Abstract:Additively manufactured (AM) conformal cooling channels are currently the state of the art for high performing tooling with reduced cycle times. This paper introduces the concept of conformal cooling layers which challenges the status quo in providing higher heat transfer rates that also provide less variation in tooling temperatures.The cooling layers are filled with self-supporting repeatable unit cells that form a lattice throughout the cooling layers. The lattices increase fluid vorticity which improves convective heat transfer.Mechanical testing of the lattices shows that the design of the unit cell significantly varies the compression characteristics.A virtual case study of the injection moulding of a plastic enclosure is used to compare the performance of conformal cooling layers with that of conventional (drilled) cooling channels and conformal (AM) cooling channels. The results show the conformal layers reduce cooling time by 26.34% over conventional cooling channels.

Abstract:Additive manufacturing (AM) provides many benefits such as reduced manufacturing lead times, streamlined supply chains, part consolidation, structural optimisation and improved buyto-fly ratios. Barriers to adoption include high material and processing costs, low build rates, isotropic material properties, and variable processing conditions. Currently AM polymer parts are far less expensive to manufacture than AM metal parts, therefore improving the properties of polymer parts is highly desirable. This paper introduces a design methodology used to integrate continuous reinforcement into AM polymer parts with the aim of improving their mechanical properties. The method is validated with the design and testing of three case studies, a pulley housing, hook and universal joint used to demonstrate the applicability of the method for tensile, bending and torsion loading types respectively.Physical testing showed that it was possible to improve the strength of parts by over 4000%,

Abstract:Electrospinning is a relatively simple method of producing nanofibres. Currently there is no method to predict the characteristics of electrospun fibres for a wide range of polymer/solvent combinations and concentrations without first measuring a number of solution properties. This paper shows how artificial neural networks can be trained to make electrospinning predictions using only commonly available prior knowledge of the polymer and solvent. Firstly, a probabilistic neural network was trained to predict the classification of three possibilities; no fibres (electrospraying), beaded fibres and smooth fibres with over 80% correct predictions. Secondly, a generalised neural network was trained to predict fibre diameter with an average absolute percentage error of 22.3% for the validation data. These predictive tools can be used to reduce the parameter space prior to scoping exercises. Graphical Abstract:Predicted versus measured electrospun-fibre diameter from an artificial neural network trained using data from 13 different polymer/solvent combinations from over 20 independent studies.

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Current additive rapid prototyping technologies fail to efficiently produce objects greater than 0.5m³ due to restrictions in build size and build time. Conversely large hot-wire cutting machines, able to cut large objects, often lack the ability to create surfaces with complex geometrical features. Therefore there is a need to develop rapid prototyping and manufacturing technologies capable of producing large objects in a rapid manner directly from CAD data. Large sized freeform objects made of soft materials, such as polystyrene foam, have numerous uses including; conceptual design of commercial products, automotive design, aerodynamic and hydrodynamic testing, advertising, film making, medical supports, sporting equipment and props for the entertainment industry. Plastic foam cutting rapid prototyping is a relatively new technology capable of producing large plastic foam objects directly from CAD data. This paper will describe nine such technologies that have been developed or are currently being developed at institutions around the world.