Roadmapping in industrial companies: Experiences

From its origins in the US electronics sector in the 1970s, technology roadmapping has been adapted (and adopted) widely, for many different innovation, strategy and policy applications. Communication is commonly cited as one of the key benefi ts of roadmapping, particularly in terms of the process that brings different organizational perspectives together, with the roadmap providing a common visual 'language'. There is signifi cant demand for methods that are agile, in the sense of being rapid, flexible and effective to apply, focused on strategic decisions and actions. 'Fast-start' roadmapping workshop techniques enable key stakeholders to address strategic issues efficiently using the visual structure of roadmaps to capture, discuss, prioritize, explore and communicate. This paper presents the learning from a set of five diverse applications of the fast-start approach in the Basque Country, which demonstrate the agility of the technique.

Multi-dimensional conditional moment closure modelling applied to a heavy-duty common-rail diesel engine

A multi-dimensional combustion code implementing the Conditional Moment Closure turbulent combustion model interfaced with a well-established RANS two- phase flow field solver has been employed to study a broad range of operating conditions for a heavy duty direct-injection common-rail Diesel engine. These conditions include different loads (25%, 50%, 75% and full load) and engine speeds (1250 and 1830 RPM) and, with respect to the fuel path, different injection timings and rail pressures. A total of nine cases have been simulated. Excellent agreement with experimental data has been found for the pressure traces and the heat release rates, without adjusting any model constants. The chemical mechanism used contains a detailed NOx sub-mechanism. The predicted emissions agree reasonably well with the experimental data considering the range of operating points and given no adjustments of any rate constants have been employed. In an effort to identify CPU cost reduction potential, various dimensionality reduction strategies have been assessed. Furthermore, the sensitivity of the predictions with respect to resolution in particular relating to the CMC grid has been investigated. Overall, the results suggest that the presented modelling strategy has considerable predictive capability concerning Diesel engine combustion without requiring model constant calibration based on experimental data. This is true particularly for the heat release rates predictions and, to a lesser extent, for NOx emissions where further progress is still necessary. © 2009 SAE International.