penetrators [1]. The material exhibits multiple stages of penetration, typically characterised by an initial local penetration phase followed by large bulge deformation of the back face [2]. The location at which transition occurs between the localised penetration stage and non-localised bulging stage is an important property of UHMW-PE composite armour. However, the conditions required to induce transition are poorly understood with a range of different mechanisms proposed to explain the behaviour [2,3], none of which can be used to predict the transition location within the target.</jats:p

A methodology for hydrocode analysis of ultra-high molecular weight polyethylene composite under ballistic impact

Ballistic performance analysis of ultra-high molecular weight polyethylene (UHMW-PE) is critical for the design of armour systems against ballistic threats. However, no validated modelling strategy has been published in literature for UHMW-PE composite that captures the penetration and damage mechanisms of thick targets impacted between 900 m/s and 2000 m/s. Here we propose a mechanistically-based and extensively validated methodology for the ballistic impact analysis of thick UHMW-PE composite. The methodology uses a non-linear orthotropic continuum model that describes the composite response using a non-linear equation of state (EoS), orthotropic elastic plastic strength with directional hardening and orthotropic failure criteria. A new sub-laminate discretisation approach is proposed that allows the model to more accurately capture out-of-plane failure. The model is extensively validated using experimental ballistic data for a wide range of UHMW-PE target thicknesses up to 102 mm against 12.7 mm and 20 mm calibre fragment simulating projectiles (FSPs) with impact velocities between 400 m/s and 2000 m/s. Very good overall agreement with experimental results is seen for depth of penetration, ballistic limit and residual velocity, while the penetration mechanisms and target bulge behaviour are accurately predicted. The model can be used to reduce the volume of testing typically required to design and assess thick UHMW-PE composite in ballistic impact applications

Modelling of guided waves in a composite plate through a combination of physical knowledge and regression analysis

The use of high-frequency guided waves, such as Rayleigh and Lamb waves (actively) or acoustic emissions (passively), has become increasingly prominent in engineering applications, particularly for structural health monitoring (SHM) and, more traditionally, non-destructive evaluation (NDE). In comparison to low-frequency analysis, guided waves have the additional benefit of being able to locate damage with finer spatial resolution (controlled by the diffraction limit). This paper looks into developing a health-monitoring strategy for fibre-reinforced polymer structures using ultrasonic guided waves (UGWs); part of the remit is to determine a methodology for modelling of UGWs propagation. As fibres within such a material act as a secondary guide for these waves, time-space modelling of the waves is difficult. Presented here is a novel methodology utilising a physics-incorporated, data-driven model to determine the feature-space of UGW propagation. The method uses Gaussian processes and in this paper is made a comparison between different kernel-based methods. By careful consideration of these machine learning techniques, more robust and generalised models can be generated