Browsing by Subject "Monte Carlo method"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Field Study of Driver Behavior at Permitted Left-Turn Indications
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2013-03) Davis, Gary A.; Mudgal, Abhisek
    A digital video camera was used to record left-turning vehicles and through vehicles at an urban intersection. A total of 39 left-turn events, with a total of 195 gap decisions, were identified and vehicle trajectories corresponding to those were extracted from the video and transformed into real coordinates using photogrammetry. Bayes estimates of each opposing vehicle’s distance, speed, and time-to-arrival were then computed from the trajectories and used as predictors in logit models of acceptance/rejection decisions. It was found, when models are penalized for the numbers of their parameters, that arrival time, the ratio of initial distance to initial speed, was best predictor. This contrasts with an earlier study that found distance clearly superior to arrival time. This may be due to the fact that in the current study, speeds and initial distances were substantially higher than in the earlier study.
  • Thumbnail Image
    Item
    Instability patterns of evaporative dendrimer deposits.
    (2012-08) Jung, Narina
    The purpose of this project is to understand the instability mechanism behind dendrimer pattern formation in evaporating micro-meter size droplets. Evaporation of droplets of alcohol-dendrimer solution leaves a unique solute pattern on a substrate, where the detailed structure depends on the system variables. We are interested in developing a theory of the morphology of the dendrimer deposits that encompasses evaporation effects, solvent hydrodynamics, and solute particle chemistry. Our approach is to consider a two-dimensional coarse-grained model of dendrimer particle deposition that involves two mechanisms: transfer of solute particles by a convective flow and an inter-particle attraction competing with the convective flow. The configuration of a drying droplet is determined by the distribution of particles on a substrate and the volume fraction of them in a droplet. The Hamiltonian of each configuration is defined to account for both a convective flow and an inter-particle attraction. The evolution of the Hamiltonian is computed by Monte Carlo method to simulate the dendrimer pattern formation and associate patterns with system parameters. We found four basic regimes of morphologies that range from ringlike, wavelike, and fingerlike to islandlike patterns depending on the number of particles and the relative strength of a convective flow and an interaction.