This study investigates the mechanical and geometrical attributes of egg–box energy absorbing structures as crash safety barriers in the automotive industry. The research herein was originated from the earlier work of Prof. Shirvani, patented and further investigated by Cellbond Composites Ltd. who has invested in further research, for developing an analytical tool for geometric optimisation as an enhanced resolution to various shapes and materials. Energy absorption in egg-box occurs through plastic deformation of cell walls, examined through non–linear finite element simulations using ANSYS® and ANSYS/LS–DYNA® FE packages. Experimental dynamic crash tests have been designed to verify the validity of the FE simulations. Geometrical models are defined as 3D graphical representations, outlined in detail. Further, the impact behaviour of commercially pure aluminium egg-box energy absorbers is studied to identify the optimum design parameters describing the geometry of the structure. A simulation-based multi-objective optimisation strategy is employed to find a set of Pareto-optimal solutions where each solution represents a trade-off point with respect to the two conflicting objectives: the maximum impact force and the energy absorption capacity of the structure. The aim is to simultaneously minimise the former and maximise the latter, in the attempt to find purpose–specific optimal egg–box geometries. In light of the associated outcomes, it is shown that egg–box geometries with < ω ), thin walls (t < 1mm), short inter–peak distances and small peak diameters. M – < ω ), thin walls (t < 1mm), lengthy inter–peak distances and smaller peak diameters. It is concluded that, egg–box structures combined in the form of sandwich panels can be designed per application to act as optimised energy absorbers. Results of the proposed optimised sandwich structure are verified using analytical techniques.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:629593 |
| Date | January 2013 |
| Creators | Sanaei, Maryam |
| Publisher | Anglia Ruskin University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://arro.anglia.ac.uk/333203/ |
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