Model sensitivity and uncertainty analysis using roadside air quality measurements

Most of the air quality modelling work has been so far oriented towards deterministic simulations of ambient pollutant concentrations. This traditional approach, which is based on the use of one selected model and one data set of discrete input values, does not reflect the uncertainties due to errors in model formulation and input data. Given the complexities of urban environments and the inherent limitations of mathematical modelling, it is unlikely that a single model based on routinely available meteorological and emission data will give satisfactory short-term predictions. In this study, different methods involving the use of more than one dispersion model, in association with different emission simulation methodologies and meteorological data sets, were explored for predicting best CO and benzene estimates, and related confidence bounds. The different approaches were tested using experimental data obtained during intensive monitoring campaigns in busy street canyons in Paris, France. Three relative simple dispersion models (STREET, OSPM and AEOLIUS) that are likely to be used for regulatory purposes were selected for this application. A sensitivity analysis was conducted in order to identify internal model parameters that might significantly affect results. Finally, a probabilistic methodology for assessing urban air quality was proposed.

Uncertainty analysis to minimise risk in designing micro-electronics manufacturing processes

A design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the process control of micro and nano-electronics based manufacturing processes is presented in this paper. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to help understand how a pre-defined geometry of micro- and nano- structures can be achieved using this technology. The process performance is characterised on the basis of developed Reduced Order Models (ROM) and are generated using results from a mathematical model of the Focused Ion Beam and Design of Experiment (DoE) methods. Two ion beam sources, Argon and Gallium ions, have been used to compare and quantify the process variable uncertainties that can be observed during the milling process. The evaluations of the process performance takes into account the uncertainties and variations of the process variables and are used to identify their impact on the reliability and quality of the fabricated structure. An optimisation based design task is to identify the optimal process conditions, by varying the process variables, so that certain quality objectives and requirements are achieved and imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

Production of lightweight aggregate from industrial waste and carbon dioxide

The concomitant recycling of waste and carbon dioxide emissions is the subject of developing technology designed to close the industrial process loop and facilitate the bulk-re-use of waste in, for example, construction. The present work discusses a treatment step that employs accelerated carbonation to convert gaseous carbon dioxide into solid calcium carbonate through a reaction with industrial thermal residues. Treatment by accelerated carbonation enabled a synthetic aggregate to be made from thermal residues and waste quarry fines. The aggregates produced had a bulk density below 1000 kg/m3 and a high water absorption capacity. Aggregate crushing strengths were between 30% and 90% stronger than the proprietary lightweight expanded clay aggregate available in the UK. Cast concrete blocks containing the carbonated aggregate achieve compressive strengths of 24 MPa, making them suitable for use with concrete exposed to non-aggressive service environments. The energy intensive firing and sintering processes traditionally required to produce lightweight aggregates can now be augmented by a cold-bonding, low energy method that contributes to the reduction of green house gases to the atmosphere.

The use of mineral trioxide aggregate in endodontics - status report

Mineral trioxide aggregate (MTA) is a clinical product comprising a mixture of Portland cement and bismuth oxide which is currently used as a root−filling material in dentistry. It has good biological compatibility, is capable of promoting both osteogenesis and cementogensis, and is finding increasing use in endodontic therapy. It is dimensionally stable, and provides an acceptable and durable seal for endodontically treated teeth. This article reviews the chemistry and applications of MTA, and highlights the fact that very little is currently known about the hydration chemistry, phase evolution and stability of this cement in physiological environments. However, biological effects of MTA have been well documented and are considered in detail. The article concludes that this material is a useful addition to the range of materials available for clinical application in endodontics.