The modeling of turbulent reactive flows based on multiple mapping conditioning

A new modeling approach-multiple mapping conditioning (MMC)-is introduced to treat mixing and reaction in turbulent flows. The model combines the advantages of the probability density function and the conditional moment closure methods and is based on a certain generalization of the mapping closure concept. An equivalent stochastic formulation of the MMC model is given. The validity of the closuring hypothesis of the model is demonstrated by a comparison with direct numerical simulation results for the three-stream mixing problem. (C) 2003 American Institute of Physics.

Evidence and information for health policy: a decade of change

Over the past decade or so, there has been increasing demand for greater clarity about the major causes of disease and injury, how these differentially affect populations, and how they are changing. In part, this demand has been motivated by resource constraints and a realisation that better health is possible with more informed allocation of resources. At the same time, there has been a change in the way population health and its determinants are quantified, with a much closer integration of the quantitative population sciences (such as epidemiology, demography and health economics) to strengthen and broaden the evidence base for healthcare policy.