A computational geometry generation method for creating 3D printed composites and porous structures

A computational method for generating porous materials and composite structures was developed and implemented. The method is based on using 3D Voronoi cells to partition a defined space into segments. The topology of the segments can be controlled by controlling the Voronoi cell set. The geometries can be realized by additive manufacturing methods, and materials can be assigned to each segment. The geometries are generated and processed virtually. The macroscopic mechanical properties of the resulting structures can be tuned by controlling microstructural features. The method is implemented in generating porous and composite structures using polymer filaments i.e., polylactic acid (PLA), thermoplastic polyurethane (TPU) and nylon. The geometries are realized using commercially available double nozzle fusion deposition modelling (FDM) equipment. The compressive properties of the generated porous and composite configurations are tested quasi statically. The structures are either porous of a single material or composites of two materials that are geometrically intertwined. The method is used to produce and explore promising material combinations that could otherwise be difficult to mix. It is potentially applicable with a variety of additive manufacturing methods, size scales, and materials for a range of potential applications

The traumatic brain injury mitigation effects of a new viscoelastic add-on liner

Traumatic brain injury (TBI) affects millions of people worldwide with significant personal and social consequences. New materials and methods offer opportunities for improving designs of TBI prevention systems, such as helmets. We combined empirical impact tests and computational modelling to test the effectiveness of new viscoelastic add-on components in decreasing biomechanical forces within the brain during helmeted head impacts. Motorcycle helmets with and without the viscoelastic components were fitted on a head/neck assembly and were tested under oblique impact to replicate realistic accident conditions. Translational and rotational accelerations were measured during the tests. The inclusion of components reduced peak accelerations, with a significant effect for frontal impacts and a marginal effect for side and rear impacts. The head accelerations were then applied on a computational model of TBI to predict strain and strain-rate across the brain. The presence of viscoelastic components in the helmet decreased strain and strain-rate for frontal impacts at low impact speeds. The effect was less pronounced for front impact at high speeds and for side and rear impacts. This work shows the potential of the viscoelastic add-on components as lightweight and cost-effective solutions for enhancing helmet protection and decreasing strain and strain-rate across the brain during head impacts

Grip socks improve slalom course performance and reduce in-shoe foot displacement of the forefoot in male and female sports players

This study assessed whether grip socks reduce in-shoe foot motion and improve change of direction performance in team sports players and compared the effects between males and females. A sledge and pulley system confirmed the static coefficient of friction was increased in the grip socks (1.17) compared to the regular socks (0.60). Performance during a slalom course was faster in the grip socks compared to regular socks (p = .001). Yet, there was no difference in the utilised coefficient of friction between the shoe-floor interface during a side-cut and turn change of direction manoeuvre. Three-dimensional motion capture revealed the grip socks reduced in-shoe foot displacement during the braking phase, with greater effect during the sharper turn manoeuvre. The magnitude of natural foot spreading within the shoe was greater in the calcaneus region than the metatarsals which suggests in-shoe sliding may only occur at the forefoot. Males tended to have increased in-shoe displacement, which is associated with larger foot spreading due to their increased mass. Findings provide guidance for product developers to enhance the support inside the shoe at the forefoot, and change of direction performance

A review of challenges and framework development for corrosion fatigue life assessment of monopile-supported horizontal-axis offshore wind turbines

Digital tools such as machine learning and the digital twins are emerging in asset management of offshore wind structures to address their structural integrity and cost challenges due to manual inspections and remote sites of offshore wind farms. The corrosive offshore environments and salt-water effects further increase the risk of fatigue failures in offshore wind turbines. This paper presents a review of corrosion fatigue research in horizontal-axis offshore wind turbines (HAOWT) support structures, including the current trends in using digital tools that address the current state of asset integrity monitoring. Based on the conducted review, it has been found that digital twins incorporating finite element analysis, material characterisation and modelling, machine learning using artificial neural networks, data analytics, and internet of things (IoT) using smart sensor technologies, can be enablers for tackling the challenges in corrosion fatigue (CF) assessment of offshore wind turbines in shallow and deep waters

High strain rate behaviour of nano-quasicrystalline Al93Fe3Cr2Ti2 alloy and composites

We demonstrate the outstanding dynamic strength of nano-quasicrystalline Al93Fe3Cr2Ti2 at% alloy and composites. Unlike most crystalline Al alloys, this alloy exhibits substantial strain rate sensitivity and retains ductility at high strain rates. This opens new pathways for use in safety-critical materials requiring impact resistance

From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury

The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a Controlled Cortical Impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4T MRI two weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in segments of the corpus callosum predicted to have a high strain, indicating white matter changes. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of TBI. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets

Dimensional considerations on the mechanical properties of 3D printed polymer parts

Additive manufacturing offers a useful and accessible tool for prototyping and manufacturing small volume functional parts. Polylactic acid (PLA) and thermoplastic polyurethane (TPU) are amongst the most commonly used materials. Characterising 3D printed PLA and TPU is potentially important for both designing and finite element modelling of functional parts. This work explores the mechanical properties of additively manufactured PLA/TPU specimens with consideration to design parameters including size, and infill percentage. PLA/TPU specimens are 3D-printed in selected ISO standard geometries with 20%, 60%, 100% infill percentage. Tensile and compression test results suggest that traditional ISO testing standards might be insufficient in characterising 3D printed materials for finite element modelling or application purposes. Infill percentage in combination to design size, may significantly affect the mechanical performance of 3D printed parts. Dimensional variation may cause inhomo-geneity in mechanical properties between large and small cross section areas of the same part. The effect was reduced in small cross section parts where reducing the nominal infill had less effect on the resulting specimens. The results suggest that for 3D printed functional parts with significant dimensional differences between sections, the material properties are not necessarily homogeneous. This consideration may be significant for designers using 3D printing for applications, which include mechanical loading

Modelling Stochastic Foam Geometries for FE Simulations Using 3D Voronoi Cells

A method for generating realistic foam geometries is developed for modelling the structure of stochastic foams. The method employs 3D Voronoi cells as pores. The virtual geometries are subjected to loading with the use of finite element methods and the results are compared to experimental data for open cell Titanium foams. The method applies statistical control to geometrical characteristics and it's used to either replicate or virtually generate prototype foam structures

Measurements and micro-mechanical modelling of the response of sintered titanium foams.

Titanium foams of relative density in the range 0.35-0.50 are tested in quasi-static compression, tension and shear. The response is ductile in compression but brittle, and weaker, in shear and tension. Virtual foam microstructures are generated by an algorithm based on Voronoi tessellation of three-dimensional space, capable of reproducing the measured size distribution of the pores in the foam. Finite Element (FE) simulations are conducted to explore the mechanical response of the material, by analysing the elasto-plastic response of a statistical volume element (SVE). The simulations correctly predict the ductile compressive response and its dependence on relative density

The compressive response of a titanium foam at low and high strain rates

Sintered titanium powder and titanium foams of relative density ranging from 0.3 to 0.9 were produced by powder metallurgy routes and tested in uniaxial compression at low, medium and high rates of strain. At all strain rates, the foams deform by plastic collapse of the pores, accompanied by micro-cracking at compressive strains exceeding 0.2. The foams investigated are strain rate sensitive, with both the yield stress and the strain hardening rate increasing with applied strain rate. The strain rate sensitivity is more pronounced for foams of lower relative density. \ua9 2010 Springer Science+Business Media, LLC.Peer reviewed: YesNRC publication: Ye