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A consortium of interested parties has conducted an experimental characterization of two Tau parallel kinematic machines which were built as a part of the EU-funded project, SMErobot1. Characteristics such as machine stiffness, work envelope, repeatability and accuracy were considered. This paper will present a brief history of the Tau parallel machine, the results of this testing and some comment on prospective application to the aerospace industry.

In recent years, interest has been growing in the 2-Stroke Diesel cycle, coupled to high speed engines. One of the most promising applications is on light aircraft piston engines, typically designed to provide a top brake power of 100-200 HP with a relatively low weight. The main advantage yielded by the 2-Stroke cycle is the possibility to achieve high power density at low crankshaft speed, allowing the propeller to be directly coupled to the engine, without a reduction drive. Furthermore, Diesel combustion is a good match for supercharging and it is expected to provide a superior fuel efficiency, in comparison to S.I. engines. However, the coupling of 2-Stroke cycle and Diesel combustion on small bore, high speed engines is quite complex, requiring a suitable support from CFD simulation.

This paper describes the development of a novel data model for storing and sharing data obtained from engine experiments, it then outlines a methodology for automatic model development and applies it to a state-of-the-art engine combustion model (including chemical kinetics) to reduce corresponding model parameter uncertainties with respect engine experiments. These challenges are met by adopting the latest developments in the semantic web to create a shared data model resource for the IC engine development community. The relevant data can be extracted and then used to set-up simulations for parameter estimation by passing it to the relevant application models. A methodology for incorporating experimental and model uncertainties into the model optimization procedure is presented.

The use of Selective Catalytic Reduction (SCR) is becoming increasingly more popular as a way of reducing NOx emissions from heavy duty vehicles while maintaining competitive operating costs. In order to make efficient use of these systems, it's important to have a complete system approach when it comes to calibration of the engine and aftertreatment system. This paper presents a simplified model of a heavy duty SCR catalyst, primarily intended for use in combination with an engine-out emissions model to perform model based offline optimization of the complete system. The traditional way of modelling catalysts using a dense discretization of the catalyst channels and non-linear differential equation solvers to solve the heat and mass balance equations, requires too much computational power in this application. The presented model is also useful in other applications such as model based control.