Jahrul Alam
| Associate Professor of Mathematics Office: HH-3054 |
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I obtained PhD in Applied Mathematics with a specialization on Turbulence at the McMaster University in 2006. Since then I spent one and a half years at the Department of Earth and Environmental Sciences, University of Waterloo as a SHARCNET post-doctoral fellow in Atmospheric modelling. I joined as an Assistant Professor at the Department of Mathematics and Statistics, Memorial University in the summer of 2008. My current scientific interests concern modelling, computing, and understanding Fluid Dynamics problems that are challenging in environmental, aeronautical, and industrial applications. More specifically, I focus on integrating dynamically adaptive mesh refinement techniques with Computational Fluid Dynamics to develop an integrated modelling and computing framework for an improved understanding of global warming and climate change issues. This includes the development and verification of high resolution computational models and adaptive parameterization techniques. Environmental i.e. geophysical flows are characterized by a wide range of length and time scales, and modern computing resources are unable to compute such flows directly from the largest scale down to the smallest scale. However, researchers have claimed that such turbulent flows are extremely intermittent in space and time. This means that only a fraction of the flow is significant. However, it is not yet known how the space-time interemittency links with non-dimensional flow parameters such as the Reynolds number, and how to capture only the most significant portion of a flow, although several attempts have been taken. I use mathematical tools such as nonlinear approximation and wavelet theory to develop a model of turbulent flow, which discards dynamically the non-significant portion of the motion. Further details of this approach can be found in my home page ( http://www.math.mun.ca/~alamj/.) |
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