Modelling the crush behaviour of thermoplastic composites

Thermoplastic composites are likely to emerge as the preferred solution for meeting the high-volume production demands of passenger road vehicles. Substantial effort is currently being directed towards the development of new modelling techniques to reduce the extent of costly and time consuming physical testing. Developing a high-fidelity numerical model to predict the crush behaviour of composite laminates is dependent on the accurate measurement of material properties as well as a thorough understanding of damage mechanisms associated with crush events. This paper details the manufacture, testing and modelling of self-supporting corrugated-shaped thermoplastic composite specimens for crashworthiness assessment. These specimens demonstrated a 57.3% higher specific energy absorption compared to identical specimen made from thermoset composites. The corresponding damage mechanisms were investigated in-situ using digital microscopy and post analysed using Scanning Electron Microscopy (SEM). Splaying and fragmentation modes were the primary failure modes involving fibre breakage, matrix cracking and delamination. A mesoscale composite damage model, with new non-linear shear constitutive laws, which combines a range of novel techniques to accurately capture the material response under crushing, is presented. The force-displacement curves, damage parameter maps and dissipated energy, obtained from the numerical analysis, are shown to be in a good qualitative and quantitative agreement with experimental results. The proposed approach could significantly reduce the extent of physical testing required in the development of crashworthy structures

Integrated waste management as a climate change stabilisation wedge for the Maltese islands

The continuous increase in anthropogenic greenhouse gas emissions occurring since the Industrial Revolution is offering significant ecological challenges to Earth. These emissions are leading to climate changes which bring about extensive damage to communities, ecosystems and resources. The analysis in this article is focussed on the waste sector within the Maltese islands, which is the largest greenhouse gas emitter in the archipelago following the energy and transportation sectors. This work shows how integrated waste management, based on a life cycle assessment methodology, acts as an effective stabilisation wedge strategy for climate change. Ten different scenarios applicable to the Maltese municipal solid waste management sector are analysed. It is shown that the scenario that is most coherent with the stabilisation wedges strategy for the Maltese islands consists of 50% landfilling, 30% mechanical biological treatment and 20% recyclable waste export for recycling. It is calculated that 16.6Mt less CO2-e gases would be emitted over 50 years by means of this integrated waste management stabilisation wedge when compared to the business-as-usual scenario. These scientific results provide evidence in support of policy development in Malta that is implemented through legislation, economic instruments and other applicable tools.peer-reviewe

Estimating the mode I through-thickness intralaminar R-curve of unidirectional carbon fibre-reinforced polymers using a micromechanics framework combined with the size effect method

A three-dimensional micromechanics framework is developed to estimate the mode I through-thickness intralaminar crack resistance curve of unidirectional carbon fibre-reinforced polymers. Finite element models of geometrically-scaled single edge notch tension specimens were generated. These were modelled following a combined micro-/meso-scale approach, where the region at the vicinity of the crack tip describes the microstructure of the material, while the regions far from the crack tip represent the mesoscopic linear-elastic behaviour of the composite. This work presents a novel methodology to estimate fracture properties of composite materials by combining computational micromechanics with the size effect method. The size effect law of the material, and consequently the crack resistance curve, are estimated through the numerically calculated peak stresses. In-depth parametric analyses, which are hard to conduct empirically, are undertaken, allowing for quantitative and qualitative comparisons to be successfully made with experimental and numerical observations taken from literature

Resistance welding of carbon fibre reinforced PEKK by means of CNT webs

Single lap shear specimens were manufactured using resistance welding of carbon fibre reinforced substrates by means of CNT web-based heating elements. Heating elements were manufactured by embedding the CNT web layers between layers of PEKK/glass fibre and connecting them to copper electrodes. An experimental campaign explored their electrothermal behaviour influencing the welding process. Single lap shear specimens were then welded at a pressure of 0.05 MPa and different levels of power and duration. An optimum bond was obtained with a specific power of 80–90 kW/m2 and a time of 150 s, achieving a shear strength of 30 MPa. Post-mortem analysis revealed that fracture propagated within the substrates. This work represents a further step in the integration of CNT web-based heating elements in an industrial welding process

Transmission laser welding of thermoplastics by using carbon nanotube web

Laser welding of transparent and semi-transparent thermoplastics using layers of carbon nanotube (CNT) web as absorbant is reported. Single lap shear specimens were manufactured placing the layers of CNT-web between two polyethylene terephthalate glycol-modified (PETG) sheets, that were successively irradiated with laser power at a wavelength of 1064 nm. Optical analyses were performed to assess the transmittance of the joint under different configurations; for the single layer of CNT web a transmittance of 83 %, in the visible range, was obtained after welding. Single-lap shear tests were performed and a shear strength of 23 MPa was obtained when using one layer of CNT-web. The investigated technology allows using a solid film as laser absorbing material, replacing conventional liquid or dye that need to be processed and applied on the surface before welding, thus speeding up the manufacturing process

Fast object detection in pastoral landscapes using a multiple expert colour feature extreme learning machine

Fast and accurate object detection is a desire of many vision-guided robotics based systems. Agriculture is an area where detection accuracy is often sacrificed for speed, especially in the pursuit of real time results. Pastoral landscapes are especially challenging with varying levels of complexity, as competing objects are rarely textually smooth or visibly different from surroundings. This study presents a machine learning algorithm designed for object detection called the Multiple Expert Colour Extreme Learning Machine (MEC-ELM). The MEC-ELM is a multiple expert implementation of a Colour Feature Extreme Learning Machine (CF-ELM). The CF-ELM is itself a modification of the Extreme Learning Machine (ELM) with a partially connected hidden layer and a fully connected output layer, taking 3 inputs. The inputs can be utilised by multiple colour systems, including, RGB, Y'UV and HSV. Colour inputs were chosen, as colour is not sensitive to adjustments in scale, size and location and provides information not available in the standard grey-scale ELM. In the MEC-ELM algorithm, feature extraction and classification techniques were implemented simultaneously making a fully functional object detection algorithm. The algorithm was tested on weed detection and cattle detection from a video feed, delivering 0.89 (cattle) to 0.98 (weeds) accuracy in tuning and a precision of 0.61 to 0.95 in testing, with classification times between 0.5s to 1s per frame. The algorithm has been designed with complex and unpredictable terrain in mind, making it an ideal application for agricultural or pastoral landscapes