Mechanical behaviour of electrospun fibre-reinforced hydrogels.

Mechanically robust and biomimicking scaffolds are needed for structural engineering of tissues such as the intervertebral disc, which are prone to failure and incapable of natural healing. Here, the formation of thick, randomly aligned polycaprolactone electrospun fibre structures infiltrated with alginate is reported. The composites are characterised using both indentation and tensile testing and demonstrate substantially different tensile and compressive moduli. The composites are mechanically robust and exhibit large strains-to-failure, exhibiting toughening mechanisms observed in other composite material systems. The method presented here provides a way to create large-scale biomimetic scaffolds that more closely mimic the composite structure of natural tissue, with tuneable tensile and compressive properties via the fibre and matrix phases, respectively.

Mechanical behaviour of electrospun fibre-reinforced hydrogels

Mechanically robust and biomimicking scaffolds are needed for structural engineering of tissues such as the intervertebral disc, which are prone to failure and incapable of natural healing. Here, the formation of thick, randomly aligned polycaprolactone electrospun fibre structures infiltrated with alginate is reported. The composites are characterised using both indentation and tensile testing and demonstrate substantially different tensile and compressive moduli. The composites are mechanically robust and exhibit large strains-to-failure, exhibiting toughening mechanisms observed in other composite material systems. The method presented here provides a way to create large-scale biomimetic scaffolds that more closely mimic the composite structure of natural tissue, with tuneable tensile and compressive properties via the fibre and matrix phases, respectively. © 2014 Springer Science+Business Media New York.

Achievements and challenges in machine vision-based inspection of large concrete structures

Large concrete structures need to be inspected in order to assess their current physical and functional state, to predict future conditions, to support investment planning and decision making, and to allocate limited maintenance and rehabilitation resources. Current procedures in condition and safety assessment of large concrete structures are performed manually leading to subjective and unreliable results, costly and time-consuming data collection, and safety issues. To address these limitations, automated machine vision-based inspection procedures have increasingly been proposed by the research community. This paper presents current achievements and open challenges in vision-based inspection of large concrete structures. First, the general concept of Building Information Modeling is introduced. Then, vision-based 3D reconstruction and as-built spatial modeling of concrete civil infrastructure are presented. Following that, the focus is set on structural member recognition as well as on concrete damage detection and assessment exemplified for concrete columns. Although some challenges are still under investigation, it can be concluded that vision-based inspection methods have significantly improved over the last 10 years, and now, as-built spatial modeling as well as damage detection and assessment of large concrete structures have the potential to be fully automated.