Sustainability Enhancement of a Turbine Vane Manufacturing Cell through Digital Simulation based Design

Modern manufacturing systems should satisfy emerging needs related to sustainable development. The design of sustainable manufacturing systems can be valuably supported by simulation, traditionally employed mainly for time and cost reduction. In this paper, a multi-purpose digital simulation approach is proposed to deal with sustainable manufacturing systems design through Discrete Event Simulation (DES) and 3D digital human modelling. DES models integrated with data on power consumption of the manufacturing equipment are utilized to simulate different scenarios with the aim to improve productivity as well as energy efficiency, avoiding resource and energy waste. 3D simulation based on digital human modelling is employed to assess human factors issues related to ergonomics and safety of manufacturing systems. The approach is implemented for the sustainability enhancement of a real manufacturing cell of the aerospace industry, automated by robotic deburring. Alternative scenarios are proposed and simulated, obtaining a significant improvement in terms of energy efficiency (−87%) for the new deburring cell, and a reduction of energy consumption around −69% for the coordinate measuring machine, with high potential annual energy cost savings and increased energy efficiency. Moreover, the simulation-based ergonomic assessment of human operator postures allows 25% improvement of the workcell ergonomic index.

In Vitro modelling of RSV infection and cytopathogenesis in well-differentiated human primary airway epithelial cells (WD-PAECs).

The choice of model used to study human respiratory syncytial virus (RSV) infection is extremely important. RSV is a human pathogen that is exquisitely adapted to infection of human hosts. Rodent models, such as mice and cotton rats, are semi-permissive to RSV infection and do not faithfully reproduce hallmarks of RSV disease in humans. Furthermore, immortalized airway-derived cell lines, such as HEp-2, BEAS-2B, and A549 cells, are poorly representative of the complexity of the respiratory epithelium. The development of a well-differentiated primary pediatric airway epithelial cell models (WD-PAECs) allows us to simulate several hallmarks of RSV infection of infant airways. They therefore represent important additions to RSV pathogenesis modeling in human-relevant tissues. The following protocols describe how to culture and differentiate both bronchial and nasal primary pediatric airway epithelial cells and how to use these cultures to study RSV cytopathogenesis.

Efficient Genotyping of KRAS Mutant Non-Small Cell Lung Cancer Using a Multiplexed Droplet Digital PCR Approach.

Droplet digital PCR (ddPCR) can be used to detect low frequency mutations in oncogene-driven lung cancer. The range of KRAS point mutations observed in NSCLC necessitates a multiplex approach to efficient mutation detection in circulating DNA. Here we report the design and optimisation of three discriminatory ddPCR multiplex assays investigating nine different KRAS mutations using PrimePCR™ ddPCR™ Mutation Assays and the Bio-Rad QX100 system. Together these mutations account for 95% of the nucleotide changes found in KRAS in human cancer. Multiplex reactions were optimised on genomic DNA extracted from KRAS mutant cell lines and tested on DNA extracted from fixed tumour tissue from a cohort of lung cancer patients without prior knowledge of the specific KRAS genotype. The multiplex ddPCR assays had a limit of detection of better than 1 mutant KRAS molecule in 2,000 wild-type KRAS molecules, which compared favourably with a limit of detection of 1 in 50 for next generation sequencing and 1 in 10 for Sanger sequencing. Multiplex ddPCR assays thus provide a highly efficient methodology to identify KRAS mutations in lung adenocarcinoma.

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 2 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.