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.

Coupled fire/evacuation analysis of the Station Nightclub fire

In this paper, coupled fire and evacuation simulation tools are used to simulate the Station Nightclub fire. This study differs from the analysis conducted by NIST in three key areas; (1)an enhanced flame spread model and (2)a toxicity generation model are used, (3)the evacuation is coupled to the fire simulation. Predicted early burning locations in the full-scale fire simulation are in line with photographic evidence and the predicted onset of flashover is similar to that produced by NIST. However, it is suggested that both predictions of the flashover time are approximately 15 sec earlier than actually occurred. Three evacuation scenarios are then considered, two of which are coupled with the fire simulation. The coupled fire and evacuation simulation suggests that 180 fatalities result from a building population of 460. With a 15 sec delay in the fire timeline, the evacuation simulation produces 84 fatalities which are in good agreement with actual number of fatalities. An important observation resulting from this work is that traditional fire engineering ASET/RSET calculations which do not couple the fire and evacuation simulations have the potential to be considerably over optimistic in terms of the level of safety achieved by building designs.

A framework for state-based time-series analysis and prediction

Time-series analysis and prediction play an important role in state-based systems that involve dealing with varying situations in terms of states of the world evolving with time. Generally speaking, the world in the discourse persists in a given state until something occurs to it into another state. This paper introduces a framework for prediction and analysis based on time-series of states. It takes a time theory that addresses both points and intervals as primitive time elements as the temporal basis. A state of the world under consideration is defined as a set of time-varying propositions with Boolean truth-values that are dependent on time, including properties, facts, actions, events and processes, etc. A time-series of states is then formalized as a list of states that are temporally ordered one after another. The framework supports explicit expression of both absolute and relative temporal knowledge. A formal schema for expressing general time-series of states to be incomplete in various ways, while the concept of complete time-series of states is also formally defined. As applications of the formalism in time-series analysis and prediction, we present two illustrating examples.

An analysis of masculine and feminine writings in postings within a series of health and social care online undergraduate courses

This study aims to extend understanding of pedagogic dialogue by analysing the effect that the gender of the student has on interaction within a selection of ordinary health and social care on line courses.