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Simulation and modeling of fluid flow through porous media are fundamental to numerous fields of study, including chemical and petroleum engineering, hydrology, micro-fluidics, biological transport, textile science, filtration science, and solidification science. The tensor permeability provides the relationship between the pressure gradient and flow rate in these systems, and is crucial to the accurate simulation of many phenomena.
Have you ever desperately needed to sample a probability distribution too complicated or ugly to have been built into MATLAB, but didn't know how? In such situations, Monte Carlo Markov Chains (MCMC) are your Swiss Army Knife. In this Brown Bag talk, I will present some background on MCMC sampling methods to elucidate why they work, and provide some practical knowledge for wielding them as well. I'll demonstrate some of the basic techniques in the ever-popular application of dating models.
Titan exhibits ample surface and crustal processes including lakes and seas, fluvial erosive features, possibly subsurface reservoirs of liquid, and rainfall. Together these constitute strong evidence for a multicomposition hydrological system, composed mostly of methane and ethane as well as trace amounts of other alkanes. Estimates of the volume of liquid methane required in streams and rainfall to produce erosional features suggest that these could be relatively recent phenomena, perhaps periodically renewed as the overall climate cycles between dry and wet periods.