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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.

Variability in composite manufacture and the limitations in positional accuracy of common industrial robots have hampered automation of assembly tasks within aircraft manufacturing. One way to handle geometry variations and robot compliancy is to use force control. Force control technology utilizes a sensor mounted on the robot to feedback force data to the controller system so instead of being position driven, i.e. programmed to achieve a certain position with the tool, the robot can be programmed to achieve a certain force. This paper presents an experimental case where a compliant rib is aligned to multiple surfaces using force feedback and an industrial robot system from ABB. Two types of ribs where used, one full size carbon fiber rib, and one smaller metal replica for evaluation purposes. The alignment sequence consisted of several iterative steps and a search procedure was implemented within the robot control system.

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.