Phase field study of the tip operating state of a freely growing dendrite against convection using a novel parallel multigrid approach

Alloy dendrite growth during solidification with coupled thermal-solute-convection fields has been studied by phase field modeling and simulation. The coupled transport equations were solved using a novel parallel-multigrid numerical approach with high computational efficiency that has enabled the investigation of dendrite growth with realistic alloy values of Lewis number ∼104 and Prandtl number ∼10−2. The detailed dendrite tip shape and character were compared with widely recognized analytical approaches to show validity, and shown to be highly dependent on undercooling, solute concentration and Lewis number. In a relatively low flow velocity regime, variations in the ratio of growth selection parameter with and without convection agreed well with theory

A reanalysis of ozone on Mars from assimilation of SPICAM observations

We have assimilated for the first time SPICAM retrievals of total ozone into a Martian global circulation model to provide a global reanalysis of the ozone cycle. Disagreement in total ozone between model prediction and assimilation is observed between 45°S–10°S from LS=135–180° and at northern polar (60°N–90°N) latitudes during northern fall (LS=150–195°). Large percentage differences in total ozone at northern fall polar latitudes identified through the assimilation process are linked with excessive northward transport of water vapour west of Tharsis and over Arabia Terra. Modelling biases in water vapour can also explain the underestimation of total ozone between 45°S–10°S from LS=135–180°. Heterogeneous uptake of odd hydrogen radicals are unable to explain the outstanding underestimation of northern polar total ozone in late northern fall. Assimilation of total ozone retrievals results in alterations of the modelled spatial distribution of ozone in the southern polar winter high altitude ozone layer. This illustrates the potential use of assimilation methods in constraining total ozone where SPICAM cannot observe, in a region where total ozone is especially important for potential investigations of the polar dynamics

Comparison of a grid-based CFD method and vortex dynamics predictions of low Reynolds number cylinder flow

Computational fluid dynamics models range from the finite difference type grid-based method to the Lagrangian style vortex cloud simulation technique for solving the Navier-Stokes equations. This paper undertakes a comparison of these two methods for the classical datum bluff body case of flow past a stationary circular cylinder at low Reynolds numbers in the range 10 to 220. Comparisons include time-history, time-mean and root-mean-square values of oscillating drag and lift coefficients, frequency of vortex shedding and related vortex street wake flow patterns. Particularly close agreement was obtained for Strouhal number versus Reynolds number, and good agreement for time-mean value of drag coefficients; comparison was also made with experimental results. Attempts are also made to calculate the skin friction and surface pressure components of the cylinder drag, revealing the significance of skin friction drag within this range and its relative insignificance above a Reynolds number of 220

Modeling and estimation of multi-source clustering in crime and security data

While the presence of clustering in crime and security event data is well established, the mechanism(s) by which clustering arises is not fully understood. Both contagion models and history independent correlation models are applied, but not simultaneously. In an attempt to disentangle contagion from other types of correlation, we consider a Hawkes process with background rate driven by a log Gaussian Cox process. Our inference methodology is an efficient Metropolis adjusted Langevin algorithm for filtering of the intensity and estimation of the model parameters. We apply the methodology to property and violent crime data from Chicago, terrorist attack data from Northern Ireland and Israel, and civilian casualty data from Iraq. For each data set we quantify the uncertainty in the levels of contagion vs. history independent correlation.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS647 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Reactive point processes: A new approach to predicting power failures in underground electrical systems

Reactive point processes (RPPs) are a new statistical model designed for predicting discrete events in time based on past history. RPPs were developed to handle an important problem within the domain of electrical grid reliability: short-term prediction of electrical grid failures ("manhole events"), including outages, fires, explosions and smoking manholes, which can cause threats to public safety and reliability of electrical service in cities. RPPs incorporate self-exciting, self-regulating and saturating components. The self-excitement occurs as a result of a past event, which causes a temporary rise in vulner ability to future events. The self-regulation occurs as a result of an external inspection which temporarily lowers vulnerability to future events. RPPs can saturate when too many events or inspections occur close together, which ensures that the probability of an event stays within a realistic range. Two of the operational challenges for power companies are (i) making continuous-time failure predictions, and (ii) cost/benefit analysis for decision making and proactive maintenance. RPPs are naturally suited for handling both of these challenges. We use the model to predict power-grid failures in Manhattan over a short-term horizon, and to provide a cost/benefit analysis of different proactive maintenance programs.Comment: Published at http://dx.doi.org/10.1214/14-AOAS789 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org