The conceptual development of a simple scale-adaptive reactive pollutant dispersion model

The paper develops the basis for a self-consistent, operationally useful, reactive pollutant dispersion model, for application in urban environments. The model addresses the multi-scale nature of the physical and chemical processes and the interaction between the different scales. The methodology builds on existing techniques of source apportionment in pollutant dispersion and on reduction techniques of detailed chemical mechanisms. © 2005 Published by Elsevier Ltd.

Redesigning the design process through interactive simulation: A case study of life-cycle engineering in jet engine conceptual design

Many aerospace companies are currently making the transition to providing fully-integrated product-service offerings in which their products are designed from the outset with life-cycle considerations in mind. Based on a case study at Rolls-Royce, Civil Aerospace, this paper demonstrates how an interactive approach to process simulation can be used to support the redesign of existing design processes in order to incorporate life-cycle engineering (LCE) considerations. The case study provides insights into the problems of redesigning the conceptual stages of a complex, concurrent engineering design process and the practical value of process simulation as a tool to support the specification of process changes in the context of engineering design. The paper also illustrates how development of a simulation model can provide significant benefit to companies through the understanding of process behaviour that is gained through validating the behaviour of the model using different design and iteration scenarios. Keywords: jet engine design; life-cycle engineering; LCE; process change; design process simulation; applied signposting model; ASM. Copyright © 2011 Inderscience Enterprises Ltd.

Industrial ecology at factory level - A conceptual model

Growing environmental concerns caused by natural resource depletion and pollution need to be addressed. One approach to these problems is Sustainable Development, a key concept for our society to meet present as well as future needs worldwide. Manufacturing clearly has a major role to play in the move towards a more sustainable society. However it appears that basic principles of environmental sustainability are not systematically applied, with practice tending to focus on local improvements. The aim of the work presented in this paper is to adopt a more holistic view of the factory unit to enable opportunities for wider improvement. This research analyses environmental principles and industrial practice to develop a conceptual manufacturing ecosystem model as a foundation to improve environmental performance. The model developed focuses on material, energy and waste flows to better understand the interactions between manufacturing operations, supporting facilities and surrounding buildings. The research was conducted in three steps: (1) existing concepts and models for industrial sustainability were reviewed and environmental practices in manufacturing were collected and analysed; (2) gaps in knowledge and practice were identified; (3) the outcome is a manufacturing ecosystem model based on industrial ecology (IE). This conceptual model has novelty in detailing IE application at factory level and integrating all resource flows. The work is a base on which to build quantitative modelling tools to seek integrated solutions for lower resource input, higher resource productivity, fewer wastes and emissions, and lower operating cost within the boundary of a factory unit. © 2012 Elsevier Ltd. All rights reserved.

Language model combination and adaptation using weighted finite state transducers

In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaptation may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences. ©2010 IEEE.